Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-2881-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-2881-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
07 Apr 2022
Development and technical paper |
| 07 Apr 2022
| 07 Apr 2022
Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1
Pacific Northwest National Laboratory, Richland, Washington, USA
Bryce E. Harrop
Pacific Northwest National Laboratory, Richland, Washington, USA
Vincent E. Larson
Department of Mathematical Sciences, University of
Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
Pacific Northwest National Laboratory, Richland, Washington, USA
Richard B. Neale
National Center for Atmospheric Research, Boulder, Colorado, USA
Andrew Gettelman
National Center for Atmospheric Research, Boulder, Colorado, USA
Hugh Morrison
National Center for Atmospheric Research, Boulder, Colorado, USA
Hailong Wang
Pacific Northwest National Laboratory, Richland, Washington, USA
Kai Zhang
Pacific Northwest National Laboratory, Richland, Washington, USA
Stephen A. Klein
Lawrence Livermore National Laboratory, Livermore, California, USA
Mark D. Zelinka
Lawrence Livermore National Laboratory, Livermore, California, USA
Yuying Zhang
Lawrence Livermore National Laboratory, Livermore, California, USA
Yun Qian
Pacific Northwest National Laboratory, Richland, Washington, USA
Jin-Ho Yoon
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology, Gwangju, South Korea
Christopher R. Jones
Pacific Northwest National Laboratory, Richland, Washington, USA
Meng Huang
Pacific Northwest National Laboratory, Richland, Washington, USA
Sheng-Lun Tai
Pacific Northwest National Laboratory, Richland, Washington, USA
Balwinder Singh
Pacific Northwest National Laboratory, Richland, Washington, USA
Peter A. Bogenschutz
Lawrence Livermore National Laboratory, Livermore, California, USA
Xue Zheng
Lawrence Livermore National Laboratory, Livermore, California, USA
Wuyin Lin
Brookhaven National Laboratory, Upton, New York, USA
Johannes Quaas
Institute for Meteorology, Universität Leipzig, Leipzig, Germany
Hélène Chepfer
LMD/IPSL, Sorbonne Université, École Polytechnique, CNRS, Paris,
France
Michael A. Brunke
Department of Hydrology and Atmospheric Sciences, University of
Arizona, Tucson, Arizona, USA
Xubin Zeng
Department of Hydrology and Atmospheric Sciences, University of
Arizona, Tucson, Arizona, USA
Johannes Mülmenstädt
Pacific Northwest National Laboratory, Richland, Washington, USA
Samson Hagos
Pacific Northwest National Laboratory, Richland, Washington, USA
Zhibo Zhang
Department of Physics, University of Maryland, Baltimore County,
Baltimore, Maryland, USA
Science Systems and Applications, Inc., Lanham, Maryland, USA
Xiaohong Liu
Department of Atmospheric Sciences, Texas A&M University, College
Station, Texas, USA
Michael S. Pritchard
Department of Earth System Science, University of California, Irvine,
California, USA
Pacific Northwest National Laboratory, Richland, Washington, USA
Jingyu Wang
Department of Humanities and Social Studies Education, National Institute of Education, Nanyang Technological University, Singapore, Singapore
Lawrence Livermore National Laboratory, Livermore, California, USA
Peter M. Caldwell
Lawrence Livermore National Laboratory, Livermore, California, USA
Jiwen Fan
Pacific Northwest National Laboratory, Richland, Washington, USA
Larry K. Berg
Pacific Northwest National Laboratory, Richland, Washington, USA
Jerome D. Fast
Pacific Northwest National Laboratory, Richland, Washington, USA
Mark A. Taylor
Sandia National Laboratory, Albuquerque, New Mexico, USA
Jean-Christophe Golaz
Lawrence Livermore National Laboratory, Livermore, California, USA
Shaocheng Xie
Lawrence Livermore National Laboratory, Livermore, California, USA
Philip J. Rasch
Pacific Northwest National Laboratory, Richland, Washington, USA
L. Ruby Leung
Pacific Northwest National Laboratory, Richland, Washington, USA
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Kai Zhang, Wentao Zhang, Hui Wan, Philip J. Rasch, Steven J. Ghan, Richard C. Easter, Xiangjun Shi, Yong Wang, Hailong Wang, Po-Lun Ma, Shixuan Zhang, Jian Sun, Susannah M. Burrows, Manish Shrivastava, Balwinder Singh, Yun Qian, Xiaohong Liu, Jean-Christophe Golaz, Qi Tang, Xue Zheng, Shaocheng Xie, Wuyin Lin, Yan Feng, Minghuai Wang, Jin-Ho Yoon, and L. Ruby Leung
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Shuaiqi Tang, Jerome D. Fast, Kai Zhang, Joseph C. Hardin, Adam C. Varble, John E. Shilling, Fan Mei, Maria A. Zawadowicz, and Po-Lun Ma
Geosci. Model Dev., 15, 4055–4076, https://doi.org/10.5194/gmd-15-4055-2022, https://doi.org/10.5194/gmd-15-4055-2022, 2022
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Susannah M. Burrows, Richard C. Easter, Xiaohong Liu, Po-Lun Ma, Hailong Wang, Scott M. Elliott, Balwinder Singh, Kai Zhang, and Philip J. Rasch
Atmos. Chem. Phys., 22, 5223–5251, https://doi.org/10.5194/acp-22-5223-2022, https://doi.org/10.5194/acp-22-5223-2022, 2022
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Artem G. Feofilov, Hélène Chepfer, Vincent Noël, Rodrigo Guzman, Cyprien Gindre, Po-Lun Ma, and Marjolaine Chiriaco
Atmos. Meas. Tech., 15, 1055–1074, https://doi.org/10.5194/amt-15-1055-2022, https://doi.org/10.5194/amt-15-1055-2022, 2022
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Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
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Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Zhonghua Zheng, Matthew West, Lei Zhao, Po-Lun Ma, Xiaohong Liu, and Nicole Riemer
Atmos. Chem. Phys., 21, 17727–17741, https://doi.org/10.5194/acp-21-17727-2021, https://doi.org/10.5194/acp-21-17727-2021, 2021
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Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. We present a framework for evaluating the error in aerosol mixing state induced by aerosol representation assumptions, which is one of the important contributors to structural uncertainty in aerosol models. Our study provides insights into potential improvements to model process representation for aerosols.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
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Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev., 14, 3067–3077, https://doi.org/10.5194/gmd-14-3067-2021, https://doi.org/10.5194/gmd-14-3067-2021, 2021
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The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth system models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling the representation of the more detailed physics and chemistry at a reduced computational cost while still retaining physical information.
Jingyu Wang, Jiwen Fan, Robert A. Houze Jr., Stella R. Brodzik, Kai Zhang, Guang J. Zhang, and Po-Lun Ma
Geosci. Model Dev., 14, 719–734, https://doi.org/10.5194/gmd-14-719-2021, https://doi.org/10.5194/gmd-14-719-2021, 2021
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This paper presents an evaluation of the E3SM model against NEXRAD radar observations for the warm seasons during 2014–2016. The COSP forward simulator package is implemented in the model to generate radar reflectivity, and the NEXRAD observations are coarsened to the model resolution for comparison. The model severely underestimates the reflectivity above 4 km. Sensitivity tests on the parameters from cumulus parameterization and cloud microphysics do not improve this model bias.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Johannes Mülmenstädt, Edward Gryspeerdt, Marc Salzmann, Po-Lun Ma, Sudhakar Dipu, and Johannes Quaas
Atmos. Chem. Phys., 19, 15415–15429, https://doi.org/10.5194/acp-19-15415-2019, https://doi.org/10.5194/acp-19-15415-2019, 2019
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The effect of aerosol–cloud interactions (ACIs) on Earth's energy budget continues to be highly uncertain. We decompose the effective radiative forcing by ACIs (ERFaci) into the instantaneous forcing due to anthropogenic increases in the number of cloud droplets and fast responses of cloud properties to the droplet number perturbation in the ECHAM–HAMMOZ aerosol–climate model. This decomposition maps onto the IPCC's Fifth Assessment Report analysis of ERFaci more directly than previous work.
Zhibo Zhang, Hua Song, Po-Lun Ma, Vincent E. Larson, Minghuai Wang, Xiquan Dong, and Jianwu Wang
Atmos. Chem. Phys., 19, 1077–1096, https://doi.org/10.5194/acp-19-1077-2019, https://doi.org/10.5194/acp-19-1077-2019, 2019
Hua Song, Zhibo Zhang, Po-Lun Ma, Steven Ghan, and Minghuai Wang
Geosci. Model Dev., 11, 3147–3158, https://doi.org/10.5194/gmd-11-3147-2018, https://doi.org/10.5194/gmd-11-3147-2018, 2018
Kai Zhang, Philip J. Rasch, Mark A. Taylor, Hui Wan, Ruby Leung, Po-Lun Ma, Jean-Christophe Golaz, Jon Wolfe, Wuyin Lin, Balwinder Singh, Susannah Burrows, Jin-Ho Yoon, Hailong Wang, Yun Qian, Qi Tang, Peter Caldwell, and Shaocheng Xie
Geosci. Model Dev., 11, 1971–1988, https://doi.org/10.5194/gmd-11-1971-2018, https://doi.org/10.5194/gmd-11-1971-2018, 2018
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The conservation of total water is an important numerical feature for global Earth system models. Even small conservation problems in the water budget can lead to systematic errors in century-long simulations for sea level rise projection. This study quantifies and reduces various sources of water conservation error in the atmosphere component of the Energy Exascale Earth System Model.
Tianyi Fan, Xiaohong Liu, Po-Lun Ma, Qiang Zhang, Zhanqing Li, Yiquan Jiang, Fang Zhang, Chuanfeng Zhao, Xin Yang, Fang Wu, and Yuying Wang
Atmos. Chem. Phys., 18, 1395–1417, https://doi.org/10.5194/acp-18-1395-2018, https://doi.org/10.5194/acp-18-1395-2018, 2018
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We found that 22–28 % of the low AOD bias in eastern China simulated by the Community Atmosphere Model version 5 can be improved by using a new emission inventory. The concentrations of primary aerosols are closely related to the emission, while the seasonal variations of secondary aerosols depend more on atmospheric processes. This study highlights the importance of improving both the emission and atmospheric processes in modeling the atmospheric aerosols and their radiative effects.
Yang Yang, Hailong Wang, Steven J. Smith, Richard Easter, Po-Lun Ma, Yun Qian, Hongbin Yu, Can Li, and Philip J. Rasch
Atmos. Chem. Phys., 17, 8903–8922, https://doi.org/10.5194/acp-17-8903-2017, https://doi.org/10.5194/acp-17-8903-2017, 2017
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Sulfate has significant impacts on air quality and climate. Local sulfate pollution could result from remote influences, making domestic mitigation efforts inefficient. Using CESM with a sulfur source-tagging technique, we found that, over regions with relatively low emissions, sulfate concentrations are primarily attributed to non-local sources and sulfate indirect radiative forcing over the Southern Hemisphere is more sensitive to emission perturbation than the polluted Northern Hemisphere.
Yang Yang, Hailong Wang, Steven J. Smith, Po-Lun Ma, and Philip J. Rasch
Atmos. Chem. Phys., 17, 4319–4336, https://doi.org/10.5194/acp-17-4319-2017, https://doi.org/10.5194/acp-17-4319-2017, 2017
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The source attributions of black carbon (BC) in China are quantified using the Community Earth System Model by source tagging. BC impacts neighboring regions greatly. Transport is important in increasing BC during regional polluted days. Emissions outside China contribute 35 % of BC direct radiative forcing in China. Efficiency analysis shows that reduction in BC emissions over eastern China could have a greater benefit for regional air quality in China, especially in the winter haze season.
N. I. Kristiansen, A. Stohl, D. J. L. Olivié, B. Croft, O. A. Søvde, H. Klein, T. Christoudias, D. Kunkel, S. J. Leadbetter, Y. H. Lee, K. Zhang, K. Tsigaridis, T. Bergman, N. Evangeliou, H. Wang, P.-L. Ma, R. C. Easter, P. J. Rasch, X. Liu, G. Pitari, G. Di Genova, S. Y. Zhao, Y. Balkanski, S. E. Bauer, G. S. Faluvegi, H. Kokkola, R. V. Martin, J. R. Pierce, M. Schulz, D. Shindell, H. Tost, and H. Zhang
Atmos. Chem. Phys., 16, 3525–3561, https://doi.org/10.5194/acp-16-3525-2016, https://doi.org/10.5194/acp-16-3525-2016, 2016
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Processes affecting aerosol removal from the atmosphere are not fully understood. In this study we investigate to what extent atmospheric transport models can reproduce observed loss of aerosols. We compare measurements of radioactive isotopes, that attached to ambient sulfate aerosols during the 2011 Fukushima nuclear accident, to 19 models using identical emissions. Results indicate aerosol removal that is too fast in most models, and apply to aerosols that have undergone long-range transport.
X. Liu, P.-L. Ma, H. Wang, S. Tilmes, B. Singh, R. C. Easter, S. J. Ghan, and P. J. Rasch
Geosci. Model Dev., 9, 505–522, https://doi.org/10.5194/gmd-9-505-2016, https://doi.org/10.5194/gmd-9-505-2016, 2016
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In this study, we describe and evaluate a new four-mode version of the Modal Aerosol Module (MAM4) in the Community Atmosphere Model version 5 (CAM5). Compared to the current three-mode version of MAM in CAM5, MAM4 significantly improves the simulation of seasonal variation of BC concentrations in the polar regions, by increasing the BC concentrations in all seasons and particularly in cold seasons.
R. Zhang, H. Wang, D. A. Hegg, Y. Qian, S. J. Doherty, C. Dang, P.-L. Ma, P. J. Rasch, and Q. Fu
Atmos. Chem. Phys., 15, 12805–12822, https://doi.org/10.5194/acp-15-12805-2015, https://doi.org/10.5194/acp-15-12805-2015, 2015
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We use a global climate model with an explicit source tagging technique to quantify contributions of emissions from various geographical regions and sectors to BC in North America. Model results are evaluated against measurements of near-surface and in-snow BC. We found strong spatial variations of BC and its radiative forcing that can be quantitatively attributed to the various source origins, and also identified a significant source of BC in snow that is likely missing in most climate models.
R. Zhang, H. Wang, Y. Qian, P. J. Rasch, R. C. Easter, P.-L. Ma, B. Singh, J. Huang, and Q. Fu
Atmos. Chem. Phys., 15, 6205–6223, https://doi.org/10.5194/acp-15-6205-2015, https://doi.org/10.5194/acp-15-6205-2015, 2015
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We use the CAM5 model with a novel source-tagging technique to characterize the fate of BC particles emitted from various geographical regions and sectors and their transport pathways to the Himalayas and Tibetan Plateau (HTP). We show a comprehensive picture of the seasonal and regional dependence of BC source attributions, and find strong seasonal and spatial variations in BC-in-snow radiative forcing in the HTP that can be quantitatively attributed to the various regional/sectoral sources.
S. Tilmes, J.-F. Lamarque, L. K. Emmons, D. E. Kinnison, P.-L. Ma, X. Liu, S. Ghan, C. Bardeen, S. Arnold, M. Deeter, F. Vitt, T. Ryerson, J. W. Elkins, F. Moore, J. R. Spackman, and M. Val Martin
Geosci. Model Dev., 8, 1395–1426, https://doi.org/10.5194/gmd-8-1395-2015, https://doi.org/10.5194/gmd-8-1395-2015, 2015
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The Community Atmosphere Model (CAM), version 5, is now coupled to extensive tropospheric and stratospheric chemistry, called CAM5-chem, and is available in addition to CAM4-chem in the Community Earth System Model (CESM) version 1.2. Both configurations are well suited as tools for atmospheric chemistry modeling studies in the troposphere and lower stratosphere.
K. Zhang, H. Wan, X. Liu, S. J. Ghan, G. J. Kooperman, P.-L. Ma, P. J. Rasch, D. Neubauer, and U. Lohmann
Atmos. Chem. Phys., 14, 8631–8645, https://doi.org/10.5194/acp-14-8631-2014, https://doi.org/10.5194/acp-14-8631-2014, 2014
P.-L. Ma, P. J. Rasch, J. D. Fast, R. C. Easter, W. I. Gustafson Jr., X. Liu, S. J. Ghan, and B. Singh
Geosci. Model Dev., 7, 755–778, https://doi.org/10.5194/gmd-7-755-2014, https://doi.org/10.5194/gmd-7-755-2014, 2014
C. Zhao, X. Liu, Y. Qian, J. Yoon, Z. Hou, G. Lin, S. McFarlane, H. Wang, B. Yang, P.-L. Ma, H. Yan, and J. Bao
Atmos. Chem. Phys., 13, 10969–10987, https://doi.org/10.5194/acp-13-10969-2013, https://doi.org/10.5194/acp-13-10969-2013, 2013
H. Wang, R. C. Easter, P. J. Rasch, M. Wang, X. Liu, S. J. Ghan, Y. Qian, J.-H. Yoon, P.-L. Ma, and V. Vinoj
Geosci. Model Dev., 6, 765–782, https://doi.org/10.5194/gmd-6-765-2013, https://doi.org/10.5194/gmd-6-765-2013, 2013
Goutam Choudhury, Karoline Block, Mahnoosh Haghighatnasab, Johannes Quaas, Tom Goren, and Matthias Tesche
Atmos. Chem. Phys., 25, 3841–3856, https://doi.org/10.5194/acp-25-3841-2025, https://doi.org/10.5194/acp-25-3841-2025, 2025
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Aerosol particles in the atmosphere increase cloud reflectivity, thereby cooling the Earth. Accurate global measurements of these particles are crucial for estimating this cooling effect. This study compares and harmonizes two newly developed global aerosol datasets, offering insights for their future use and refinement. We identify pristine oceans as a significant source of uncertainty in the datasets and, therefore, in quantifying the role of aerosols in Earth's climate.
Branko Kosović, Sukanta Basu, Jacob Berg, Larry K. Berg, Sue E. Haupt, Xiaoli G. Larsén, Joachim Peinke, Richard J. A. M. Stevens, Paul Veers, and Simon Watson
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-42, https://doi.org/10.5194/wes-2025-42, 2025
Preprint under review for WES
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Most human activity happens in the layer of the atmosphere which extends a few hundred meters to a couple of kilometers above the surface of the Earth. The flow in this layer is turbulent. Turbulence impacts wind power production and turbine lifespan. Optimizing wind turbine performance requires understanding how turbulence affects both wind turbine efficiency and reliability. This paper points to gaps in our knowledge that need to be addressed to effectively utilize wind resources.
Jihun Ryu, Hisu Kim, Shih-Yu Simon Wang, and Jin-Ho Yoon
EGUsphere, https://doi.org/10.5194/egusphere-2025-308, https://doi.org/10.5194/egusphere-2025-308, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Using a neural network model, county-level weather forecasts was achieved in the Western U.S. By combining traditional forecasting data with actual weather observations, the AI system achieved better temperature predictions at local scales. While showed promise for temperature forecasting, it still had difficulty accurately predicting extreme rainfall events. The research advances weather forecasting capabilities, potentially helping communities prepare for severe weather conditions.
Anthony La Luna, Zhibo Zhang, Jianyu Zheng, Qianqian Song, Hongbin Yu, Jiachen Ding, Ping Yang, and Masanori Saito
EGUsphere, https://doi.org/10.5194/egusphere-2025-1117, https://doi.org/10.5194/egusphere-2025-1117, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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The lidar backscattering properties of Asian dust particles were studied using a discrete dipole approximation (DDA) model. Both the lidar ratio (LR) and depolarization ratio (DPR) exhibit an asymptotic trend with dust particle size. Two parameterization schemes were developed: one to estimate the DPR of a single dust particle given its size, and the other to estimate the DPR of dust particles with a lognormal particle size distribution given the effective radius.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Fan Mei, Qi Zhang, Damao Zhang, Jerome D. Fast, Gourihar Kulkarni, Mikhail S. Pekour, Christopher R. Niedek, Susanne Glienke, Israel Silber, Beat Schmid, Jason M. Tomlinson, Hardeep S. Mehta, Xena Mansoura, Zezhen Cheng, Gregory W. Vandergrift, Nurun Nahar Lata, Swarup China, and Zihua Zhu
Atmos. Chem. Phys., 25, 3425–3444, https://doi.org/10.5194/acp-25-3425-2025, https://doi.org/10.5194/acp-25-3425-2025, 2025
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This study highlights the unique capability of the ArcticShark, an uncrewed aerial system, in measuring vertically resolved atmospheric properties. Data from 32 research flights in 2023 reveal seasonal patterns and correlations with conventional measurements. The consistency and complementarity of in situ and remote sensing methods are highlighted. The study demonstrates the ArcticShark’s versatility in bridging data gaps and improving the understanding of vertical atmospheric structures.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Yang Yang, Li You, Hailong Wang, Huimin Li, Pinya Wang, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-840, https://doi.org/10.5194/egusphere-2025-840, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study used machine learning to predict global and regional temperature changes under carbon neutrality and high emissions from 2015 to 2100.The results show that while carbon neutrality slows long-term warming, it causes short-term warming due to the rapid decline in aerosols. In contrast, greenhouse gases dominate warming in the high-emission scenario. These findings emphasize the important role of aerosols in shaping near-term climate change under carbon-neutral pathways.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
Atmos. Chem. Phys., 25, 2087–2121, https://doi.org/10.5194/acp-25-2087-2025, https://doi.org/10.5194/acp-25-2087-2025, 2025
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We use the GEOS-Chem model to simulate aerosol distributions and properties over the western North Atlantic Ocean (WNAO) during the winter and summer deployments in 2020 of the NASA ACTIVATE mission. Model results are evaluated against aircraft, ground-based, and satellite observations. The improved understanding of life cycle, composition, transport pathways, and distribution of aerosols has important implications for characterizing aerosol–cloud–meteorology interactions over WNAO.
Brandon M. Duran, Casey J. Wall, Nicholas J. Lutsko, Takuro Michibata, Po-Lun Ma, Yi Qin, Margaret L. Duffy, Brian Medeiros, and Matvey Debolskiy
Atmos. Chem. Phys., 25, 2123–2146, https://doi.org/10.5194/acp-25-2123-2025, https://doi.org/10.5194/acp-25-2123-2025, 2025
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We use satellite simulator data generated by global climate models to investigate how aerosol particles impact the radiative properties of liquid clouds. Specifically, we quantify the radiative perturbations arising from aerosol-driven changes in the number density of cloud droplets, the vertically integrated cloud water mass, and the cloud amount. Our results show that, in models, aerosol effects on the number density of cloud droplets contribute the most to anthropogenic climate forcing.
Mingxuan Wu, Hailong Wang, Zheng Lu, Xiaohong Liu, Huisheng Bian, David Cohen, Yan Feng, Mian Chin, Didier A. Hauglustaine, Vlassis A. Karydis, Marianne T. Lund, Gunnar Myhre, Andrea Pozzer, Michael Schulz, Ragnhild B. Skeie, Alexandra P. Tsimpidi, Svetlana G. Tsyro, and Shaocheng Xie
EGUsphere, https://doi.org/10.5194/egusphere-2025-235, https://doi.org/10.5194/egusphere-2025-235, 2025
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A key challenge in simulating the lifecycle of nitrate aerosol in global climate models is to accurately represent mass size distribution of nitrate aerosol, which lacks sufficient observational constraints. We found that most climate models underestimate the mass fraction of fine-mode nitrate at surface in all regions. Our study highlights the importance of gas-aerosol partitioning parameterization and simulation of dust and sea salt in correctly simulating mass size distribution of nitrate.
Ryan J. O'Loughlin, Dan Li, Richard Neale, and Travis A. O'Brien
Geosci. Model Dev., 18, 787–802, https://doi.org/10.5194/gmd-18-787-2025, https://doi.org/10.5194/gmd-18-787-2025, 2025
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We draw from traditional climate modeling practices to make recommendations for machine-learning (ML)-driven climate science. Our intended audience is climate modelers who are relatively new to ML. We show how component-level understanding – obtained when scientists can link model behavior to parts within the overall model – should guide the development and evaluation of ML models. Better understanding yields a stronger basis for trust in the models. We highlight several examples to demonstrate.
Mariya Petrenko, Ralph Kahn, Mian Chin, Susanne E. Bauer, Tommi Bergman, Huisheng Bian, Gabriele Curci, Ben Johnson, Johannes W. Kaiser, Zak Kipling, Harri Kokkola, Xiaohong Liu, Keren Mezuman, Tero Mielonen, Gunnar Myhre, Xiaohua Pan, Anna Protonotariou, Samuel Remy, Ragnhild Bieltvedt Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Hailong Wang, Duncan Watson-Parris, and Kai Zhang
Atmos. Chem. Phys., 25, 1545–1567, https://doi.org/10.5194/acp-25-1545-2025, https://doi.org/10.5194/acp-25-1545-2025, 2025
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We compared smoke plume simulations from 11 global models to each other and to satellite smoke amount observations aimed at constraining smoke source strength. In regions where plumes are thick and background aerosol is low, models and satellites compare well. However, the input emission inventory tends to underestimate in many places, and particle property and loss rate assumptions vary enormously among models, causing uncertainties that require systematic in situ measurements to resolve.
Mark D. Zelinka, Li-Wei Chao, Timothy A. Myers, Yi Qin, and Stephen A. Klein
Atmos. Chem. Phys., 25, 1477–1495, https://doi.org/10.5194/acp-25-1477-2025, https://doi.org/10.5194/acp-25-1477-2025, 2025
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Clouds lie at the heart of uncertainty in both climate sensitivity and radiative forcing, making it imperative to properly diagnose their radiative effects. Here we provide a recommended methodology and code base for the community to use in performing such diagnoses using cloud radiative kernels. We show that properly accounting for changes in obscuration of lower-level clouds by upper-level clouds is important for accurate diagnosis and attribution of cloud feedbacks and adjustments.
Zeli Tan, Donghui Xu, Sourav Taraphdar, Jiangqin Ma, Gautam Bisht, and L. Ruby Leung
EGUsphere, https://doi.org/10.5194/egusphere-2024-3816, https://doi.org/10.5194/egusphere-2024-3816, 2025
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Flow depth and velocity determine many river functions, but their high-resolution simulations are expensive. Here, we developed a downscaling approach that can provide fast and accurate estimation of high-resolution river hydrodynamics. The 84-fold acceleration achieved by the method makes reliable flood risk analysis that needs hundreds or thousands of model runs feasible. More importantly, it provides an opportunity to couple large-scale hydrodynamics with local processes in river models.
Sheng-Lun Tai, Zhao Yang, Brian Gaudet, Koichi Sakaguchi, Larry Berg, Colleen Kaul, Yun Qian, Ye Liu, and Jerome Fast
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-599, https://doi.org/10.5194/essd-2024-599, 2025
Preprint under review for ESSD
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Our study created a high-resolution soil moisture dataset for the eastern U.S. by integrating satellite data with a land surface model and advanced algorithms, achieving 1-km scale analyses. Validated against multiple networks and datasets, it demonstrated superior accuracy. This dataset is vital for understanding soil moisture dynamics, especially during droughts, and highlights the need for improved modeling of clay soils to refine future predictions.
Kai Lyu, Xiaohong Liu, and Bernd Kärcher
EGUsphere, https://doi.org/10.5194/egusphere-2024-4144, https://doi.org/10.5194/egusphere-2024-4144, 2025
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Two nucleation schemes are used to study ice nucleation, focusing on three ice sources: mountains, turbulence and anvils. Ice from mountains is concentrated in mid- and high-latitudes, while ice from turbulence and anvils is more common in low and mid-latitudes. Both schemes simulate orographic cirrus clouds, with mountain ice as the dominant source. The schemes differ in how they handle ice source competition, causing turbulence and anvils to influence clouds differently.
Weiyu Zhang, Kwinten Van Weverberg, Cyril J. Morcrette, Wuhu Feng, Kalli Furtado, Paul R. Field, Chih-Chieh Chen, Andrew Gettelman, Piers M. Forster, Daniel R. Marsh, and Alexandru Rap
Atmos. Chem. Phys., 25, 473–489, https://doi.org/10.5194/acp-25-473-2025, https://doi.org/10.5194/acp-25-473-2025, 2025
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Contrail cirrus is the largest, but also most uncertain, contribution of aviation to global warming. We evaluate, for the first time, the impact of the host climate model on contrail cirrus properties. Substantial differences exist between contrail cirrus formation, persistence, and radiative effects in the host climate models. Reliable contrail cirrus simulations require advanced representation of cloud optical properties and microphysics, which should be better constrained by observations.
Hui Wan, Abhishek Yenpure, Berk Geveci, Richard C. Easter, Philip J. Rasch, Kai Zhang, and Xubin Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2024-4020, https://doi.org/10.5194/egusphere-2024-4020, 2025
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In E3SMv2 and many other global climate models, the simulated anthropogenic aerosol influence on the Earth's energy balance is sensitive to the presence of clouds with very low droplet number concentrations. Numerical experiments conducted in this study suggest that mid- and high-latitude low-level stratus occurring under weak turbulence is an important cloud regime for understanding the causes of very low cloud droplet number concentrations in global climate simulations.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Johannes Mülmenstädt, Andrew S. Ackerman, Ann M. Fridlind, Meng Huang, Po-Lun Ma, Naser Mahfouz, Susanne E. Bauer, Susannah M. Burrows, Matthew W. Christensen, Sudhakar Dipu, Andrew Gettelman, L. Ruby Leung, Florian Tornow, Johannes Quaas, Adam C. Varble, Hailong Wang, Kai Zhang, and Youtong Zheng
Atmos. Chem. Phys., 24, 13633–13652, https://doi.org/10.5194/acp-24-13633-2024, https://doi.org/10.5194/acp-24-13633-2024, 2024
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Stratocumulus clouds play a large role in Earth's climate by reflecting incoming solar energy back to space. Turbulence at stratocumulus cloud top mixes in dry, warm air, which can lead to cloud dissipation. This process is challenging for coarse-resolution global models to represent. We show that global models nevertheless agree well with our process understanding. Global models also think the process is less important for the climate than other lines of evidence have led us to conclude.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Jerome D. Fast, Adam C. Varble, Fan Mei, Mikhail Pekour, Jason Tomlinson, Alla Zelenyuk, Art J. Sedlacek III, Maria Zawadowicz, and Louisa Emmons
Atmos. Chem. Phys., 24, 13477–13502, https://doi.org/10.5194/acp-24-13477-2024, https://doi.org/10.5194/acp-24-13477-2024, 2024
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Aerosol property measurements recently collected on the ground and by a research aircraft in central Argentina during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign exhibit large spatial and temporal variability. These measurements coupled with coincident meteorological information provide a valuable data set needed to evaluate and improve model predictions of aerosols in a traditionally data-sparse region of South America.
Jianqi Zhao, Xiaoyan Ma, and Johannes Quaas
EGUsphere, https://doi.org/10.5194/egusphere-2024-3662, https://doi.org/10.5194/egusphere-2024-3662, 2024
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We conduct a comparative analysis of aerosol-cloud responses in liquid-phase clouds under different aerosol and meteorological conditions based on simulations using the WRF-Chem-SBM model. Our findings highlight the different effects of aerosols on clouds and precipitation, as well as variations in the roles of aerosol and meteorological factors influencing aerosol-cloud interactions, in different environment.
Fan Mei, Jennifer M. Comstock, Mikhail S. Pekour, Jerome D. Fast, Krista L. Gaustad, Beat Schmid, Shuaiqi Tang, Damao Zhang, John E. Shilling, Jason M. Tomlinson, Adam C. Varble, Jian Wang, L. Ruby Leung, Lawrence Kleinman, Scot Martin, Sebastien C. Biraud, Brian D. Ermold, and Kenneth W. Burk
Earth Syst. Sci. Data, 16, 5429–5448, https://doi.org/10.5194/essd-16-5429-2024, https://doi.org/10.5194/essd-16-5429-2024, 2024
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Our study explores a comprehensive dataset from airborne field studies (2013–2018) conducted using the US Department of Energy's Gulfstream 1 (G-1). The 236 flights span diverse regions, including the Arctic, US Southern Great Plains, US West Coast, eastern North Atlantic, Amazon Basin in Brazil, and Sierras de Córdoba range in Argentina. This dataset provides unique insights into atmospheric dynamics, aerosols, and clouds and makes data available in a more accessible format.
Robert S. Arthur, Alex Rybchuk, Timothy W. Juliano, Gabriel Rios, Sonia Wharton, Julie K. Lundquist, and Jerome D. Fast
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-137, https://doi.org/10.5194/wes-2024-137, 2024
Revised manuscript accepted for WES
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This paper evaluates a new model configuration for wind energy forecasting in complex terrain. We compare model results to observations in the Altamont Pass (California, USA), where wind channeling through a mountain pass leads to increased energy production. We show evidence of improved wind speed and turbulence predictions compared to a more established modeling approach. Our work helps to ensure the robustness of the new model configuration for future wind energy applications.
Jiyuan Gao, Yang Yang, Hailong Wang, Pinya Wang, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2024-3399, https://doi.org/10.5194/egusphere-2024-3399, 2024
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The decline in aerosols in China altered temperature and pressure gradients between the two hemispheres, which intensified the Southern Trade Winds and caused a moisture divergence in Australia, resulting in less rainfall. Reduced surface moisture led to more energy being converted into sensible heat instead of evaporating as latent heat, which raised near-surface temperatures. Our findings offer insights for managing drought and wildfire risks in Australia.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Iris Papakonstantinou-Presvelou and Johannes Quaas
EGUsphere, https://doi.org/10.5194/egusphere-2024-3293, https://doi.org/10.5194/egusphere-2024-3293, 2024
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As the Arctic warms and the sea ice retreats, more open ocean is exposed, changing how aerosols impact clouds. Our previous 10-year satellite analysis found higher ice crystal numbers over sea ice than over ocean. Using model simulations and aircraft observations we identify here two factors as potential causes at colder temperatures; ice nucleating particles over sea ice and blowing snow. With further sea ice loss, these processes may weaken, leading to fewer ice particles in the future.
Charlotte Lange and Johannes Quaas
EGUsphere, https://doi.org/10.5194/egusphere-2024-3229, https://doi.org/10.5194/egusphere-2024-3229, 2024
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We studied how the Earth’s climate system adjusts to sudden changes in the energy budget, by analyzing data of four climate models, which simulated a 4 % reduction of incoming solar energy. We found rapid cooling of the atmosphere and shifts in cloud cover and atmospheric circulation patterns like land-sea-circulation. Our research helps to better understand cloud adjustments, which are a main source of uncertainty in climate models. This can improve future climate predictions.
Chang Liao, Ruby Leung, Yilin Fang, Teklu Tesfa, and Robinson Negron-Juarez
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-178, https://doi.org/10.5194/gmd-2024-178, 2024
Preprint under review for GMD
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Understanding horizontal groundwater flow is important for understanding how water moves through the ground. Current climate models often simplify this process because they don't have detailed enough information about the land surface. Our study developed a new model that divides the land surface into hillslopes to better represent how groundwater flows. This model can help improve predictions of water availability and how it affects ecosystems.
Hsiang-He Lee, Xue Zheng, Shaoyue Qiu, and Yuan Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3199, https://doi.org/10.5194/egusphere-2024-3199, 2024
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The study investigates how aerosol-cloud interactions affect warm boundary layer stratiform clouds over the Eastern North Atlantic. High-resolution WRF-Chem simulations reveal that non-rain clouds at the edges of cloud systems are prone to evaporation, leading to an aerosol drying effect and a transition of aerosols back to accumulation mode for future activation. The study emphasizes that this dynamic behavior is often not adequately represented in most previous prescribed-aerosol simulations.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-183, https://doi.org/10.5194/gmd-2024-183, 2024
Revised manuscript accepted for GMD
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Improving climate predictions has significant socio-economic impacts. In this study, we developed and applied a weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. It also enhances the simulation of interannual precipitation and temperature variability over the southern US. This system is to support future predictability studies.
Soodabeh Namdari, Sanja Dmitrovic, Gao Chen, Yonghoon Choi, Ewan Crosbie, Joshua P. DiGangi, Glenn S. Diskin, Richard A. Ferrare, Johnathan W. Hair, Simon Kirschler, John B. Nowak, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Xubin Zeng, and Armin Sorooshian
EGUsphere, https://doi.org/10.5194/egusphere-2024-3024, https://doi.org/10.5194/egusphere-2024-3024, 2024
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We conducted this study to assess the accuracy of airborne measurements of wind, temperature, and humidity, essential for understanding atmospheric processes. Using data from NASA's ACTIVATE campaign, we compared measurements from the TAMMS and DLH aboard a Falcon aircraft with dropsondes from a King Air, matching data points based on location and time using statistical methods. The study showed strong agreement, confirming the reliability of these methods for advancing climate models.
Sina Mehrdad, Dörthe Handorf, Ines Höschel, Khalil Karami, Johannes Quaas, Sudhakar Dipu, and Christoph Jacobi
Weather Clim. Dynam., 5, 1223–1268, https://doi.org/10.5194/wcd-5-1223-2024, https://doi.org/10.5194/wcd-5-1223-2024, 2024
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This study introduces a novel deep learning (DL) approach to analyze how regional radiative forcing in Europe impacts the Arctic climate. By integrating atmospheric poleward energy transport with DL-based clustering of atmospheric patterns and attributing anomalies to specific clusters, our method reveals crucial, nuanced interactions within the climate system, enhancing our understanding of intricate climate dynamics.
Julien Lenhardt, Johannes Quaas, Dino Sejdinovic, and Daniel Klocke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2724, https://doi.org/10.5194/egusphere-2024-2724, 2024
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Clouds come in various shapes and sizes and constitute a fundamental element of the Earth’s climate system. Different cloud types show variable impacts on climate change. We present a new cloud type classification method called CloudViT relying on spatial patterns of cloud properties obtained from satellite data using machine learning. We can thus help understanding the effects of different cloud types on climate change.
Lindsay M. Sheridan, Jiali Wang, Caroline Draxl, Nicola Bodini, Caleb Phillips, Dmitry Duplyakin, Heidi Tinnesand, Raj K. Rai, Julia E. Flaherty, Larry K. Berg, Chunyong Jung, and Ethan Young
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-115, https://doi.org/10.5194/wes-2024-115, 2024
Revised manuscript under review for WES
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Three recent wind resource datasets are assessed for their skills in representing annual average wind speeds and seasonal, diurnal, and inter-annual trends in the wind resource to support customers interested in small and midsize wind energy.
Julien Lenhardt, Johannes Quaas, and Dino Sejdinovic
Atmos. Meas. Tech., 17, 5655–5677, https://doi.org/10.5194/amt-17-5655-2024, https://doi.org/10.5194/amt-17-5655-2024, 2024
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Clouds play a key role in the regulation of the Earth's climate. Aspects like the height of their base are of essential interest to quantify their radiative effects but remain difficult to derive from satellite data. In this study, we combine observations from the surface and satellite retrievals of cloud properties to build a robust and accurate method to retrieve the cloud base height, based on a computer vision model and ordinal regression.
Dongyu Feng, Zeli Tan, Darren Engwirda, Jonathan D. Wolfe, Donghui Xu, Chang Liao, Gautam Bisht, James J. Benedict, Tian Zhou, Mithun Deb, Hong-Yi Li, and L. Ruby Leung
EGUsphere, https://doi.org/10.5194/egusphere-2024-2785, https://doi.org/10.5194/egusphere-2024-2785, 2024
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Our study explores how riverine and coastal flooding during hurricanes is influenced by the interaction of atmosphere, land, river and ocean conditions. Using an advanced Earth system model, we simulate Hurricane Irene to evaluate how meteorological and hydrological uncertainties affect flood modeling. Our findings reveal the importance of a multi-component modeling system, how hydrological conditions play critical roles in flood modeling, and greater flood risks if multiple factors are present.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Shuaiqi Tang, Hailong Wang, Xiang-Yu Li, Jingyi Chen, Armin Sorooshian, Xubin Zeng, Ewan Crosbie, Kenneth L. Thornhill, Luke D. Ziemba, and Christiane Voigt
Atmos. Chem. Phys., 24, 10073–10092, https://doi.org/10.5194/acp-24-10073-2024, https://doi.org/10.5194/acp-24-10073-2024, 2024
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We examined marine boundary layer clouds and their interactions with aerosols in the E3SM single-column model (SCM) for a case study. The SCM shows good agreement when simulating the clouds with high-resolution models. It reproduces the relationship between cloud droplet and aerosol particle number concentrations as produced in global models. However, the relationship between cloud liquid water and droplet number concentration is different, warranting further investigation.
August Mikkelsen, Daniel T. McCoy, Trude Eidhammer, Andrew Gettelman, Ci Song, Hamish Gordon, and Isabel L. McCoy
EGUsphere, https://doi.org/10.5194/egusphere-2024-2158, https://doi.org/10.5194/egusphere-2024-2158, 2024
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The largest uncertainty in inferring the magnitude of future warming comes from ambiguity in the strength of cooling in the historical record from aerosols. Aerosols are small liquid and solid particles that are important for cloud formation. The interactions between aerosols and clouds are complex and difficult to observe. In this study, we use surface observations of cloud and precipitation properties to constrain a climate model and interpret causality in complex aerosol-cloud interactions.
Jianqi Zhao, Xiaoyan Ma, Johannes Quaas, and Hailing Jia
Atmos. Chem. Phys., 24, 9101–9118, https://doi.org/10.5194/acp-24-9101-2024, https://doi.org/10.5194/acp-24-9101-2024, 2024
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We explore aerosol–cloud interactions in liquid-phase clouds over eastern China and its adjacent ocean in winter based on the WRF-Chem–SBM model, which couples a spectral-bin microphysics scheme and an online aerosol module. Our study highlights the differences in aerosol–cloud interactions between land and ocean and between precipitation clouds and non-precipitation clouds, and it differentiates and quantifies their underlying mechanisms.
Allen Hu, Xiaohong Liu, Ziming Ke, Benjamin Wagman, Hunter Brown, Zheng Lu, Diana Bull, and Kara Peterson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2227, https://doi.org/10.5194/egusphere-2024-2227, 2024
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Volcanic eruptions have a major effect on temperature throughout the atmosphere and can be studied as a proxy for geo-engineering. The aerosol module in the Energy Exascale Earth System Model (E3SM) was originally intended for simulation of tropospheric aerosols and has problems handling stratospheric sulfate aerosols due to volcanic eruptions. We have made alterations to the aerosol module to overcome these problems, with simulation results more closely reproducing observations.
Bo-Wen Shen, Roger Pielke Sr., and Xubin Zeng
EGUsphere, https://doi.org/10.13140/RG.2.2.32941.15849, https://doi.org/10.13140/RG.2.2.32941.15849, 2024
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Our reanalysis does not support the claim that Lorenz’s and Lilly’s formulas are mathematically or physically comparable. No common factor of 2^{−2/3} can be robustly determined from Lorenz's data, disproving the assumption that the saturation time difference and turnover time are linearly proportional over wave modes. These issues, along with the highly simplified features of the Lorenz 1969 model, indicate that an upper bound for the predictability limit has not been robustly determined.
Ye Liu, Yun Qian, Larry K. Berg, Zhe Feng, Jianfeng Li, Jingyi Chen, and Zhao Yang
Atmos. Chem. Phys., 24, 8165–8181, https://doi.org/10.5194/acp-24-8165-2024, https://doi.org/10.5194/acp-24-8165-2024, 2024
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Deep convection under various large-scale meteorological patterns (LSMPs) shows distinct precipitation features. In southeastern Texas, mesoscale convective systems (MCSs) contribute significantly to precipitation year-round, while isolated deep convection (IDC) is prominent in summer and fall. Self-organizing maps (SOMs) reveal convection can occur without large-scale lifting or moisture convergence. MCSs and IDC events have distinct life cycles influenced by specific LSMPs.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Jinbo Xie, Qi Tang, Michael Prather, Jadwiga Richter, and Shixuan Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1927, https://doi.org/10.5194/egusphere-2024-1927, 2024
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Analysis of the interaction between the climate and ozone in the stratosphere is complicated by the in-ability climate model in simulating the Quasi-Biennial Oscillation (QBO) – an important climate mode in the stratosphere. We use a set of model simulation that realistically simulate QBO and a novel ozone diagnostic tool to separate the temperature and circulation-driven QBO impact. These are important for diagnosing model-model differences in the QBO-ozone responses for climate projections.
Johannes Mülmenstädt, Edward Gryspeerdt, Sudhakar Dipu, Johannes Quaas, Andrew S. Ackerman, Ann M. Fridlind, Florian Tornow, Susanne E. Bauer, Andrew Gettelman, Yi Ming, Youtong Zheng, Po-Lun Ma, Hailong Wang, Kai Zhang, Matthew W. Christensen, Adam C. Varble, L. Ruby Leung, Xiaohong Liu, David Neubauer, Daniel G. Partridge, Philip Stier, and Toshihiko Takemura
Atmos. Chem. Phys., 24, 7331–7345, https://doi.org/10.5194/acp-24-7331-2024, https://doi.org/10.5194/acp-24-7331-2024, 2024
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Human activities release copious amounts of small particles called aerosols into the atmosphere. These particles change how much sunlight clouds reflect to space, an important human perturbation of the climate, whose magnitude is highly uncertain. We found that the latest climate models show a negative correlation but a positive causal relationship between aerosols and cloud water. This means we need to be very careful when we interpret observational studies that can only see correlation.
Naser Mahfouz, Johannes Mülmenstädt, and Susannah Burrows
Atmos. Chem. Phys., 24, 7253–7260, https://doi.org/10.5194/acp-24-7253-2024, https://doi.org/10.5194/acp-24-7253-2024, 2024
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Climate models are our primary tool to probe past, present, and future climate states unlike the more recent observation record. By constructing a hypothetical model configuration, we show that present-day correlations are insufficient to predict a persistent uncertainty in climate projection (how much sun because clouds will reflect in a changing climate). We hope our result will contribute to the scholarly conversation on better utilizing observations to constrain climate uncertainties.
Guta Wakbulcho Abeshu, Hong-Yi Li, Mingjie Shi, and Ruby Leung
EGUsphere, https://doi.org/10.5194/egusphere-2024-1748, https://doi.org/10.5194/egusphere-2024-1748, 2024
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This study examined how water availability, climate dryness, and plant productivity interact at the catchment scale. Using various indices and statistical methods, it found a 0–2-month lag in these interactions. Strong correlations during peak productivity months were observed, with a notable hysteresis effect in vegetation response to changes in water availability and climate dryness. The findings help better understand catchment responses to climate variability.
Jianfeng Li, Andrew Geiss, Zhe Feng, L. Ruby Leung, Yun Qian, and Wenjun Cui
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-112, https://doi.org/10.5194/essd-2024-112, 2024
Preprint under review for ESSD
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We develop a high-resolution (4 km and hourly) observational derecho dataset over the United States east of the Rocky Mountains from 2004 to 2021 by using a mesoscale convective system dataset, bow echo detection based on a machine learning method, hourly gust speed measurements, and physically based identification criteria.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter G. Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankararaman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Johann Engelbrecht, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbigniew Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-1617, https://doi.org/10.5194/egusphere-2024-1617, 2024
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Aerosol particles are an important part of the Earth system, but their concentrations are spatially and temporally heterogeneous, as well as variable in size and composition. Here we present a new compilation of PM2.5 and PM10 aerosol observations, focusing on the spatial variability across different observational stations, including composition, and demonstrate a method for comparing the datasets to model output.
Tapio Schneider, L. Ruby Leung, and Robert C. J. Wills
Atmos. Chem. Phys., 24, 7041–7062, https://doi.org/10.5194/acp-24-7041-2024, https://doi.org/10.5194/acp-24-7041-2024, 2024
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Climate models are crucial for predicting climate change in detail. This paper proposes a balanced approach to improving their accuracy by combining traditional process-based methods with modern artificial intelligence (AI) techniques while maximizing the resolution to allow for ensemble simulations. The authors propose using AI to learn from both observational and simulated data while incorporating existing physical knowledge to reduce data demands and improve climate prediction reliability.
Ziming Ke, Qi Tang, Jean-Christoophe Golaz, Xiaohong Liu, and Hailong Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1612, https://doi.org/10.5194/egusphere-2024-1612, 2024
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By treating volcanic emission interactively, model results improve simulated temperature variability, showing better correlations for 1940–1959 and 1960–1979, and reveals how volcanic activity influences cloud behavior and climate.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024, https://doi.org/10.5194/amt-17-3515-2024, 2024
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This study introduces and evaluates a new ocean surface wind speed product from the NASA Langley Research Center (LARC) airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) during the NASA ACTIVATE mission. We show that HSRL-2 surface wind speed data are accurate when compared to ground-truth dropsonde measurements. Therefore, the HSRL-2 instrument is able obtain accurate, high-resolution surface wind speed data in airborne field campaigns.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
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This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Yang Yang, Shaoxuan Mou, Hailong Wang, Pinya Wang, Baojie Li, and Hong Liao
Atmos. Chem. Phys., 24, 6509–6523, https://doi.org/10.5194/acp-24-6509-2024, https://doi.org/10.5194/acp-24-6509-2024, 2024
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The variations in anthropogenic aerosol concentrations and source contributions and their subsequent radiative impact in major emission regions during historical periods are quantified based on an aerosol-tagging system in E3SMv1. Due to the industrial development and implementation of economic policies, sources of anthropogenic aerosols show different variations, which has important implications for pollution prevention and control measures and decision-making for global collaboration.
Matthew W. Christensen, Peng Wu, Adam C. Varble, Heng Xiao, and Jerome D. Fast
Atmos. Chem. Phys., 24, 6455–6476, https://doi.org/10.5194/acp-24-6455-2024, https://doi.org/10.5194/acp-24-6455-2024, 2024
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Clouds are essential to keep Earth cooler by reflecting sunlight back to space. We show that an increase in aerosol concentration suppresses precipitation in clouds, causing them to accumulate water and expand in a polluted environment with stronger turbulence and radiative cooling. This process enhances their reflectance by 51 %. It is therefore prudent to account for cloud fraction changes in assessments of aerosol–cloud interactions to improve predictions of climate change.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Leong Wai Siu, Joseph S. Schlosser, David Painemal, Brian Cairns, Marta A. Fenn, Richard A. Ferrare, Johnathan W. Hair, Chris A. Hostetler, Longlei Li, Mary M. Kleb, Amy Jo Scarino, Taylor J. Shingler, Armin Sorooshian, Snorre A. Stamnes, and Xubin Zeng
Atmos. Meas. Tech., 17, 2739–2759, https://doi.org/10.5194/amt-17-2739-2024, https://doi.org/10.5194/amt-17-2739-2024, 2024
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An unprecedented 3-year aerosol dataset was collected from a recent NASA field campaign over the western North Atlantic Ocean, which offers a special opportunity to evaluate two state-of-the-art remote sensing instruments, one lidar and the other polarimeter, on the same aircraft. Special attention has been paid to validate aerosol optical depth data and their uncertainties when no reference dataset is available. Physical reasons for the disagreement between two instruments are discussed.
Charlotte M. Beall, Po-Lun Ma, Matthew W. Christensen, Johannes Mülmenstädt, Adam Varble, Kentaroh Suzuki, and Takuro Michibata
Atmos. Chem. Phys., 24, 5287–5302, https://doi.org/10.5194/acp-24-5287-2024, https://doi.org/10.5194/acp-24-5287-2024, 2024
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Single-layer warm liquid clouds cover nearly one-third of the Earth's surface, and uncertainties regarding the impact of aerosols on their radiative properties pose a significant challenge to climate prediction. Here, we demonstrate how satellite observations can be used to constrain Earth system model estimates of the radiative forcing from the interactions of aerosols with clouds due to warm rain processes.
Lindsay M. Sheridan, Dmitry Duplyakin, Caleb Phillips, Heidi Tinnesand, Raj K. Rai, Julia E. Flaherty, and Larry K. Berg
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-37, https://doi.org/10.5194/wes-2024-37, 2024
Revised manuscript under review for WES
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Twelve months of onsite wind measurement is standard for correcting model-based long-term wind speed estimates for utility-scale wind farms, however, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities for distributed wind projects. This study aims to answer the question of how low can you go in terms of the observational time period needed to make impactful improvements to long-term wind speed estimates.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Lingcheng Li, Gautam Bisht, Dalei Hao, and L. Ruby Leung
Earth Syst. Sci. Data, 16, 2007–2032, https://doi.org/10.5194/essd-16-2007-2024, https://doi.org/10.5194/essd-16-2007-2024, 2024
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This study fills a gap to meet the emerging needs of kilometer-scale Earth system modeling by developing global 1 km land surface parameters for land use, vegetation, soil, and topography. Our demonstration simulations highlight the substantial impacts of these parameters on spatial variability and information loss in water and energy simulations. Using advanced explainable machine learning methods, we identified influential factors driving spatial variability and information loss.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Weiming Ma, Hailong Wang, Gang Chen, Yun Qian, Ian Baxter, Yiling Huo, and Mark W. Seefeldt
Atmos. Chem. Phys., 24, 4451–4472, https://doi.org/10.5194/acp-24-4451-2024, https://doi.org/10.5194/acp-24-4451-2024, 2024
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Extreme warming events with surface temperature going above 0°C can occur in the high-Arctic winter. Although reanalysis data show that these events were short-lived and occurred rarely during 1980–2021, they have become more frequent, stronger, and longer lasting latterly. A dipole pattern, comprising high- and low-pressure systems, is found to be the key in driving them. These findings have implications for the recent changes in sea ice, hydrological cycle, and ecosystem over the Arctic.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
John T. Fasullo, Jean-Christophe Golaz, Julie M. Caron, Nan Rosenbloom, Gerald A. Meehl, Warren Strand, Sasha Glanville, Samantha Stevenson, Maria Molina, Christine A. Shields, Chengzhu Zhang, James Benedict, Hailong Wang, and Tony Bartoletti
Earth Syst. Dynam., 15, 367–386, https://doi.org/10.5194/esd-15-367-2024, https://doi.org/10.5194/esd-15-367-2024, 2024
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Climate model large ensembles provide a unique and invaluable means for estimating the climate response to external forcing agents and quantify contrasts in model structure. Here, an overview of the Energy Exascale Earth System Model (E3SM) version 2 large ensemble is given along with comparisons to large ensembles from E3SM version 1 and versions 1 and 2 of the Community Earth System Model. The paper provides broad and important context for users of these ensembles.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-43, https://doi.org/10.5194/essd-2024-43, 2024
Revised manuscript accepted for ESSD
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We have developed a new map that reveals how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2,500 gauges and a wealth of climate and environmental information. The map is a critical step in understanding and predicting how carbon moves through our environment, hence a useful tool for tackling climate challenges.
Hao Wang, Xiaohong Liu, Chenglai Wu, and Guangxing Lin
Atmos. Chem. Phys., 24, 3309–3328, https://doi.org/10.5194/acp-24-3309-2024, https://doi.org/10.5194/acp-24-3309-2024, 2024
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We quantified different global- and regional-scale drivers of biogenic volatile organic compound (BVOC) emission trends over the past 20 years. The results show that global greening trends significantly boost BVOC emissions and deforestation reduces BVOC emissions in South America and Southeast Asia. Elevated temperature in Europe and increased soil moisture in East and South Asia enhance BVOC emissions. The results deepen our understanding of long-term BVOC emission trends in hotspots.
Yawen Liu, Yun Qian, Philip J. Rasch, Kai Zhang, Lai-yung Ruby Leung, Yuhang Wang, Minghuai Wang, Hailong Wang, Xin Huang, and Xiu-Qun Yang
Atmos. Chem. Phys., 24, 3115–3128, https://doi.org/10.5194/acp-24-3115-2024, https://doi.org/10.5194/acp-24-3115-2024, 2024
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Fire management has long been a challenge. Here we report that spring-peak fire activity over southern Mexico and Central America (SMCA) has a distinct quasi-biennial signal by measuring multiple fire metrics. This signal is initially driven by quasi-biennial variability in precipitation and is further amplified by positive feedback of fire–precipitation interaction at short timescales. This work highlights the importance of fire–climate interactions in shaping fires on an interannual scale.
Adeleke S. Ademakinwa, Zahid H. Tushar, Jianyu Zheng, Chenxi Wang, Sanjay Purushotham, Jianwu Wang, Kerry G. Meyer, Tamas Várnai, and Zhibo Zhang
Atmos. Chem. Phys., 24, 3093–3114, https://doi.org/10.5194/acp-24-3093-2024, https://doi.org/10.5194/acp-24-3093-2024, 2024
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Clouds play a critical role in our climate system. At present and in the near future, satellite-based remote sensing is the only means to obtain regional and global observations of cloud properties. The current satellite remote sensing algorithms are mostly based on the so-called 1D radiative transfer. This deviation from the 3D world reality can lead to large errors. In this study we investigate how this error affects our estimation of cloud radiative effects.
Shaoyue Qiu, Xue Zheng, David Painemal, Christopher R. Terai, and Xiaoli Zhou
Atmos. Chem. Phys., 24, 2913–2935, https://doi.org/10.5194/acp-24-2913-2024, https://doi.org/10.5194/acp-24-2913-2024, 2024
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The aerosol indirect effect (AIE) depends on cloud states, which exhibit significant diurnal variations in the northeastern Atlantic. Yet the AIE diurnal cycle remains poorly understood. Using satellite retrievals, we find a pronounced “U-shaped” diurnal variation in the AIE, which is contributed to by the transition of cloud states combined with the lagged cloud responses. This suggests that polar-orbiting satellites with overpass times at noon underestimate daytime mean values of the AIE.
Yu Yao, Po-Lun Ma, Yi Qin, Matthew W. Christensen, Hui Wan, Kai Zhang, Balwinder Singh, Meng Huang, and Mikhail Ovchinnikov
EGUsphere, https://doi.org/10.5194/egusphere-2024-523, https://doi.org/10.5194/egusphere-2024-523, 2024
Preprint withdrawn
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Giant aerosols have substantial effects on warm rain formation. However, it remains challenging to quantify the impact of giant particles at global scale. In this work, we applied earth system model to investigate its impacts by implementing new giant aerosol treatments to consider its physical process. We found this approach substantially affect liquid cloud and improved model's precipitation response to aerosols. Our findings demonstrate the significant impact of giant aerosols on climate.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Chen Zhang, John J. Cassano, Mark Seefeldt, Hailong Wang, Weiming Ma, and Wen-wen Tung
EGUsphere, https://doi.org/10.5194/egusphere-2024-320, https://doi.org/10.5194/egusphere-2024-320, 2024
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An atmospheric river (AR) is a long, narrow corridor of moisture transport in the atmosphere. ARs are crucial for moisture and heat transport into the polar regions. Our study examines the role of ARs on the surface energy budget (SEB) in the Arctic. The results reveal distinct seasonality and land-sea-sea ice contrasts due to the impacts of ARs on the SEB. The conclusions provide greater insights into the current and future role of ARs on the Arctic climate system.
Ruth A. R. Digby, Nathan P. Gillett, Adam H. Monahan, Knut von Salzen, Antonis Gkikas, Qianqian Song, and Zhibo Zhang
Atmos. Chem. Phys., 24, 2077–2097, https://doi.org/10.5194/acp-24-2077-2024, https://doi.org/10.5194/acp-24-2077-2024, 2024
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The COVID-19 lockdowns reduced aerosol emissions. We ask whether these reductions affected regional aerosol optical depth (AOD) and compare the observed changes to predictions from Earth system models. Only India has an observed AOD reduction outside of typical variability. Models overestimate the response in some regions, but when key biases have been addressed, the agreement is improved. Our results suggest that current models can realistically predict the effects of future emission changes.
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024, https://doi.org/10.5194/gmd-17-1387-2024, 2024
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Sophisticated numerical models of the Earth's atmosphere include representations of many physical and chemical processes. In numerical simulations, these processes need to be calculated in a certain sequence. This study reveals the weaknesses of the sequence of calculations used for aerosol processes in a global atmosphere model. A revision of the sequence is proposed and its impacts on the simulated global aerosol climatology are evaluated.
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024, https://doi.org/10.5194/gmd-17-1409-2024, 2024
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Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of each group is combined with that of other groups to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Huisheng Bian, Mian Chin, Peter R. Colarco, Eric C. Apel, Donald R. Blake, Karl Froyd, Rebecca S. Hornbrook, Jose Jimenez, Pedro Campuzano Jost, Michael Lawler, Mingxu Liu, Marianne Tronstad Lund, Hitoshi Matsui, Benjamin A. Nault, Joyce E. Penner, Andrew W. Rollins, Gregory Schill, Ragnhild B. Skeie, Hailong Wang, Lu Xu, Kai Zhang, and Jialei Zhu
Atmos. Chem. Phys., 24, 1717–1741, https://doi.org/10.5194/acp-24-1717-2024, https://doi.org/10.5194/acp-24-1717-2024, 2024
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This work studies sulfur in the remote troposphere at global and seasonal scales using aircraft measurements and multi-model simulations. The goal is to understand the sulfur cycle over remote oceans, spread of model simulations, and observation–model discrepancies. Such an understanding and comparison with real observations are crucial to narrow down the uncertainties in model sulfur simulations and improve understanding of the sulfur cycle in atmospheric air quality, climate, and ecosystems.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
Preprint withdrawn
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Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
Yang Yang, Yang Zhou, Hailong Wang, Mengyun Li, Huimin Li, Pinya Wang, Xu Yue, Ke Li, Jia Zhu, and Hong Liao
Atmos. Chem. Phys., 24, 1177–1191, https://doi.org/10.5194/acp-24-1177-2024, https://doi.org/10.5194/acp-24-1177-2024, 2024
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This study reveals that extreme ozone pollution over the North China Plain and Yangtze River Delta is due to the chemical production related to hot and dry conditions, and the regional transport explains the ozone pollution over the Sichuan Basin and Pearl River Delta. The frequency of meteorological conditions of the extreme ozone pollution increases from the past to the future. The sustainable scenario is the optimal path to retaining clean air in China in the future.
Jun-Ichi Yano, Vince Larson, and Vaughan T. J. Phillips
EGUsphere, https://doi.org/10.5194/egusphere-2023-2278, https://doi.org/10.5194/egusphere-2023-2278, 2024
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The distribution problems appear in atmospheric sciences at almost every corner for describing diverse processes. This manuscript presents a general formulation for addressing all these problem.
Karoline Block, Mahnoosh Haghighatnasab, Daniel G. Partridge, Philip Stier, and Johannes Quaas
Earth Syst. Sci. Data, 16, 443–470, https://doi.org/10.5194/essd-16-443-2024, https://doi.org/10.5194/essd-16-443-2024, 2024
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Aerosols being able to act as condensation nuclei for cloud droplets (CCNs) are a key element in cloud formation but very difficult to determine. In this study we present a new global vertically resolved CCN dataset for various humidity conditions and aerosols. It is obtained using an atmospheric model (CAMS reanalysis) that is fed by satellite observations of light extinction (AOD). We investigate and evaluate the abundance of CCNs in the atmosphere and their temporal and spatial occurrence.
Hsiang-He Lee, Qi Tang, and Michael Prather
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-203, https://doi.org/10.5194/gmd-2023-203, 2024
Revised manuscript not accepted
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The E3SM Chemistry diagnostics package (ChemDyg) is a software tool, which is designed for the global climate model (E3SM) chemistry development. ChemDyg generates several diagnostic plots and tables for model-to-model and model-to-observation comparison, including 2-dimentional contour mapping plots, diurnal and annual cycle, time-series plots, and comprehensive processing tables. This paper is to introduce the details of each diagnostics set and its required input data formats in ChemDyg.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Yang Wang, Chanakya Bagya Ramesh, Scott E. Giangrande, Jerome Fast, Xianda Gong, Jiaoshi Zhang, Ahmet Tolga Odabasi, Marcus Vinicius Batista Oliveira, Alyssa Matthews, Fan Mei, John E. Shilling, Jason Tomlinson, Die Wang, and Jian Wang
Atmos. Chem. Phys., 23, 15671–15691, https://doi.org/10.5194/acp-23-15671-2023, https://doi.org/10.5194/acp-23-15671-2023, 2023
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We report the vertical profiles of aerosol properties over the Southern Great Plains (SGP), a region influenced by shallow convective clouds, land–atmosphere interactions, boundary layer turbulence, and the aerosol life cycle. We examined the processes that drive the aerosol population and distribution in the lower troposphere over the SGP. This study helps improve our understanding of aerosol–cloud interactions and the model representation of aerosol processes.
Jingyu Wang, Jiwen Fan, and Zhe Feng
Nat. Hazards Earth Syst. Sci., 23, 3823–3838, https://doi.org/10.5194/nhess-23-3823-2023, https://doi.org/10.5194/nhess-23-3823-2023, 2023
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Hail and tornadoes are devastating hazards responsible for significant property damage and economic losses in the United States. Quantifying the connection between hazard events and mesoscale convective systems (MCSs) is of great significance for improving predictability, as well as for better understanding the influence of the climate-scale perturbations. A 14-year statistical dataset of MCS-related hazard production is presented.
Jim M. Haywood, Andy Jones, Anthony C. Jones, Paul Halloran, and Philip J. Rasch
Atmos. Chem. Phys., 23, 15305–15324, https://doi.org/10.5194/acp-23-15305-2023, https://doi.org/10.5194/acp-23-15305-2023, 2023
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The difficulties in ameliorating global warming and the associated climate change via conventional mitigation are well documented, with all climate model scenarios exceeding 1.5 °C above the preindustrial level in the near future. There is therefore a growing interest in geoengineering to reflect a greater proportion of sunlight back to space and offset some of the global warming. We use a state-of-the-art Earth-system model to investigate two of the most prominent geoengineering strategies.
Tianle Yuan, Fei Liu, Lok N. Lamsal, and Hua Song
EGUsphere, https://doi.org/10.22541/essoar.168771101.14987378/v1, https://doi.org/10.22541/essoar.168771101.14987378/v1, 2023
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We train and apply a state-of-the-art deep learning model to detect NO2 plumes emitted by ships using NO2 retrievals from TROPOMI. By applying the model, we can detect individual plumes with excellent fidelity. The aggregated data show major shipping routes, but miss other routes. The missing routes are due to high cloudiness. Our method can be potentially useful for monitoring ship emissions of NOx and verifying compliance of emission standards.
Hamza Ahsan, Hailong Wang, Jingbo Wu, Mingxuan Wu, Steven J. Smith, Susanne Bauer, Harrison Suchyta, Dirk Olivié, Gunnar Myhre, Hitoshi Matsui, Huisheng Bian, Jean-François Lamarque, Ken Carslaw, Larry Horowitz, Leighton Regayre, Mian Chin, Michael Schulz, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Vaishali Naik
Atmos. Chem. Phys., 23, 14779–14799, https://doi.org/10.5194/acp-23-14779-2023, https://doi.org/10.5194/acp-23-14779-2023, 2023
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We examine the impact of the assumed effective height of SO2 injection, SO2 and BC emission seasonality, and the assumed fraction of SO2 emissions injected as SO4 on climate and chemistry model results. We find that the SO2 injection height has a large impact on surface SO2 concentrations and, in some models, radiative flux. These assumptions are a
hiddensource of inter-model variability and may be leading to bias in some climate model results.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
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A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Shuaiqi Tang, Adam C. Varble, Jerome D. Fast, Kai Zhang, Peng Wu, Xiquan Dong, Fan Mei, Mikhail Pekour, Joseph C. Hardin, and Po-Lun Ma
Geosci. Model Dev., 16, 6355–6376, https://doi.org/10.5194/gmd-16-6355-2023, https://doi.org/10.5194/gmd-16-6355-2023, 2023
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To assess the ability of Earth system model (ESM) predictions, we developed a tool called ESMAC Diags to understand how aerosols, clouds, and aerosol–cloud interactions are represented in ESMs. This paper describes its version 2 functionality. We compared the model predictions with measurements taken by planes, ships, satellites, and ground instruments over four regions across the world. Results show that this new tool can help identify model problems and guide future development of ESMs.
Calvin Howes, Pablo E. Saide, Hugh Coe, Amie Dobracki, Steffen Freitag, Jim M. Haywood, Steven G. Howell, Siddhant Gupta, Janek Uin, Mary Kacarab, Chongai Kuang, L. Ruby Leung, Athanasios Nenes, Greg M. McFarquhar, James Podolske, Jens Redemann, Arthur J. Sedlacek, Kenneth L. Thornhill, Jenny P. S. Wong, Robert Wood, Huihui Wu, Yang Zhang, Jianhao Zhang, and Paquita Zuidema
Atmos. Chem. Phys., 23, 13911–13940, https://doi.org/10.5194/acp-23-13911-2023, https://doi.org/10.5194/acp-23-13911-2023, 2023
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To better understand smoke properties and its interactions with clouds, we compare the WRF-CAM5 model with observations from ORACLES, CLARIFY, and LASIC field campaigns in the southeastern Atlantic in August 2017. The model transports and mixes smoke well but does not fully capture some important processes. These include smoke chemical and physical aging over 4–12 days, smoke removal by rain, sulfate particle formation, aerosol activation into cloud droplets, and boundary layer turbulence.
Dongyu Feng, Zeli Tan, Donghui Xu, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 27, 3911–3934, https://doi.org/10.5194/hess-27-3911-2023, https://doi.org/10.5194/hess-27-3911-2023, 2023
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This study assesses the flood risks concurrently induced by river flooding and coastal storm surge along the coast of the contiguous United States using statistical and numerical models. We reveal a few hotspots of such risks, the critical spatial variabilities within a river basin and over the whole US coast, and the uncertainties of the risk assessment. We highlight the importance of weighing different risk measures to avoid underestimating or exaggerating the compound flood impacts.
Adam C. Varble, Adele L. Igel, Hugh Morrison, Wojciech W. Grabowski, and Zachary J. Lebo
Atmos. Chem. Phys., 23, 13791–13808, https://doi.org/10.5194/acp-23-13791-2023, https://doi.org/10.5194/acp-23-13791-2023, 2023
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As atmospheric particles called aerosols increase in number, the number of droplets in clouds tends to increase, which has been theorized to increase storm intensity. We critically evaluate the evidence for this theory, showing that flaws and limitations of previous studies coupled with unaddressed cloud process complexities draw it into question. We provide recommendations for future observations and modeling to overcome current uncertainties.
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, and Terry Deshler
Geosci. Model Dev., 16, 6087–6125, https://doi.org/10.5194/gmd-16-6087-2023, https://doi.org/10.5194/gmd-16-6087-2023, 2023
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We implemented an alternative aerosol scheme in the high- and low-top model versions of the Community Earth System Model Version 2 (CESM2) with a more detailed description of tropospheric and stratospheric aerosol size distributions than the existing aerosol model. This development enables the comparison of different aerosol schemes with different complexity in the same model framework. It identifies improvements compared to a range of observations in both the troposphere and stratosphere.
Adam C. Varble, Po-Lun Ma, Matthew W. Christensen, Johannes Mülmenstädt, Shuaiqi Tang, and Jerome Fast
Atmos. Chem. Phys., 23, 13523–13553, https://doi.org/10.5194/acp-23-13523-2023, https://doi.org/10.5194/acp-23-13523-2023, 2023
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We evaluate how clouds change in response to changing atmospheric particle (aerosol) concentrations in a climate model and find that the model-predicted cloud brightness increases too much as aerosols increase because the cloud drop number increases too much. Excessive drizzle in the model mutes this difference. Many differences between observational and model estimates are explained by varying assumptions of how much liquid has been lost in clouds, which impacts the estimated cloud drop number.
Fabien Margairaz, Balwinder Singh, Jeremy A. Gibbs, Loren Atwood, Eric R. Pardyjak, and Rob Stoll
Geosci. Model Dev., 16, 5729–5754, https://doi.org/10.5194/gmd-16-5729-2023, https://doi.org/10.5194/gmd-16-5729-2023, 2023
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The Quick Environmental Simulation (QES) tool is a low-computational-cost fast-response framework. It provides high-resolution wind and concentration information to study complex problems, such as spore or smoke transport, urban pollution, and air quality. This paper presents the particle dispersion model and its validation against analytical solutions and wind-tunnel data for a mock-urban setting. In all cases, the model provides accurate results with competitive computational performance.
Chupeng Zhang, Shangfei Hai, Yang Gao, Yuhang Wang, Shaoqing Zhang, Lifang Sheng, Bin Zhao, Shuxiao Wang, Jingkun Jiang, Xin Huang, Xiaojing Shen, Junying Sun, Aura Lupascu, Manish Shrivastava, Jerome D. Fast, Wenxuan Cheng, Xiuwen Guo, Ming Chu, Nan Ma, Juan Hong, Qiaoqiao Wang, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 23, 10713–10730, https://doi.org/10.5194/acp-23-10713-2023, https://doi.org/10.5194/acp-23-10713-2023, 2023
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New particle formation is an important source of atmospheric particles, exerting critical influences on global climate. Numerical models are vital tools to understanding atmospheric particle evolution, which, however, suffer from large biases in simulating particle numbers. Here we improve the model chemical processes governing particle sizes and compositions. The improved model reveals substantial contributions of newly formed particles to climate through effects on cloud condensation nuclei.
Olivia Linke, Johannes Quaas, Finja Baumer, Sebastian Becker, Jan Chylik, Sandro Dahlke, André Ehrlich, Dörthe Handorf, Christoph Jacobi, Heike Kalesse-Los, Luca Lelli, Sina Mehrdad, Roel A. J. Neggers, Johannes Riebold, Pablo Saavedra Garfias, Niklas Schnierstein, Matthew D. Shupe, Chris Smith, Gunnar Spreen, Baptiste Verneuil, Kameswara S. Vinjamuri, Marco Vountas, and Manfred Wendisch
Atmos. Chem. Phys., 23, 9963–9992, https://doi.org/10.5194/acp-23-9963-2023, https://doi.org/10.5194/acp-23-9963-2023, 2023
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Lapse rate feedback (LRF) is a major driver of the Arctic amplification (AA) of climate change. It arises because the warming is stronger at the surface than aloft. Several processes can affect the LRF in the Arctic, such as the omnipresent temperature inversion. Here, we compare multimodel climate simulations to Arctic-based observations from a large research consortium to broaden our understanding of these processes, find synergy among them, and constrain the Arctic LRF and AA.
Andrew Gettelman
Geosci. Model Dev., 16, 4937–4956, https://doi.org/10.5194/gmd-16-4937-2023, https://doi.org/10.5194/gmd-16-4937-2023, 2023
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A representation of rainbows is developed for a climate model. The diagnostic raises many common issues. Simulated rainbows are evaluated against limited observations. The pattern of rainbows in the model matches observations and theory about when and where rainbows are most common. The diagnostic is used to assess the past and future state of rainbows. Changes to clouds from climate change are expected to increase rainbows as cloud cover decreases in a warmer world.
McKenna W. Stanford, Ann M. Fridlind, Israel Silber, Andrew S. Ackerman, Greg Cesana, Johannes Mülmenstädt, Alain Protat, Simon Alexander, and Adrian McDonald
Atmos. Chem. Phys., 23, 9037–9069, https://doi.org/10.5194/acp-23-9037-2023, https://doi.org/10.5194/acp-23-9037-2023, 2023
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Clouds play an important role in the Earth’s climate system as they modulate the amount of radiation that either reaches the surface or is reflected back to space. This study demonstrates an approach to robustly evaluate surface-based observations against a large-scale model. We find that the large-scale model precipitates too infrequently relative to observations, contrary to literature documentation suggesting otherwise based on satellite measurements.
Sue Ellen Haupt, Branko Kosović, Larry K. Berg, Colleen M. Kaul, Matthew Churchfield, Jeffrey Mirocha, Dries Allaerts, Thomas Brummet, Shannon Davis, Amy DeCastro, Susan Dettling, Caroline Draxl, David John Gagne, Patrick Hawbecker, Pankaj Jha, Timothy Juliano, William Lassman, Eliot Quon, Raj K. Rai, Michael Robinson, William Shaw, and Regis Thedin
Wind Energ. Sci., 8, 1251–1275, https://doi.org/10.5194/wes-8-1251-2023, https://doi.org/10.5194/wes-8-1251-2023, 2023
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The Mesoscale to Microscale Coupling team, part of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative, has studied various important challenges related to coupling mesoscale models to microscale models. Lessons learned and discerned best practices are described in the context of the cases studied for the purpose of enabling further deployment of wind energy. It also points to code, assessment tools, and data for testing the methods.
Mark D. Zelinka, Christopher J. Smith, Yi Qin, and Karl E. Taylor
Atmos. Chem. Phys., 23, 8879–8898, https://doi.org/10.5194/acp-23-8879-2023, https://doi.org/10.5194/acp-23-8879-2023, 2023
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The primary uncertainty in how strongly Earth's climate has been perturbed by human activities comes from the unknown radiative impact of aerosol changes. Accurately quantifying these forcings – and their sub-components – in climate models is crucial for understanding the past and future simulated climate. In this study we describe biases in previously published estimates of aerosol radiative forcing in climate models and provide corrected estimates along with code for users to compute them.
Armin Sorooshian, Mikhail D. Alexandrov, Adam D. Bell, Ryan Bennett, Grace Betito, Sharon P. Burton, Megan E. Buzanowicz, Brian Cairns, Eduard V. Chemyakin, Gao Chen, Yonghoon Choi, Brian L. Collister, Anthony L. Cook, Andrea F. Corral, Ewan C. Crosbie, Bastiaan van Diedenhoven, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Eva-Lou Edwards, Marta A. Fenn, Richard A. Ferrare, David van Gilst, Johnathan W. Hair, David B. Harper, Miguel Ricardo A. Hilario, Chris A. Hostetler, Nathan Jester, Michael Jones, Simon Kirschler, Mary M. Kleb, John M. Kusterer, Sean Leavor, Joseph W. Lee, Hongyu Liu, Kayla McCauley, Richard H. Moore, Joseph Nied, Anthony Notari, John B. Nowak, David Painemal, Kasey E. Phillips, Claire E. Robinson, Amy Jo Scarino, Joseph S. Schlosser, Shane T. Seaman, Chellappan Seethala, Taylor J. Shingler, Michael A. Shook, Kenneth A. Sinclair, William L. Smith Jr., Douglas A. Spangenberg, Snorre A. Stamnes, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Andrzej P. Wasilewski, Hailong Wang, Edward L. Winstead, Kira Zeider, Xubin Zeng, Bo Zhang, Luke D. Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data, 15, 3419–3472, https://doi.org/10.5194/essd-15-3419-2023, https://doi.org/10.5194/essd-15-3419-2023, 2023
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The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions. HU-25 Falcon and King Air aircraft conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.
Jingyu Wang, Xianfeng Wang, Edward Park, and Yun Lin
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-100, https://doi.org/10.5194/nhess-2023-100, 2023
Manuscript not accepted for further review
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Building upon the findings in a preceding study by the authors (Wang et al., 2023), this brief communication successfully applied the soil moisture-based tornado damage track detection method to the 24–25 March 2023 Mississippi outbreak. This study also found that the notable discrepancies between spotter reports and ground survey assessments at the tornado early stage can be reconciled using the new method.
Jianyu Zheng, Zhibo Zhang, Hongbin Yu, Anne Garnier, Qianqian Song, Chenxi Wang, Claudia Di Biagio, Jasper F. Kok, Yevgeny Derimian, and Claire Ryder
Atmos. Chem. Phys., 23, 8271–8304, https://doi.org/10.5194/acp-23-8271-2023, https://doi.org/10.5194/acp-23-8271-2023, 2023
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We developed a multi-year satellite-based retrieval of dust optical depth at 10 µm and the coarse-mode dust effective diameter over global oceans. It reveals climatological coarse-mode dust transport patterns and regional differences over the North Atlantic, the Indian Ocean and the North Pacific.
Hao Luo, Johannes Quaas, and Yong Han
Atmos. Chem. Phys., 23, 8169–8186, https://doi.org/10.5194/acp-23-8169-2023, https://doi.org/10.5194/acp-23-8169-2023, 2023
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Clouds exhibit a wide range of vertical structures with varying microphysical and radiative properties. We show a global survey of spatial distribution, vertical extent and radiative effect of various classified cloud vertical structures using joint satellite observations from the new CCCM datasets during 2007–2010. Moreover, the long-term trends in CVSs are investigated based on different CMIP6 future scenarios to capture the cloud variations with different, increasing anthropogenic forcings.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023, https://doi.org/10.5194/gmd-16-4017-2023, 2023
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Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Hyein Jeong, Adrian K. Turner, Andrew F. Roberts, Milena Veneziani, Stephen F. Price, Xylar S. Asay-Davis, Luke P. Van Roekel, Wuyin Lin, Peter M. Caldwell, Hyo-Seok Park, Jonathan D. Wolfe, and Azamat Mametjanov
The Cryosphere, 17, 2681–2700, https://doi.org/10.5194/tc-17-2681-2023, https://doi.org/10.5194/tc-17-2681-2023, 2023
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We find that E3SM-HR reproduces the main features of the Antarctic coastal polynyas. Despite the high amount of coastal sea ice production, the densest water masses are formed in the open ocean. Biases related to the lack of dense water formation are associated with overly strong atmospheric polar easterlies. Our results indicate that the large-scale polar atmospheric circulation must be accurately simulated in models to properly reproduce Antarctic dense water formation.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
Aishwarya Raman, Thomas Hill, Paul J. DeMott, Balwinder Singh, Kai Zhang, Po-Lun Ma, Mingxuan Wu, Hailong Wang, Simon P. Alexander, and Susannah M. Burrows
Atmos. Chem. Phys., 23, 5735–5762, https://doi.org/10.5194/acp-23-5735-2023, https://doi.org/10.5194/acp-23-5735-2023, 2023
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Ice-nucleating particles (INPs) play an important role in cloud processes and associated precipitation. Yet, INPs are not accurately represented in climate models. This study attempts to uncover these gaps by comparing model-simulated INP concentrations against field campaign measurements in the SO for an entire year, 2017–2018. Differences in INP concentrations and variability between the model and observations have major implications for modeling cloud properties in high latitudes.
Zhe Feng, Joseph Hardin, Hannah C. Barnes, Jianfeng Li, L. Ruby Leung, Adam Varble, and Zhixiao Zhang
Geosci. Model Dev., 16, 2753–2776, https://doi.org/10.5194/gmd-16-2753-2023, https://doi.org/10.5194/gmd-16-2753-2023, 2023
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PyFLEXTRKR is a flexible atmospheric feature tracking framework with specific capabilities to track convective clouds from a variety of observations and model simulations. The package has a collection of multi-object identification algorithms and has been optimized for large datasets. This paper describes the algorithms and demonstrates applications for tracking deep convective cells and mesoscale convective systems from observations and model simulations at a wide range of scales.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Pengwei Li, Yang Yang, Hailong Wang, Su Li, Ke Li, Pinya Wang, Baojie Li, and Hong Liao
Atmos. Chem. Phys., 23, 5403–5417, https://doi.org/10.5194/acp-23-5403-2023, https://doi.org/10.5194/acp-23-5403-2023, 2023
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We use a novel technique that can attribute O3 to precursors to investigate O3 changes in the United States during 1995–2019. We found that the US domestic energy and surface transportation emission reductions are primarily responsible for the O3 decrease in summer. In winter, factors such as nitrogen oxide emission reduction in the context of its inhibition of ozone production, increased aviation and shipping activities, and large-scale circulation changes contribute to the O3 increases.
Andrew Geiss, Po-Lun Ma, Balwinder Singh, and Joseph C. Hardin
Geosci. Model Dev., 16, 2355–2370, https://doi.org/10.5194/gmd-16-2355-2023, https://doi.org/10.5194/gmd-16-2355-2023, 2023
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Atmospheric aerosols play a critical role in Earth's climate, but it is too computationally expensive to directly model their interaction with radiation in climate simulations. This work develops a new neural-network-based parameterization of aerosol optical properties for use in the Energy Exascale Earth System Model that is much more accurate than the current one; it also introduces a unique model optimization method that involves randomly generating neural network architectures.
Samuel Kwakye, Heike Kalesse-Los, Maximilian Maahn, Patric Seifert, Roel van Klink, Christian Wirth, and Johannes Quaas
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-69, https://doi.org/10.5194/amt-2023-69, 2023
Publication in AMT not foreseen
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Insect numbers in the atmosphere can be calculated using polarimetric weather radar but they have to be identified and separated from other echoes, especially weather phenomena. Here, the separation is demonstrated using three machine-learning algorithms and insect count data from suction traps and the nature of radar measurements of different radar echoes is revealed. Random forest is the best separating algorithm and insect echoes radar measurements are distinct.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev., 16, 1909–1924, https://doi.org/10.5194/gmd-16-1909-2023, https://doi.org/10.5194/gmd-16-1909-2023, 2023
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Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Sheng-Lun Tai, Larry K. Berg, Raghavendra Krishnamurthy, Rob Newsom, and Anthony Kirincich
Wind Energ. Sci., 8, 433–448, https://doi.org/10.5194/wes-8-433-2023, https://doi.org/10.5194/wes-8-433-2023, 2023
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Turbulence intensity is critical for wind turbine design and operation as it affects wind power generation efficiency. Turbulence measurements in the marine environment are limited. We use a model to derive turbulence intensity and test how sea surface temperature data may impact the simulated turbulence intensity and atmospheric stability. The model slightly underestimates turbulence, and improved sea surface temperature data reduce the bias. Error with unrealistic mesoscale flow is identified.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
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Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
Jianqi Zhao, Xiaoyan Ma, Johannes Quaas, and Hailing Jia
EGUsphere, https://doi.org/10.5194/egusphere-2023-331, https://doi.org/10.5194/egusphere-2023-331, 2023
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We improve the ability of WRF-Chem model to simulate aerosol-cloud physical and chemical processes by coupling a spectral-bin cloud microphysics scheme and online aerosol module, and consequently explore the aerosol-cloud interactions over eastern China and its adjacent ocean in boreal winter. Our study highlights the differences in aerosol-cloud interactions between land and ocean, precipitation clouds and non-precipitation clouds, and differentiates and quantifies their underlying mechanisms.
Enner Alcântara, José A. Marengo, José Mantovani, Luciana R. Londe, Rachel Lau Yu San, Edward Park, Yunung Nina Lin, Jingyu Wang, Tatiana Mendes, Ana Paula Cunha, Luana Pampuch, Marcelo Seluchi, Silvio Simões, Luz Adriana Cuartas, Demerval Goncalves, Klécia Massi, Regina Alvalá, Osvaldo Moraes, Carlos Souza Filho, Rodolfo Mendes, and Carlos Nobre
Nat. Hazards Earth Syst. Sci., 23, 1157–1175, https://doi.org/10.5194/nhess-23-1157-2023, https://doi.org/10.5194/nhess-23-1157-2023, 2023
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The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains 68 km outside the city of Rio de Janeiro. On 15 February 2022, the city of Petrópolis in Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm). This resulted in flash floods and subsequent landslides that caused 231 fatalities, the deadliest landslide disaster recorded in Petrópolis. This work shows how the disaster was triggered.
Matthew W. Christensen, Po-Lun Ma, Peng Wu, Adam C. Varble, Johannes Mülmenstädt, and Jerome D. Fast
Atmos. Chem. Phys., 23, 2789–2812, https://doi.org/10.5194/acp-23-2789-2023, https://doi.org/10.5194/acp-23-2789-2023, 2023
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An increase in aerosol concentration (tiny airborne particles) is shown to suppress rainfall and increase the abundance of droplets in clouds passing over Graciosa Island in the Azores. Cloud drops remain affected by aerosol for several days across thousands of kilometers in satellite data. Simulations from an Earth system model show good agreement, but differences in the amount of cloud water and its extent remain despite modifications to model parameters that control the warm-rain process.
Marine Bonazzola, Hélène Chepfer, Po-Lun Ma, Johannes Quaas, David M. Winker, Artem Feofilov, and Nick Schutgens
Geosci. Model Dev., 16, 1359–1377, https://doi.org/10.5194/gmd-16-1359-2023, https://doi.org/10.5194/gmd-16-1359-2023, 2023
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Aerosol has a large impact on climate. Using a lidar aerosol simulator ensures consistent comparisons between modeled and observed aerosol. We present a lidar aerosol simulator that applies a cloud masking and an aerosol detection threshold. We estimate the lidar signals that would be observed at 532 nm by the Cloud-Aerosol Lidar with Orthogonal Polarization overflying the atmosphere predicted by a climate model. Our comparison at the seasonal timescale shows a discrepancy in the Southern Ocean.
Dalei Hao, Gautam Bisht, Karl Rittger, Timbo Stillinger, Edward Bair, Yu Gu, and L. Ruby Leung
The Cryosphere, 17, 673–697, https://doi.org/10.5194/tc-17-673-2023, https://doi.org/10.5194/tc-17-673-2023, 2023
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We comprehensively evaluated the snow simulations in E3SM land model over the western United States in terms of spatial patterns, temporal correlations, interannual variabilities, elevation gradients, and change with forest cover of snow properties and snow phenology. Our study underscores the need for diagnosing model biases and improving the model representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.
Chandan Sarangi, Yun Qian, L. Ruby Leung, Yang Zhang, Yufei Zou, and Yuhang Wang
Atmos. Chem. Phys., 23, 1769–1783, https://doi.org/10.5194/acp-23-1769-2023, https://doi.org/10.5194/acp-23-1769-2023, 2023
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We show that for air quality, the densely populated eastern US may see even larger impacts of wildfires due to long-distance smoke transport and associated positive climatic impacts, partially compensating the improvements from regulations on anthropogenic emissions. This study highlights the tension between natural and anthropogenic contributions and the non-local nature of air pollution that complicate regulatory strategies for improving future regional air quality for human health.
Mengyun Li, Yang Yang, Hailong Wang, Huimin Li, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 23, 1533–1544, https://doi.org/10.5194/acp-23-1533-2023, https://doi.org/10.5194/acp-23-1533-2023, 2023
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Using the GEOS-Chem model, the impact of the quasi-biennial oscillation (QBO) on summertime tropospheric O3 in China is investigated. In the warm phases of sea surface temperature anomalies over the eastern tropical Pacific, the QBO has a significant positive correlation with near-surface O3 concentrations over central China. The QBO impacts on O3 pollution in China are mainly a result of changing vertical transport of O3.
Huimin Li, Yang Yang, Jianbing Jin, Hailong Wang, Ke Li, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 23, 1131–1145, https://doi.org/10.5194/acp-23-1131-2023, https://doi.org/10.5194/acp-23-1131-2023, 2023
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Future climate change will aggravate ozone pollution in Asia, especially in high-forcing scenarios. Ozone pollution in China will expand from North China to South China and extend into the cold season in a warmer future. The emphasis of this work is to quantify the impacts of future climate change on O3 pollution in Asia, which is of great significance for future O3 pollution mitigation strategies.
Siegfried Schobesberger, Emma L. D'Ambro, Lejish Vettikkat, Ben H. Lee, Qiaoyun Peng, David M. Bell, John E. Shilling, Manish Shrivastava, Mikhail Pekour, Jerome Fast, and Joel A. Thornton
Atmos. Meas. Tech., 16, 247–271, https://doi.org/10.5194/amt-16-247-2023, https://doi.org/10.5194/amt-16-247-2023, 2023
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We present a new, highly sensitive technique for measuring atmospheric ammonia, an important trace gas that is emitted mainly by agriculture. We deployed the instrument on an aircraft during research flights over rural Oklahoma. Due to its fast response, we could analyze correlations with turbulent winds and calculate ammonia emissions from nearby areas at 1 to 2 km resolution. We observed high spatial variability and point sources that are not resolved in the US National Emissions Inventory.
Younjoo J. Lee, Wieslaw Maslowski, John J. Cassano, Jaclyn Clement Kinney, Anthony P. Craig, Samy Kamal, Robert Osinski, Mark W. Seefeldt, Julienne Stroeve, and Hailong Wang
The Cryosphere, 17, 233–253, https://doi.org/10.5194/tc-17-233-2023, https://doi.org/10.5194/tc-17-233-2023, 2023
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During 1979–2020, four winter polynyas occurred in December 1986 and February 2011, 2017, and 2018 north of Greenland. Instead of ice melting due to the anomalous warm air intrusion, the extreme wind forcing resulted in greater ice transport offshore. Based on the two ensemble runs, representing a 1980s thicker ice vs. a 2010s thinner ice, a dominant cause of these winter polynyas stems from internal variability of atmospheric forcing rather than from the forced response to a warming climate.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
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Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
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Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Huilin Huang, Yun Qian, Ye Liu, Cenlin He, Jianyu Zheng, Zhibo Zhang, and Antonis Gkikas
Atmos. Chem. Phys., 22, 15469–15488, https://doi.org/10.5194/acp-22-15469-2022, https://doi.org/10.5194/acp-22-15469-2022, 2022
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Using a clustering method developed in the field of artificial neural networks, we identify four typical dust transport patterns across the Sierra Nevada, associated with the mesoscale and regional-scale wind circulations. Our results highlight the connection between dust transport and dominant weather patterns, which can be used to understand dust transport in a changing climate.
William J. Shaw, Larry K. Berg, Mithu Debnath, Georgios Deskos, Caroline Draxl, Virendra P. Ghate, Charlotte B. Hasager, Rao Kotamarthi, Jeffrey D. Mirocha, Paytsar Muradyan, William J. Pringle, David D. Turner, and James M. Wilczak
Wind Energ. Sci., 7, 2307–2334, https://doi.org/10.5194/wes-7-2307-2022, https://doi.org/10.5194/wes-7-2307-2022, 2022
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This paper provides a review of prominent scientific challenges to characterizing the offshore wind resource using as examples phenomena that occur in the rapidly developing wind energy areas off the United States. The paper also describes the current state of modeling and observations in the marine atmospheric boundary layer and provides specific recommendations for filling key current knowledge gaps.
Alberto Caldas-Alvarez, Markus Augenstein, Georgy Ayzel, Klemens Barfus, Ribu Cherian, Lisa Dillenardt, Felix Fauer, Hendrik Feldmann, Maik Heistermann, Alexia Karwat, Frank Kaspar, Heidi Kreibich, Etor Emanuel Lucio-Eceiza, Edmund P. Meredith, Susanna Mohr, Deborah Niermann, Stephan Pfahl, Florian Ruff, Henning W. Rust, Lukas Schoppa, Thomas Schwitalla, Stella Steidl, Annegret H. Thieken, Jordis S. Tradowsky, Volker Wulfmeyer, and Johannes Quaas
Nat. Hazards Earth Syst. Sci., 22, 3701–3724, https://doi.org/10.5194/nhess-22-3701-2022, https://doi.org/10.5194/nhess-22-3701-2022, 2022
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In a warming climate, extreme precipitation events are becoming more frequent. To advance our knowledge on such phenomena, we present a multidisciplinary analysis of a selected case study that took place on 29 June 2017 in the Berlin metropolitan area. Our analysis provides evidence of the extremeness of the case from the atmospheric and the impacts perspectives as well as new insights on the physical mechanisms of the event at the meteorological and climate scales.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
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This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Yang Yang, Liangying Zeng, Hailong Wang, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 22, 14489–14502, https://doi.org/10.5194/acp-22-14489-2022, https://doi.org/10.5194/acp-22-14489-2022, 2022
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Using an aerosol–climate model, dust pollution in China affected by different spatial and temporal types of El Niño are examined. Both eastern and central Pacific El Niño and short-duration El Niño increase winter dust concentrations over northern China, while long-duration El Niño decreases concentrations. Only long-duration El Niño events can significantly affect dust over China in the following spring. This study has profound implications for air pollution control and dust storm prediction.
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, https://doi.org/10.5194/gmd-15-8135-2022, 2022
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We focus on the recent development of a state-of-the-art storm-resolving global climate model and investigate how this next-generation model performs for precipitation prediction over the western USA. Results show realistic representations of precipitation with significantly enhanced snowpack over complex terrains. The model evaluation advances the unified modeling of large-scale forcing constraints and realistic fine-scale features to advance multi-scale climate predictions and changes.
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 5473–5491, https://doi.org/10.5194/hess-26-5473-2022, https://doi.org/10.5194/hess-26-5473-2022, 2022
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Sea level rise, storm surge and river discharge can cause coastal backwater effects in downstream sections of rivers, creating critical flood risks. This study simulates the backwater effects using a large-scale river model on a coastal-refined computational mesh. By decomposing the backwater drivers, we revealed their relative importance and long-term variations. Our analysis highlights the increasing strength of backwater effects due to sea level rise and more frequent storm surge.
Yilin Fang, L. Ruby Leung, Charles D. Koven, Gautam Bisht, Matteo Detto, Yanyan Cheng, Nate McDowell, Helene Muller-Landau, S. Joseph Wright, and Jeffrey Q. Chambers
Geosci. Model Dev., 15, 7879–7901, https://doi.org/10.5194/gmd-15-7879-2022, https://doi.org/10.5194/gmd-15-7879-2022, 2022
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We develop a model that integrates an Earth system model with a three-dimensional hydrology model to explicitly resolve hillslope topography and water flow underneath the land surface to understand how local-scale hydrologic processes modulate vegetation along water availability gradients. Our coupled model can be used to improve the understanding of the diverse impact of local heterogeneity and water flux on nutrient availability and plant communities.
Qianqian Song, Zhibo Zhang, Hongbin Yu, Jasper F. Kok, Claudia Di Biagio, Samuel Albani, Jianyu Zheng, and Jiachen Ding
Atmos. Chem. Phys., 22, 13115–13135, https://doi.org/10.5194/acp-22-13115-2022, https://doi.org/10.5194/acp-22-13115-2022, 2022
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This study developed a dataset that enables us to efficiently calculate dust direct radiative effect (DRE, i.e., cooling or warming our planet) for any given dust size distribution in addition to three sets of dust mineral components and two dust shapes. We demonstrate and validate the method of using this dataset to calculate dust DRE. Moreover, using this dataset we found that dust mineral composition is a more important factor in determining dust DRE than dust size and shape.
Johannes Quaas, Hailing Jia, Chris Smith, Anna Lea Albright, Wenche Aas, Nicolas Bellouin, Olivier Boucher, Marie Doutriaux-Boucher, Piers M. Forster, Daniel Grosvenor, Stuart Jenkins, Zbigniew Klimont, Norman G. Loeb, Xiaoyan Ma, Vaishali Naik, Fabien Paulot, Philip Stier, Martin Wild, Gunnar Myhre, and Michael Schulz
Atmos. Chem. Phys., 22, 12221–12239, https://doi.org/10.5194/acp-22-12221-2022, https://doi.org/10.5194/acp-22-12221-2022, 2022
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Pollution particles cool climate and offset part of the global warming. However, they are washed out by rain and thus their effect responds quickly to changes in emissions. We show multiple datasets to demonstrate that aerosol emissions and their concentrations declined in many regions influenced by human emissions, as did the effects on clouds. Consequently, the cooling impact on the Earth energy budget became smaller. This change in trend implies a relative warming.
Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Yongjie Huang, Greg M. McFarquhar, Hugh Morrison, Mengistu Wolde, and Cuong Nguyen
Atmos. Chem. Phys., 22, 12287–12310, https://doi.org/10.5194/acp-22-12287-2022, https://doi.org/10.5194/acp-22-12287-2022, 2022
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Secondary ice production (SIP) is an important physical phenomenon that results in an increase in the cloud ice particle concentration and can have a significant impact on the evolution of clouds. Here, idealized simulations of a tropical convective system were conducted. Agreement between the simulations and observations highlights the impacts of SIP on the maintenance of tropical convection in nature and the importance of including the modelling of SIP in numerical weather prediction models.
Shixuan Zhang, Kai Zhang, Hui Wan, and Jian Sun
Geosci. Model Dev., 15, 6787–6816, https://doi.org/10.5194/gmd-15-6787-2022, https://doi.org/10.5194/gmd-15-6787-2022, 2022
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This study investigates the nudging implementation in the EAMv1 model. We find that (1) revising the sequence of calculations and using higher-frequency constraining data to improve the performance of a simulation nudged to EAMv1’s own meteorology, (2) using the relocated nudging tendency and 3-hourly ERA5 reanalysis to obtain a better agreement between nudged simulations and observations, and (3) using wind-only nudging are recommended for the estimates of global mean aerosol effects.
Jerome D. Fast, David M. Bell, Gourihar Kulkarni, Jiumeng Liu, Fan Mei, Georges Saliba, John E. Shilling, Kaitlyn Suski, Jason Tomlinson, Jian Wang, Rahul Zaveri, and Alla Zelenyuk
Atmos. Chem. Phys., 22, 11217–11238, https://doi.org/10.5194/acp-22-11217-2022, https://doi.org/10.5194/acp-22-11217-2022, 2022
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Recent aircraft measurements from the HI-SCALE campaign conducted over the Southern Great Plains (SGP) site in Oklahoma are used to quantify spatial variability of aerosol properties in terms of grid spacings typically used by weather and climate models. Surprisingly large horizontal gradients in aerosol properties were frequently observed in this rural area. This spatial variability can be used as an uncertainty range when comparing surface point measurements with model predictions.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Meng Huang, Po-Lun Ma, Nathaniel W. Chaney, Dalei Hao, Gautam Bisht, Megan D. Fowler, Vincent E. Larson, and L. Ruby Leung
Geosci. Model Dev., 15, 6371–6384, https://doi.org/10.5194/gmd-15-6371-2022, https://doi.org/10.5194/gmd-15-6371-2022, 2022
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The land surface in one grid cell may be diverse in character. This study uses an explicit way to account for that subgrid diversity in a state-of-the-art Earth system model (ESM) and explores its implications for the overlying atmosphere. We find that the shallow clouds are increased significantly with the land surface diversity. Our work highlights the importance of accurately representing the land surface and its interaction with the atmosphere in next-generation ESMs.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
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Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Fan Mei, Mikhail S. Pekour, Darielle Dexheimer, Gijs de Boer, RaeAnn Cook, Jason Tomlinson, Beat Schmid, Lexie A. Goldberger, Rob Newsom, and Jerome D. Fast
Earth Syst. Sci. Data, 14, 3423–3438, https://doi.org/10.5194/essd-14-3423-2022, https://doi.org/10.5194/essd-14-3423-2022, 2022
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This work focuses on an expanding number of data sets observed using ARM TBS (133 flights) and UAS (seven flights) platforms by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research, such as the aerosol–cloud interaction in the boundary layer.
Sol Kim, L. Ruby Leung, Bin Guan, and John C. H. Chiang
Geosci. Model Dev., 15, 5461–5480, https://doi.org/10.5194/gmd-15-5461-2022, https://doi.org/10.5194/gmd-15-5461-2022, 2022
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The Energy Exascale Earth System Model (E3SM) project is a state-of-the-science Earth system model developed by the US Department of Energy (DOE). Understanding how the water cycle behaves in this model is of particular importance to the DOE’s mission. Atmospheric rivers (ARs) – which are crucial to the global water cycle – move vast amounts of water vapor through the sky and produce rain and snow. We find that this model reliably represents atmospheric rivers around the world.
Lingcheng Li, Gautam Bisht, and L. Ruby Leung
Geosci. Model Dev., 15, 5489–5510, https://doi.org/10.5194/gmd-15-5489-2022, https://doi.org/10.5194/gmd-15-5489-2022, 2022
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Land surface heterogeneity plays a critical role in the terrestrial water, energy, and biogeochemical cycles. Our study systematically quantified the effects of four dominant heterogeneity sources on water and energy partitioning via Sobol' indices. We found that atmospheric forcing and land use land cover are the most dominant heterogeneity sources in determining spatial variability of water and energy partitioning. Our findings can help prioritize the future development of land surface models.
Kai Zhang, Wentao Zhang, Hui Wan, Philip J. Rasch, Steven J. Ghan, Richard C. Easter, Xiangjun Shi, Yong Wang, Hailong Wang, Po-Lun Ma, Shixuan Zhang, Jian Sun, Susannah M. Burrows, Manish Shrivastava, Balwinder Singh, Yun Qian, Xiaohong Liu, Jean-Christophe Golaz, Qi Tang, Xue Zheng, Shaocheng Xie, Wuyin Lin, Yan Feng, Minghuai Wang, Jin-Ho Yoon, and L. Ruby Leung
Atmos. Chem. Phys., 22, 9129–9160, https://doi.org/10.5194/acp-22-9129-2022, https://doi.org/10.5194/acp-22-9129-2022, 2022
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Here we analyze the effective aerosol forcing simulated by E3SM version 1 using both century-long free-running and short nudged simulations. The aerosol forcing in E3SMv1 is relatively large compared to other models, mainly due to the large indirect aerosol effect. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 have a strong correlation. The aerosol forcing estimates in E3SMv1 are sensitive to the parameterization changes in both liquid and ice cloud processes.
Ovid O. Krüger, Bruna A. Holanda, Sourangsu Chowdhury, Andrea Pozzer, David Walter, Christopher Pöhlker, Maria Dolores Andrés Hernández, John P. Burrows, Christiane Voigt, Jos Lelieveld, Johannes Quaas, Ulrich Pöschl, and Mira L. Pöhlker
Atmos. Chem. Phys., 22, 8683–8699, https://doi.org/10.5194/acp-22-8683-2022, https://doi.org/10.5194/acp-22-8683-2022, 2022
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The abrupt reduction in human activities during the first COVID-19 lockdown created unprecedented atmospheric conditions. We took the opportunity to quantify changes in black carbon (BC) as a major anthropogenic air pollutant. Therefore, we measured BC on board a research aircraft over Europe during the lockdown and compared the results to measurements from 2017. With model simulations we account for different weather conditions and find a lockdown-related decrease in BC of 41 %.
Mahnoosh Haghighatnasab, Jan Kretzschmar, Karoline Block, and Johannes Quaas
Atmos. Chem. Phys., 22, 8457–8472, https://doi.org/10.5194/acp-22-8457-2022, https://doi.org/10.5194/acp-22-8457-2022, 2022
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The impact of aerosols emitted by the Holuhraun volcanic eruption on liquid clouds was assessed from a pair of cloud-system-resolving simulations along with satellite retrievals. Inside and outside the plume were compared in terms of their statistical distributions. Analyses indicated enhancement for cloud droplet number concentration inside the volcano plume in model simulations and satellite retrievals, while there was on average a small effect on both liquid water path and cloud fraction.
Assia Arouf, Hélène Chepfer, Thibault Vaillant de Guélis, Marjolaine Chiriaco, Matthew D. Shupe, Rodrigo Guzman, Artem Feofilov, Patrick Raberanto, Tristan S. L'Ecuyer, Seiji Kato, and Michael R. Gallagher
Atmos. Meas. Tech., 15, 3893–3923, https://doi.org/10.5194/amt-15-3893-2022, https://doi.org/10.5194/amt-15-3893-2022, 2022
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We proposed new estimates of the surface longwave (LW) cloud radiative effect (CRE) derived from observations collected by a space-based lidar on board the CALIPSO satellite and radiative transfer computations. Our estimate appropriately captures the surface LW CRE annual variability over bright polar surfaces, and it provides a dataset more than 13 years long.
Donghui Xu, Gautam Bisht, Khachik Sargsyan, Chang Liao, and L. Ruby Leung
Geosci. Model Dev., 15, 5021–5043, https://doi.org/10.5194/gmd-15-5021-2022, https://doi.org/10.5194/gmd-15-5021-2022, 2022
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The runoff outputs in Earth system model simulations involve high uncertainty, which needs to be constrained by parameter calibration. In this work, we used a surrogate-assisted Bayesian framework to efficiently calibrate the runoff-generation processes in the Energy Exascale Earth System Model v1 at a global scale. The model performance was improved compared to the default parameter after calibration, and the associated parametric uncertainty was significantly constrained.
Hailing Jia, Johannes Quaas, Edward Gryspeerdt, Christoph Böhm, and Odran Sourdeval
Atmos. Chem. Phys., 22, 7353–7372, https://doi.org/10.5194/acp-22-7353-2022, https://doi.org/10.5194/acp-22-7353-2022, 2022
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Aerosol–cloud interaction is the most uncertain component of the anthropogenic forcing of the climate. By combining satellite and reanalysis data, we show that the strength of the Twomey effect (S) increases remarkably with vertical velocity. Both the confounding effect of aerosol–precipitation interaction and the lack of vertical co-location between aerosol and cloud are found to overestimate S, whereas the retrieval biases in aerosol and cloud appear to underestimate S.
Jiyuan Gao, Yang Yang, Hailong Wang, Pinya Wang, Huimin Li, Mengyun Li, Lili Ren, Xu Yue, and Hong Liao
Atmos. Chem. Phys., 22, 7131–7142, https://doi.org/10.5194/acp-22-7131-2022, https://doi.org/10.5194/acp-22-7131-2022, 2022
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China has been implementing a sequence of policies for clean air since the year 2013. The aerosol decline produced a 0.09 ± 0.10°C warming during 2013–2017 estimated in this study, and the increase in ozone in the lower troposphere during this time period accelerated the warming, leading to a total 0.16 ± 0.15°C temperature increase in eastern China. Residential emission reductions led to a cooling effect because of a substantial decrease in light-absorbing aerosols.
Shuaiqi Tang, Jerome D. Fast, Kai Zhang, Joseph C. Hardin, Adam C. Varble, John E. Shilling, Fan Mei, Maria A. Zawadowicz, and Po-Lun Ma
Geosci. Model Dev., 15, 4055–4076, https://doi.org/10.5194/gmd-15-4055-2022, https://doi.org/10.5194/gmd-15-4055-2022, 2022
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We developed an Earth system model (ESM) diagnostics package to compare various types of aerosol properties simulated in ESMs with aircraft, ship, and surface measurements from six field campaigns across spatial scales. The diagnostics package is coded and organized to be flexible and modular for future extension to other field campaign datasets and adapted to higher-resolution model simulations. Future releases will include comprehensive cloud and aerosol–cloud interaction diagnostics.
Yun Lin, Jiwen Fan, Pengfei Li, Lai-yung Ruby Leung, Paul J. DeMott, Lexie Goldberger, Jennifer Comstock, Ying Liu, Jong-Hoon Jeong, and Jason Tomlinson
Atmos. Chem. Phys., 22, 6749–6771, https://doi.org/10.5194/acp-22-6749-2022, https://doi.org/10.5194/acp-22-6749-2022, 2022
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How sea spray aerosols may affect cloud and precipitation over the region by acting as ice-nucleating particles (INPs) is unknown. We explored the effects of INPs from marine aerosols on orographic cloud and precipitation for an atmospheric river event observed during the 2015 ACAPEX field campaign. The marine INPs enhance the formation of ice and snow, leading to less shallow warm clouds but more mixed-phase and deep clouds. This work suggests models need to consider the impacts of marine INPs.
Xue Zheng, Qing Li, Tian Zhou, Qi Tang, Luke P. Van Roekel, Jean-Christophe Golaz, Hailong Wang, and Philip Cameron-Smith
Geosci. Model Dev., 15, 3941–3967, https://doi.org/10.5194/gmd-15-3941-2022, https://doi.org/10.5194/gmd-15-3941-2022, 2022
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We document the model experiments for the future climate projection by E3SMv1.0. At the highest future emission scenario, E3SMv1.0 projects a strong surface warming with rapid changes in the atmosphere, ocean, sea ice, and land runoff. Specifically, we detect a significant polar amplification and accelerated warming linked to the unmasking of the aerosol effects. The impact of greenhouse gas forcing is examined in different climate components.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
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A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Susannah M. Burrows, Richard C. Easter, Xiaohong Liu, Po-Lun Ma, Hailong Wang, Scott M. Elliott, Balwinder Singh, Kai Zhang, and Philip J. Rasch
Atmos. Chem. Phys., 22, 5223–5251, https://doi.org/10.5194/acp-22-5223-2022, https://doi.org/10.5194/acp-22-5223-2022, 2022
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Sea spray particles are composed of a mixture of salts and organic substances from oceanic microorganisms. In prior work, our team developed an approach connecting sea spray chemistry to ocean biology, called OCEANFILMS. Here we describe its implementation within an Earth system model, E3SM. We show that simulated sea spray chemistry is consistent with observed seasonal cycles and that sunlight reflected by simulated Southern Ocean clouds increases, consistent with analysis of satellite data.
Hui Wan, Kai Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, Shixuan Zhang, and Ross Dixon
Geosci. Model Dev., 15, 3205–3231, https://doi.org/10.5194/gmd-15-3205-2022, https://doi.org/10.5194/gmd-15-3205-2022, 2022
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This paper describes a tool embedded in a global climate model for sampling atmospheric conditions and monitoring physical processes as a numerical simulation is being carried out. The tool facilitates process-level model evaluation by allowing the users to select a wide range of quantities and processes to monitor at run time without having to do tedious ad hoc coding.
Pinya Wang, Yang Yang, Huimin Li, Lei Chen, Ruijun Dang, Daokai Xue, Baojie Li, Jianping Tang, L. Ruby Leung, and Hong Liao
Atmos. Chem. Phys., 22, 4705–4719, https://doi.org/10.5194/acp-22-4705-2022, https://doi.org/10.5194/acp-22-4705-2022, 2022
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China is now suffering from both severe ozone (O3) pollution and heat events. We highlight that North China Plain is the hot spot of the co-occurrences of extremes in O3 and high temperatures in China. Such coupled extremes exhibit an increasing trend during 2014–2019 and will continue to increase until the middle of this century. And the coupled extremes impose more severe health impacts to human than O3 pollution occurring alone because of elevated O3 levels and temperatures.
Lindsay M. Sheridan, Caleb Phillips, Alice C. Orrell, Larry K. Berg, Heidi Tinnesand, Raj K. Rai, Sagi Zisman, Dmitry Duplyakin, and Julia E. Flaherty
Wind Energ. Sci., 7, 659–676, https://doi.org/10.5194/wes-7-659-2022, https://doi.org/10.5194/wes-7-659-2022, 2022
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The small wind community relies on simplified wind models and energy production simulation tools to obtain energy generation expectations. We gathered actual wind speed and turbine production data across the US to test the accuracy of models and tools for small wind turbines. This study provides small wind installers and owners with the error metrics and sources of error associated with using models and tools to make performance estimates, empowering them to adjust expectations accordingly.
Sally S.-C. Wang, Yun Qian, L. Ruby Leung, and Yang Zhang
Atmos. Chem. Phys., 22, 3445–3468, https://doi.org/10.5194/acp-22-3445-2022, https://doi.org/10.5194/acp-22-3445-2022, 2022
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This study develops an interpretable machine learning (ML) model predicting monthly PM2.5 fire emission over the contiguous US at 0.25° resolution and compares the prediction skills of the ML and process-based models. The comparison facilitates attributions of model biases and better understanding of the strengths and uncertainties in the two types of models at regional scales, for informing future model development and their applications in fire emission projection.
Yang Shi, Xiaohong Liu, Mingxuan Wu, Xi Zhao, Ziming Ke, and Hunter Brown
Atmos. Chem. Phys., 22, 2909–2935, https://doi.org/10.5194/acp-22-2909-2022, https://doi.org/10.5194/acp-22-2909-2022, 2022
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We perform a modeling study to evaluate the contribution to Arctic dust loading and ice-nucleating particle (INP) population from high-latitude local and low-latitude dust. High-latitude dust has a large contribution in the lower troposphere, while low-latitude dust dominates the upper troposphere. The high-latitude dust INPs result in a net cooling effect on the Arctic surface by glaciating mixed-phase clouds. Our results highlight the contribution of high-latitude dust to the Arctic climate.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, Rodrigo Guzman, Cyprien Gindre, Po-Lun Ma, and Marjolaine Chiriaco
Atmos. Meas. Tech., 15, 1055–1074, https://doi.org/10.5194/amt-15-1055-2022, https://doi.org/10.5194/amt-15-1055-2022, 2022
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Space-borne lidars have been providing invaluable information of atmospheric optical properties since 2006, and new lidar missions are on the way to ensure continuous observations. In this work, we compare the clouds estimated from space-borne ALADIN and CALIOP lidar observations. The analysis of collocated data shows that the agreement between the retrieved clouds is good up to 3 km height. Above that, ALADIN detects 40 % less clouds than CALIOP, except for polar stratospheric clouds (PSCs).
Xi Zhao and Xiaohong Liu
Atmos. Chem. Phys., 22, 2585–2600, https://doi.org/10.5194/acp-22-2585-2022, https://doi.org/10.5194/acp-22-2585-2022, 2022
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The goal of this study is to investigate the relative importance and interactions of primary and secondary ice production in the Arctic mixed-phase clouds. Our results show that the SIP is not only a result of ice crystals produced from ice nucleation, but also competes with the ice production; conversely, strong ice nucleation also suppresses SIP.
Guta Wakbulcho Abeshu, Hong-Yi Li, Zhenduo Zhu, Zeli Tan, and L. Ruby Leung
Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, https://doi.org/10.5194/essd-14-929-2022, 2022
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Existing riverbed sediment particle size data are sparsely available at individual sites. We develop a continuous map of median riverbed sediment particle size over the contiguous US corresponding to millions of river segments based on the existing observations and machine learning methods. This map is useful for research in large-scale river sediment using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Ming Xue, Hugh Morrison, Jason Milbrandt, Alexei V. Korolev, Yachao Hu, Zhipeng Qu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, and Ivan Heckman
Atmos. Chem. Phys., 22, 2365–2384, https://doi.org/10.5194/acp-22-2365-2022, https://doi.org/10.5194/acp-22-2365-2022, 2022
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Numerous small ice crystals in tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. Previous numerical simulations failed to reproduce this phenomenon and hypothesized that key microphysical processes are still lacking in current models to realistically simulate the phenomenon. This study uses numerical experiments to confirm the dominant role of secondary ice production in the formation of these large numbers of small ice crystals.
Hong-Yi Li, Zeli Tan, Hongbo Ma, Zhenduo Zhu, Guta Wakbulcho Abeshu, Senlin Zhu, Sagy Cohen, Tian Zhou, Donghui Xu, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 665–688, https://doi.org/10.5194/hess-26-665-2022, https://doi.org/10.5194/hess-26-665-2022, 2022
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We introduce a new multi-process river sediment module for Earth system models. Application and validation over the contiguous US indicate a satisfactory model performance over large river systems, including those heavily regulated by reservoirs. This new sediment module enables future modeling of the transportation and transformation of carbon and nutrients carried by the fine sediment along the river–ocean continuum to close the global carbon and nutrient cycles.
Michael R. Gallagher, Matthew D. Shupe, Hélène Chepfer, and Tristan L'Ecuyer
The Cryosphere, 16, 435–450, https://doi.org/10.5194/tc-16-435-2022, https://doi.org/10.5194/tc-16-435-2022, 2022
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By using direct observations of snowfall and mass changes, the variability of daily snowfall mass input to the Greenland ice sheet is quantified for the first time. With new methods we conclude that cyclones west of Greenland in summer contribute the most snowfall, with 1.66 Gt per occurrence. These cyclones are contextualized in the broader Greenland climate, and snowfall is validated against mass changes to verify the results. Snowfall and mass change observations are shown to agree well.
Ka Ming Fung, Colette L. Heald, Jesse H. Kroll, Siyuan Wang, Duseong S. Jo, Andrew Gettelman, Zheng Lu, Xiaohong Liu, Rahul A. Zaveri, Eric C. Apel, Donald R. Blake, Jose-Luis Jimenez, Pedro Campuzano-Jost, Patrick R. Veres, Timothy S. Bates, John E. Shilling, and Maria Zawadowicz
Atmos. Chem. Phys., 22, 1549–1573, https://doi.org/10.5194/acp-22-1549-2022, https://doi.org/10.5194/acp-22-1549-2022, 2022
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Understanding the natural aerosol burden in the preindustrial era is crucial for us to assess how atmospheric aerosols affect the Earth's radiative budgets. Our study explores how a detailed description of dimethyl sulfide (DMS) oxidation (implemented in the Community Atmospheric Model version 6 with chemistry, CAM6-chem) could help us better estimate the present-day and preindustrial concentrations of sulfate and other relevant chemicals, as well as the resulting aerosol radiative impacts.
Justin A. Covert, David B. Mechem, and Zhibo Zhang
Atmos. Chem. Phys., 22, 1159–1174, https://doi.org/10.5194/acp-22-1159-2022, https://doi.org/10.5194/acp-22-1159-2022, 2022
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Stratocumulus play an important role in Earth's radiative balance. The simulation of these cloud systems in climate models is difficult due to the scale at which cloud microphysical processes occur compared with model grid sizes. In this study, we use large-eddy simulation to analyze subgrid-scale variability of cloud water and its implications on a cloud water to drizzle model enhancement factor E. We find current values of E may be too large and that E should be vertically dependent in models.
Ye Liu, Yun Qian, and Larry K. Berg
Wind Energ. Sci., 7, 37–51, https://doi.org/10.5194/wes-7-37-2022, https://doi.org/10.5194/wes-7-37-2022, 2022
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Uncertainties in initial conditions (ICs) decrease the accuracy of wind speed forecasts. We find that IC uncertainties can alter wind speed by modulating the weather system. IC uncertainties in local thermal gradient and large-scale circulation jointly contribute to wind speed forecast uncertainties. Wind forecast accuracy in the Columbia River Basin is confined by initial uncertainties in a few specific regions, providing useful information for more intense measurement and modeling studies.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
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Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, https://doi.org/10.5194/esd-12-1427-2021, 2021
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We address the question of how large an initial condition ensemble of climate model simulations should be if we are concerned with accurately projecting future changes in temperature and precipitation extremes. We find that for most cases (and both models considered), an ensemble of 20–25 members is sufficient for many extreme metrics, spatial scales and time horizons. This may leave computational resources to tackle other uncertainties in climate model simulations with our ensembles.
Zhonghua Zheng, Matthew West, Lei Zhao, Po-Lun Ma, Xiaohong Liu, and Nicole Riemer
Atmos. Chem. Phys., 21, 17727–17741, https://doi.org/10.5194/acp-21-17727-2021, https://doi.org/10.5194/acp-21-17727-2021, 2021
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Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. We present a framework for evaluating the error in aerosol mixing state induced by aerosol representation assumptions, which is one of the important contributors to structural uncertainty in aerosol models. Our study provides insights into potential improvements to model process representation for aerosols.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Yanda Zhang, Fangqun Yu, Gan Luo, Jiwen Fan, and Shuai Liu
Atmos. Chem. Phys., 21, 17433–17451, https://doi.org/10.5194/acp-21-17433-2021, https://doi.org/10.5194/acp-21-17433-2021, 2021
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This paper explores the impacts of dust on summertime convective cloud and precipitation through a numerical experiment. The result indicates that the long-range-transported dust can notably affect the properties of convective cloud and precipitation by enhancing immersion freezing and invigorating convection. We also analyze the different dust effects predicted by the Morrison and SBM schemes, which are partially attributed to the saturation adjustment approach utilized in the bulk schemes.
Hossein Dadashazar, Majid Alipanah, Miguel Ricardo A. Hilario, Ewan Crosbie, Simon Kirschler, Hongyu Liu, Richard H. Moore, Andrew J. Peters, Amy Jo Scarino, Michael Shook, K. Lee Thornhill, Christiane Voigt, Hailong Wang, Edward Winstead, Bo Zhang, Luke Ziemba, and Armin Sorooshian
Atmos. Chem. Phys., 21, 16121–16141, https://doi.org/10.5194/acp-21-16121-2021, https://doi.org/10.5194/acp-21-16121-2021, 2021
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This study investigates precipitation impacts on long-range transport of North American outflow over the western North Atlantic Ocean (WNAO). Results demonstrate that precipitation scavenging plays a significant role in modifying surface aerosol concentrations over the WNAO, especially in winter and spring due to large-scale scavenging processes. This study highlights how precipitation impacts surface aerosol properties with relevance for other marine regions vulnerable to continental outflow.
Dalei Hao, Gautam Bisht, Yu Gu, Wei-Liang Lee, Kuo-Nan Liou, and L. Ruby Leung
Geosci. Model Dev., 14, 6273–6289, https://doi.org/10.5194/gmd-14-6273-2021, https://doi.org/10.5194/gmd-14-6273-2021, 2021
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Topography exerts significant influence on the incoming solar radiation at the land surface. This study incorporated a well-validated sub-grid topographic parameterization in E3SM land model (ELM) version 1.0. The results demonstrate that sub-grid topography has non-negligible effects on surface energy budget, snow cover, and surface temperature over the Tibetan Plateau and that the ELM simulations are sensitive to season, elevation, and spatial scale.
Lili Ren, Yang Yang, Hailong Wang, Pinya Wang, Lei Chen, Jia Zhu, and Hong Liao
Atmos. Chem. Phys., 21, 15431–15445, https://doi.org/10.5194/acp-21-15431-2021, https://doi.org/10.5194/acp-21-15431-2021, 2021
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Due to the COVID-19 pandemic, human activities were strictly restricted in China. Even though anthropogenic aerosol emissions largely decreased, haze events still occurred. Our results shows that PM2.5 over the North China Plain is largely contributed by local sources. For other regions in China, PM2.5 is largely contributed from nonlocal sources. As emission reduction is a future goal, aerosol long-range transport and unfavorable meteorology are increasingly important to air quality.
Wojciech W. Grabowski and Hugh Morrison
Atmos. Chem. Phys., 21, 13997–14018, https://doi.org/10.5194/acp-21-13997-2021, https://doi.org/10.5194/acp-21-13997-2021, 2021
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The paper provides a discussion of key elements of moist convective dynamics: cloud buoyancy, latent heating, precipitation, and entrainment. The motivation comes from recent discussions concerning differences in convective dynamics in polluted and pristine environments.
Qianqian Song, Zhibo Zhang, Hongbin Yu, Paul Ginoux, and Jerry Shen
Atmos. Chem. Phys., 21, 13369–13395, https://doi.org/10.5194/acp-21-13369-2021, https://doi.org/10.5194/acp-21-13369-2021, 2021
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We present a satellite-derived global dust climatological record over the last two decades, including the monthly mean visible dust optical depth (DAOD) and vertical distribution of dust extinction coefficient at a 2º × 5º spatial resolution derived from CALIOP and MODIS. In addition, the CALIOP climatological dataset also includes dust vertical extinction profiles. Based on these two datasets, we carried out a comprehensive comparative study of the spatial and temporal climatology of dust.
Hongbin Yu, Qian Tan, Lillian Zhou, Yaping Zhou, Huisheng Bian, Mian Chin, Claire L. Ryder, Robert C. Levy, Yaswant Pradhan, Yingxi Shi, Qianqian Song, Zhibo Zhang, Peter R. Colarco, Dongchul Kim, Lorraine A. Remer, Tianle Yuan, Olga Mayol-Bracero, and Brent N. Holben
Atmos. Chem. Phys., 21, 12359–12383, https://doi.org/10.5194/acp-21-12359-2021, https://doi.org/10.5194/acp-21-12359-2021, 2021
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This study characterizes a historic African dust intrusion into the Caribbean Basin in June 2020 using satellites and NASA GEOS. Dust emissions in West Africa were large albeit not extreme. However, a unique synoptic system accumulated the dust near the coast for about 4 d before it was ventilated. Although GEOS reproduced satellite-observed plume tracks well, it substantially underestimated dust emissions and did not lift up dust high enough for ensuing long-range transport.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Liangying Zeng, Yang Yang, Hailong Wang, Jing Wang, Jing Li, Lili Ren, Huimin Li, Yang Zhou, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 21, 10745–10761, https://doi.org/10.5194/acp-21-10745-2021, https://doi.org/10.5194/acp-21-10745-2021, 2021
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Using an aerosol–climate model, the impacts of El Niño with different durations on aerosols in China are examined. The modulation on aerosol concentrations and haze days by short-duration El Niño events is 2–3 times more than that by long-duration El Niño events in China. The frequency of short-duration El Niño has been increasing significantly in recent decades, suggesting that El Niño events have exerted increasingly intense modulation on aerosol pollution in China over the past few decades.
Hossein Dadashazar, David Painemal, Majid Alipanah, Michael Brunke, Seethala Chellappan, Andrea F. Corral, Ewan Crosbie, Simon Kirschler, Hongyu Liu, Richard H. Moore, Claire Robinson, Amy Jo Scarino, Michael Shook, Kenneth Sinclair, K. Lee Thornhill, Christiane Voigt, Hailong Wang, Edward Winstead, Xubin Zeng, Luke Ziemba, Paquita Zuidema, and Armin Sorooshian
Atmos. Chem. Phys., 21, 10499–10526, https://doi.org/10.5194/acp-21-10499-2021, https://doi.org/10.5194/acp-21-10499-2021, 2021
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This study investigates the seasonal cycle of cloud drop number concentration (Nd) over the western North Atlantic Ocean (WNAO) using multiple datasets. Reasons for the puzzling discrepancy between the seasonal cycles of Nd and aerosol concentration were identified. Results indicate that Nd is highest in winter (when aerosol proxy values are often lowest) due to conditions both linked to cold-air outbreaks and that promote greater droplet activation.
Hyun Cheol Kim, Soontae Kim, Mark Cohen, Changhan Bae, Dasom Lee, Rick Saylor, Minah Bae, Eunhye Kim, Byeong-Uk Kim, Jin-Ho Yoon, and Ariel Stein
Atmos. Chem. Phys., 21, 10065–10080, https://doi.org/10.5194/acp-21-10065-2021, https://doi.org/10.5194/acp-21-10065-2021, 2021
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Global outbreaks of COVID-19 offer rare opportunities of natural experiments in emission control and corresponding responses of tropospheric chemistry. This study's novel approach investigates (1) isolating the pandemic's impact from natural and anthropogenic variations, (2) emission adjustment to reproduce real-time emissions, and (3) brute-force modeling to investigate Chinese economic activities. Results provide characteristics of the region's chemistry and emissions.
Johannes Mohrmann, Robert Wood, Tianle Yuan, Hua Song, Ryan Eastman, and Lazaros Oreopoulos
Atmos. Chem. Phys., 21, 9629–9642, https://doi.org/10.5194/acp-21-9629-2021, https://doi.org/10.5194/acp-21-9629-2021, 2021
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Observations of marine-boundary-layer conditions are composited by cloud type, based on a new classification dataset. It is found that two cloud types, representing regions of clustered and suppressed low-level clouds, occur in very similar large-scale conditions but are distinguished from each other by considering low-level circulation and surface wind fields, validating prior results from modeling.
Andrew Gettelman, Chieh-Chieh Chen, and Charles G. Bardeen
Atmos. Chem. Phys., 21, 9405–9416, https://doi.org/10.5194/acp-21-9405-2021, https://doi.org/10.5194/acp-21-9405-2021, 2021
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The COVID-19 pandemic caused significant economic disruption in 2020 and severely impacted air traffic. We use a climate model to evaluate the effect of the reductions in aviation on climate in 2020. Contrails, in general, warm the planet, and COVID-19-related reductions in contrails cooled the land surface in 2020. The timing of reductions in aviation was important, and this may change how we think about the future effects of contrails.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
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Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev., 14, 3067–3077, https://doi.org/10.5194/gmd-14-3067-2021, https://doi.org/10.5194/gmd-14-3067-2021, 2021
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The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth system models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling the representation of the more detailed physics and chemistry at a reduced computational cost while still retaining physical information.
Maria A. Zawadowicz, Kaitlyn Suski, Jiumeng Liu, Mikhail Pekour, Jerome Fast, Fan Mei, Arthur J. Sedlacek, Stephen Springston, Yang Wang, Rahul A. Zaveri, Robert Wood, Jian Wang, and John E. Shilling
Atmos. Chem. Phys., 21, 7983–8002, https://doi.org/10.5194/acp-21-7983-2021, https://doi.org/10.5194/acp-21-7983-2021, 2021
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This paper describes the results of a recent field campaign in the eastern North Atlantic, where two mass spectrometers were deployed aboard a research aircraft to measure the chemistry of aerosols and trace gases. Very clean conditions were found, dominated by local sulfate-rich acidic aerosol and very aged organics. Evidence of
long-range transport of aerosols from the continents was also identified.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Xuguang Wang, Hugh Morrison, Alexander Ryzhkov, Yachao Hu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, Jason Milbrandt, Alexei V. Korolev, and Ivan Heckman
Atmos. Chem. Phys., 21, 6919–6944, https://doi.org/10.5194/acp-21-6919-2021, https://doi.org/10.5194/acp-21-6919-2021, 2021
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Numerous small ice crystals in the tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. This study evaluated the numerical models against the airborne observations and investigated the potential cloud processes that could lead to the production of these large numbers of small ice crystals. It is found that key microphysical processes are still lacking or misrepresented in current numerical models to realistically simulate the phenomenon.
Xi Zhao, Xiaohong Liu, Vaughan T. J. Phillips, and Sachin Patade
Atmos. Chem. Phys., 21, 5685–5703, https://doi.org/10.5194/acp-21-5685-2021, https://doi.org/10.5194/acp-21-5685-2021, 2021
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Arctic mixed-phase clouds significantly influence the energy budget of the Arctic. We show that a climate model considering secondary ice production (SIP) can explain the observed cloud ice number concentrations, vertical distribution pattern, and probability density distribution of ice crystal number concentrations. The mixed-phase cloud occurrence and phase partitioning are also improved.
Hui Wan, Shixuan Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, and Huiping Yan
Geosci. Model Dev., 14, 1921–1948, https://doi.org/10.5194/gmd-14-1921-2021, https://doi.org/10.5194/gmd-14-1921-2021, 2021
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Numerical models used in weather and climate research and prediction unavoidably contain numerical errors resulting from temporal discretization, and the impact of such errors can be substantial. Complex process interactions often make it difficult to pinpoint the exact sources of such errors. This study uses a series of sensitivity experiments to identify components in a global atmosphere model that are responsible for time step sensitivities in various cloud regimes.
Jiumeng Liu, Liz Alexander, Jerome D. Fast, Rodica Lindenmaier, and John E. Shilling
Atmos. Chem. Phys., 21, 5101–5116, https://doi.org/10.5194/acp-21-5101-2021, https://doi.org/10.5194/acp-21-5101-2021, 2021
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To bridge the gaps in modeling and observational results due to insufficient understanding of aerosol properties, co-located measurements of aerosols and trace gases were conducted at SGP during the HI-SCALE campaign. Organic aerosols at the SGP site exhibited to be highly oxidized, and biogenic emissions appear to largely control the formation of organic aerosols. Seasonal variations of sources and meteorological impacts likely resulted in the highly oxygenated feature of aerosols.
Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma
Geosci. Model Dev., 14, 1575–1593, https://doi.org/10.5194/gmd-14-1575-2021, https://doi.org/10.5194/gmd-14-1575-2021, 2021
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A stochastic deep convection parameterization is implemented into the US Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of
too much light rain and too little heavy rainis largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in the deep convective parameterization.
Duseong S. Jo, Alma Hodzic, Louisa K. Emmons, Simone Tilmes, Rebecca H. Schwantes, Michael J. Mills, Pedro Campuzano-Jost, Weiwei Hu, Rahul A. Zaveri, Richard C. Easter, Balwinder Singh, Zheng Lu, Christiane Schulz, Johannes Schneider, John E. Shilling, Armin Wisthaler, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 3395–3425, https://doi.org/10.5194/acp-21-3395-2021, https://doi.org/10.5194/acp-21-3395-2021, 2021
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Secondary organic aerosol (SOA) is a major component of submicron particulate matter, but there are a lot of uncertainties in the future prediction of SOA. We used CESM 2.1 to investigate future IEPOX SOA concentration changes. The explicit chemistry predicted substantial changes in IEPOX SOA depending on the future scenario, but the parameterization predicted weak changes due to simplified chemistry, which shows the importance of correct physicochemical dependencies in future SOA prediction.
Qi Tang, Michael J. Prather, Juno Hsu, Daniel J. Ruiz, Philip J. Cameron-Smith, Shaocheng Xie, and Jean-Christophe Golaz
Geosci. Model Dev., 14, 1219–1236, https://doi.org/10.5194/gmd-14-1219-2021, https://doi.org/10.5194/gmd-14-1219-2021, 2021
Jianfeng Li, Zhe Feng, Yun Qian, and L. Ruby Leung
Earth Syst. Sci. Data, 13, 827–856, https://doi.org/10.5194/essd-13-827-2021, https://doi.org/10.5194/essd-13-827-2021, 2021
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Deep convection has different properties at different scales. We develop a 4 km h−1 observational data product of mesoscale convective systems and isolated deep convection in the United States from 2004–2017. We find that both types of convective systems contribute significantly to precipitation east of the Rocky Mountains but with distinct spatiotemporal characteristics. The data product will be useful for observational analyses and model evaluations of convection events at different scales.
Zhibo Zhang, Qianqian Song, David B. Mechem, Vincent E. Larson, Jian Wang, Yangang Liu, Mikael K. Witte, Xiquan Dong, and Peng Wu
Atmos. Chem. Phys., 21, 3103–3121, https://doi.org/10.5194/acp-21-3103-2021, https://doi.org/10.5194/acp-21-3103-2021, 2021
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This study investigates the small-scale variations and covariations of cloud microphysical properties, namely, cloud liquid water content and cloud droplet number concentration, in marine boundary layer clouds based on in situ observation from the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign. We discuss the dependence of cloud variations on vertical location in cloud and the implications for warm-rain simulations in the global climate models.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Yuwei Zhang, Jiwen Fan, Zhanqing Li, and Daniel Rosenfeld
Atmos. Chem. Phys., 21, 2363–2381, https://doi.org/10.5194/acp-21-2363-2021, https://doi.org/10.5194/acp-21-2363-2021, 2021
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Impacts of anthropogenic aerosols on deep convective clouds (DCCs) and precipitation are examined using both the Morrison bulk and spectral bin microphysics (SBM) schemes. With the SBM scheme, anthropogenic aerosols notably invigorate convective intensity and precipitation, causing better agreement between the simulated DCCs and observations; this effect is absent with the Morrison scheme, mainly due to limitations of the saturation adjustment approach for droplet condensation and evaporation.
Xi Zhao, Xiaohong Liu, Susannah M. Burrows, and Yang Shi
Atmos. Chem. Phys., 21, 2305–2327, https://doi.org/10.5194/acp-21-2305-2021, https://doi.org/10.5194/acp-21-2305-2021, 2021
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Organic sea spray particles influence aerosol and cloud processes over the ocean. This study introduces the emission, cloud droplet activation, and ice nucleation (IN) of marine organic aerosol (MOA) into the Community Earth System Model. Our results indicate that MOA IN particles dominate primary ice nucleation below 400 hPa over the Southern Ocean and Arctic boundary layer. MOA enhances cloud forcing over the Southern Ocean in the austral winter and summer.
Ryan Patnaude, Minghui Diao, Xiaohong Liu, and Suqian Chu
Atmos. Chem. Phys., 21, 1835–1859, https://doi.org/10.5194/acp-21-1835-2021, https://doi.org/10.5194/acp-21-1835-2021, 2021
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A comprehensive, in situ observation dataset of cirrus clouds was developed based on seven field campaigns, ranging from 87° N–75° S. The observations were compared with a global climate model. Several key factors for cirrus cloud formation were examined, including thermodynamics, dynamics, aerosol indirect effects and geographical locations. Model biases include lower ice mass concentrations, smaller ice crystals and weaker aerosol indirect effects.
Bo Zhang, Hongyu Liu, James H. Crawford, Gao Chen, T. Duncan Fairlie, Scott Chambers, Chang-Hee Kang, Alastair G. Williams, Kai Zhang, David B. Considine, Melissa P. Sulprizio, and Robert M. Yantosca
Atmos. Chem. Phys., 21, 1861–1887, https://doi.org/10.5194/acp-21-1861-2021, https://doi.org/10.5194/acp-21-1861-2021, 2021
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We simulate atmospheric 222Rn using the GEOS-Chem model to improve understanding of 222Rn emissions and characterize convective transport in the model. We demonstrate the potential of a customized global 222Rn emission scenario to improve simulated surface 222Rn concentrations and seasonality. We assess convective transport using observed 222Rn vertical profiles. Results have important implications for using chemical transport models to interpret the transport of trace gases and aerosols.
Jingyu Wang, Jiwen Fan, Robert A. Houze Jr., Stella R. Brodzik, Kai Zhang, Guang J. Zhang, and Po-Lun Ma
Geosci. Model Dev., 14, 719–734, https://doi.org/10.5194/gmd-14-719-2021, https://doi.org/10.5194/gmd-14-719-2021, 2021
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This paper presents an evaluation of the E3SM model against NEXRAD radar observations for the warm seasons during 2014–2016. The COSP forward simulator package is implemented in the model to generate radar reflectivity, and the NEXRAD observations are coarsened to the model resolution for comparison. The model severely underestimates the reflectivity above 4 km. Sensitivity tests on the parameters from cumulus parameterization and cloud microphysics do not improve this model bias.
Georgia Sotiropoulou, Étienne Vignon, Gillian Young, Hugh Morrison, Sebastian J. O'Shea, Thomas Lachlan-Cope, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, https://doi.org/10.5194/acp-21-755-2021, 2021
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Summer clouds have a significant impact on the radiation budget of the Antarctic surface and thus on ice-shelf melting. However, these are poorly represented in climate models due to errors in their microphysical structure, including the number of ice crystals that they contain. We show that breakup from ice particle collisions can substantially magnify the ice crystal number concentration with significant implications for surface radiation. This process is currently missing in climate models.
Hsi-Yen Ma, Chen Zhou, Yunyan Zhang, Stephen A. Klein, Mark D. Zelinka, Xue Zheng, Shaocheng Xie, Wei-Ting Chen, and Chien-Ming Wu
Geosci. Model Dev., 14, 73–90, https://doi.org/10.5194/gmd-14-73-2021, https://doi.org/10.5194/gmd-14-73-2021, 2021
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We propose an experimental design of a suite of multi-year, short-term hindcasts and compare them with corresponding observations or measurements for periods based on different weather and climate phenomena. This atypical way of evaluating model performance is particularly useful and beneficial, as these hindcasts can give scientists a robust picture of modeled precipitation, and cloud and radiation processes from their diurnal variation to year-to-year variability.
Caroline Draxl, Rochelle P. Worsnop, Geng Xia, Yelena Pichugina, Duli Chand, Julie K. Lundquist, Justin Sharp, Garrett Wedam, James M. Wilczak, and Larry K. Berg
Wind Energ. Sci., 6, 45–60, https://doi.org/10.5194/wes-6-45-2021, https://doi.org/10.5194/wes-6-45-2021, 2021
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Mountain waves can create oscillations in low-level wind speeds and subsequently in the power output of wind plants. We document such oscillations by analyzing sodar and lidar observations, nacelle wind speeds, power observations, and Weather Research and Forecasting model simulations. This research describes how mountain waves form in the Columbia River basin and affect wind energy production and their impact on operational forecasting, wind plant layout, and integration of power into the grid.
Oksana Guba, Mark A. Taylor, Andrew M. Bradley, Peter A. Bosler, and Andrew Steyer
Geosci. Model Dev., 13, 6467–6480, https://doi.org/10.5194/gmd-13-6467-2020, https://doi.org/10.5194/gmd-13-6467-2020, 2020
Tianle Yuan, Hua Song, Robert Wood, Johannes Mohrmann, Kerry Meyer, Lazaros Oreopoulos, and Steven Platnick
Atmos. Meas. Tech., 13, 6989–6997, https://doi.org/10.5194/amt-13-6989-2020, https://doi.org/10.5194/amt-13-6989-2020, 2020
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We use deep transfer learning techniques to classify satellite cloud images into different morphology types. It achieves the state-of-the-art results and can automatically process a large amount of satellite data. The algorithm will help low-cloud researchers to better understand their mesoscale organizations.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Laura Palacios-Peña, Jerome D. Fast, Enrique Pravia-Sarabia, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 13, 5897–5915, https://doi.org/10.5194/gmd-13-5897-2020, https://doi.org/10.5194/gmd-13-5897-2020, 2020
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The main objective of this work is to study the impact of the representation of aerosol size distribution on aerosol optical properties over central Europe and the Mediterranean Basin during a summertime aerosol episode using the WRF-Chem online model. Results reveal that the reduction in the standard deviation of the accumulation mode leads to the largest impacts on aerosol optical depth (AOD) representation due to a transfer of particles from the accumulation mode to the coarse mode.
Jiwen Fan, Yuwei Zhang, Zhanqing Li, Jiaxi Hu, and Daniel Rosenfeld
Atmos. Chem. Phys., 20, 14163–14182, https://doi.org/10.5194/acp-20-14163-2020, https://doi.org/10.5194/acp-20-14163-2020, 2020
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We investigate the urbanization-induced land and aerosol impacts on convective clouds and precipitation over Houston. We find that Houston urbanization notably enhances storm intensity and precipitation, with the anthropogenic aerosol effect more significant. Urban land effect strengthens sea-breeze circulation, leading to a faster development of warm cloud into mixed-phase cloud and earlier rain. The anthropogenic aerosol effect accelerates the development of storms into deep convection.
Mingxuan Wu, Xiaohong Liu, Hongbin Yu, Hailong Wang, Yang Shi, Kang Yang, Anton Darmenov, Chenglai Wu, Zhien Wang, Tao Luo, Yan Feng, and Ziming Ke
Atmos. Chem. Phys., 20, 13835–13855, https://doi.org/10.5194/acp-20-13835-2020, https://doi.org/10.5194/acp-20-13835-2020, 2020
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The spatiotemporal distributions of dust aerosol simulated by global climate models (GCMs) are highly uncertain. In this study, we evaluate dust extinction profiles, optical depth, and surface concentrations simulated in three GCMs and one reanalysis against multiple satellite retrievals and surface observations to gain process-level understanding. Our results highlight the importance of correctly representing dust emission, dry/wet deposition, and size distribution in GCMs.
Jan Kretzschmar, Johannes Stapf, Daniel Klocke, Manfred Wendisch, and Johannes Quaas
Atmos. Chem. Phys., 20, 13145–13165, https://doi.org/10.5194/acp-20-13145-2020, https://doi.org/10.5194/acp-20-13145-2020, 2020
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This study compares simulations with the ICON model at the kilometer scale to airborne radiation and cloud microphysics observations that have been derived during the ACLOUD aircraft campaign around Svalbard, Norway, in May/June 2017. We find an overestimated surface warming effect of clouds compared to the observations in our setup. This bias was reduced by considering subgrid-scale vertical motion in the activation of cloud condensation nuclei in the two-moment microphysical scheme used.
Martina Krämer, Christian Rolf, Nicole Spelten, Armin Afchine, David Fahey, Eric Jensen, Sergey Khaykin, Thomas Kuhn, Paul Lawson, Alexey Lykov, Laura L. Pan, Martin Riese, Andrew Rollins, Fred Stroh, Troy Thornberry, Veronika Wolf, Sarah Woods, Peter Spichtinger, Johannes Quaas, and Odran Sourdeval
Atmos. Chem. Phys., 20, 12569–12608, https://doi.org/10.5194/acp-20-12569-2020, https://doi.org/10.5194/acp-20-12569-2020, 2020
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To improve the representations of cirrus clouds in climate predictions, extended knowledge of their properties and geographical distribution is required. This study presents extensive airborne in situ and satellite remote sensing climatologies of cirrus and humidity, which serve as a guide to cirrus clouds. Further, exemplary radiative characteristics of cirrus types and also in situ observations of tropical tropopause layer cirrus and humidity in the Asian monsoon anticyclone are shown.
Landon A. Rieger, Jason N. S. Cole, John C. Fyfe, Stephen Po-Chedley, Philip J. Cameron-Smith, Paul J. Durack, Nathan P. Gillett, and Qi Tang
Geosci. Model Dev., 13, 4831–4843, https://doi.org/10.5194/gmd-13-4831-2020, https://doi.org/10.5194/gmd-13-4831-2020, 2020
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Recently, the stratospheric aerosol forcing dataset used as an input to the Coupled Model Intercomparison Project phase 6 was updated. This work explores the impact of those changes on the modelled historical climates in the CanESM5 and EAMv1 models. Temperature differences in the stratosphere shortly after the Pinatubo eruption are found to be significant, but surface temperatures and precipitation do not show a significant change.
Peter A. Bogenschutz, Shuaiqi Tang, Peter M. Caldwell, Shaocheng Xie, Wuyin Lin, and Yao-Sheng Chen
Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020, https://doi.org/10.5194/gmd-13-4443-2020, 2020
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This paper documents a tool that has been developed that can be used to accelerate the development and understanding of climate models. This version of the model, known as a the single-column model, is much faster to run than the full climate model, and we demonstrate that this tool can be used to quickly exploit model biases that arise due to physical processes. We show examples of how this single-column model can directly benefit the field.
Stefan Rahimi, Xiaohong Liu, Chun Zhao, Zheng Lu, and Zachary J. Lebo
Atmos. Chem. Phys., 20, 10911–10935, https://doi.org/10.5194/acp-20-10911-2020, https://doi.org/10.5194/acp-20-10911-2020, 2020
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Dark particles emitted to the atmosphere can absorb sunlight and heat the air. As these particles settle, they may darken the surface, especially over snow-covered regions like the Rocky Mountains. This darkening of the surface may lead to changes in snowpack, affecting the local meteorology and hydrology. We seek to evaluate whether these light-absorbing particles more prominently affect this region through their atmospheric presence or their on-snow presence.
Chenglai Wu, Zhaohui Lin, and Xiaohong Liu
Atmos. Chem. Phys., 20, 10401–10425, https://doi.org/10.5194/acp-20-10401-2020, https://doi.org/10.5194/acp-20-10401-2020, 2020
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This study provides a comprehensive evaluation of the global dust cycle in 15 models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We assess the global budget and associated uncertainties. We also quantify the discrepancies in each model. The results highlight the large uncertainties in both the locations and intensities of dust emission. Our study will serve as a useful reference for model communities and help further model improvements.
María A. Burgos, Elisabeth Andrews, Gloria Titos, Angela Benedetti, Huisheng Bian, Virginie Buchard, Gabriele Curci, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Anton Laakso, Julie Letertre-Danczak, Marianne T. Lund, Hitoshi Matsui, Gunnar Myhre, Cynthia Randles, Michael Schulz, Twan van Noije, Kai Zhang, Lucas Alados-Arboledas, Urs Baltensperger, Anne Jefferson, James Sherman, Junying Sun, Ernest Weingartner, and Paul Zieger
Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, https://doi.org/10.5194/acp-20-10231-2020, 2020
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We investigate how well models represent the enhancement in scattering coefficients due to particle water uptake, and perform an evaluation of several implementation schemes used in ten Earth system models. Our results show the importance of the parameterization of hygroscopicity and model chemistry as drivers of some of the observed diversity amongst model estimates. The definition of dry conditions and the phenomena taking place in this relative humidity range also impact the model evaluation.
Bethany Sutherland, Ben Kravitz, Philip J. Rasch, and Hailong Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-228, https://doi.org/10.5194/gmd-2020-228, 2020
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Through a cascade of physical mechanisms, a change in one location can trigger a response in a different location. These responses and the mechanisms that cause them are difficult to detect. Here we propose a method, using global climate models, to detect possible relationships between changes in one region and responses throughout the globe caused by that change. A change in the Pacific ocean is used as a test case to determine the effectiveness of the method.
Lili Ren, Yang Yang, Hailong Wang, Rudong Zhang, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 20, 9067–9085, https://doi.org/10.5194/acp-20-9067-2020, https://doi.org/10.5194/acp-20-9067-2020, 2020
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Observations show that the concentrations of Arctic aerosols have declined since the early 1980s, which potentially contributed to the recent, rapid Arctic warming. We found that changes in sulfate and black carbon aerosols over the midlatitudes of the Northern Hemisphere had a larger impact on Arctic temperature than other regions and that the aerosol-induced temperature change explained approximately 20 % of the observed Arctic warming during 1980–2018.
Gunnar Myhre, Bjørn H. Samset, Christian W. Mohr, Kari Alterskjær, Yves Balkanski, Nicolas Bellouin, Mian Chin, James Haywood, Øivind Hodnebrog, Stefan Kinne, Guangxing Lin, Marianne T. Lund, Joyce E. Penner, Michael Schulz, Nick Schutgens, Ragnhild B. Skeie, Philip Stier, Toshihiko Takemura, and Kai Zhang
Atmos. Chem. Phys., 20, 8855–8865, https://doi.org/10.5194/acp-20-8855-2020, https://doi.org/10.5194/acp-20-8855-2020, 2020
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The radiative forcing of the direct aerosol effects can be decomposed into clear-sky and cloudy-sky portions. In this study we use observational methods and two sets of multi-model global aerosol simulations over the industrial era to show that the contribution from cloudy-sky regions is likely weak.
Nicolas Bellouin, Will Davies, Keith P. Shine, Johannes Quaas, Johannes Mülmenstädt, Piers M. Forster, Chris Smith, Lindsay Lee, Leighton Regayre, Guy Brasseur, Natalia Sudarchikova, Idir Bouarar, Olivier Boucher, and Gunnar Myhre
Earth Syst. Sci. Data, 12, 1649–1677, https://doi.org/10.5194/essd-12-1649-2020, https://doi.org/10.5194/essd-12-1649-2020, 2020
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Quantifying the imbalance in the Earth's energy budget caused by human activities is important to understand and predict climate changes. This study presents new estimates of the imbalance caused by changes in atmospheric concentrations of carbon dioxide, methane, ozone, and particles of pollution. Over the period 2003–2017, the overall imbalance has been positive, indicating that the climate system has gained energy and will warm further.
Wenchao Han, Zhanqing Li, Fang Wu, Yuwei Zhang, Jianping Guo, Tianning Su, Maureen Cribb, Jiwen Fan, Tianmeng Chen, Jing Wei, and Seoung-Soo Lee
Atmos. Chem. Phys., 20, 6479–6493, https://doi.org/10.5194/acp-20-6479-2020, https://doi.org/10.5194/acp-20-6479-2020, 2020
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Observational data and model simulation were used to analyze the daytime urban heat island intensity (UHII) under polluted and clean conditions in China. We found that aerosols reduce the UHII in summer but increase the UHII in winter. Two mechanisms, the aerosol radiative effect (ARE) and the aerosol dynamic effect (ADE), behave differently in summer and winter. In summer, the UHII is mainly affected by the ARE, and the ADE is weak, and the opposite is the case in winter.
Montserrat Costa-Surós, Odran Sourdeval, Claudia Acquistapace, Holger Baars, Cintia Carbajal Henken, Christa Genz, Jonas Hesemann, Cristofer Jimenez, Marcel König, Jan Kretzschmar, Nils Madenach, Catrin I. Meyer, Roland Schrödner, Patric Seifert, Fabian Senf, Matthias Brueck, Guido Cioni, Jan Frederik Engels, Kerstin Fieg, Ksenia Gorges, Rieke Heinze, Pavan Kumar Siligam, Ulrike Burkhardt, Susanne Crewell, Corinna Hoose, Axel Seifert, Ina Tegen, and Johannes Quaas
Atmos. Chem. Phys., 20, 5657–5678, https://doi.org/10.5194/acp-20-5657-2020, https://doi.org/10.5194/acp-20-5657-2020, 2020
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The impact of anthropogenic aerosols on clouds is a key uncertainty in climate change. This study analyses large-domain simulations with a new high-resolution model to investigate the differences in clouds between 1985 and 2013 comparing multiple observational datasets. The differences in aerosol and in cloud droplet concentrations are clearly detectable. For other quantities, the detection and attribution proved difficult, despite a substantial impact on the Earth's energy budget.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
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We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
Chenxi Wang, Steven Platnick, Kerry Meyer, Zhibo Zhang, and Yaping Zhou
Atmos. Meas. Tech., 13, 2257–2277, https://doi.org/10.5194/amt-13-2257-2020, https://doi.org/10.5194/amt-13-2257-2020, 2020
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A machine-learning (ML)-based approach that can be used for cloud mask and phase detection is developed. An all-day model that uses infrared (IR) observations and a daytime model that uses shortwave and IR observations from a passive instrument are trained separately for different surface types. The training datasets are selected by using reference pixel types from collocated space lidar. The ML approach is validated carefully and the overall performance is better than traditional methods.
Yufei Zou, Yuhang Wang, Zuowei Xie, Hailong Wang, and Philip J. Rasch
Atmos. Chem. Phys., 20, 4999–5017, https://doi.org/10.5194/acp-20-4999-2020, https://doi.org/10.5194/acp-20-4999-2020, 2020
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We analyze the relationship between winter air stagnation and pollution extremes over eastern China and preceding Arctic sea ice loss based on climate modeling and dynamic diagnoses. We find significant increases in both the probability and intensity of air stagnation extremes in the modeling result driven by regional sea ice and sea surface temperature changes over the Pacific sector of the Arctic. We reveal the considerable impact of the Arctic climate change on mid-latitude weather extremes.
Erin A. Riley, Jessica M. Kleiss, Laura D. Riihimaki, Charles N. Long, Larry K. Berg, and Evgueni Kassianov
Atmos. Meas. Tech., 13, 2099–2117, https://doi.org/10.5194/amt-13-2099-2020, https://doi.org/10.5194/amt-13-2099-2020, 2020
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Discrepancies in hourly shallow cumuli cover estimates can be substantial. Instrument detection differences contribute to long-term bias in shallow cumuli cover estimates, whereas narrow field-of-view configurations impact measurement uncertainty as averaging time decreases. A new tool is introduced to visually assess both impacts on sub-hourly cloud cover estimates. Accurate shallow cumuli cover estimation is needed for model–observation comparisons and studying cloud-surface interactions.
Tongwen Wu, Fang Zhang, Jie Zhang, Weihua Jie, Yanwu Zhang, Fanghua Wu, Laurent Li, Jinghui Yan, Xiaohong Liu, Xiao Lu, Haiyue Tan, Lin Zhang, Jun Wang, and Aixue Hu
Geosci. Model Dev., 13, 977–1005, https://doi.org/10.5194/gmd-13-977-2020, https://doi.org/10.5194/gmd-13-977-2020, 2020
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This paper describes the first version of the Beijing Climate Center (BCC) fully coupled Earth System Model with interactive atmospheric chemistry and aerosols (BCC-ESM1). It is one of the models at the BCC for the Coupled Model Intercomparison Project Phase 6 (CMIP6). The CMIP6 Aerosol Chemistry Model Intercomparison Project (AerChemMIP) experiment using BCC-ESM1 has been finished. The evaluations show an overall good agreement between BCC-ESM1 simulations and observations in the 20th century.
Yang Yang, Sijia Lou, Hailong Wang, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 20, 2579–2590, https://doi.org/10.5194/acp-20-2579-2020, https://doi.org/10.5194/acp-20-2579-2020, 2020
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Aerosol concentration decreased in Europe during 1980–2018, of which 7 % was induced by the changes in non-European emissions. Aerosols transported from other source regions are increasingly important to air quality in Europe. Contributions to the sulfate radiative forcing over Europe from both European and non-European emissions should decrease at a comparable rate in the next three decades. Future changes in non-European emissions are important in causing regional climate change in Europe.
Claudia Unglaub, Karoline Block, Johannes Mülmenstädt, Odran Sourdeval, and Johannes Quaas
Atmos. Chem. Phys., 20, 2407–2418, https://doi.org/10.5194/acp-20-2407-2020, https://doi.org/10.5194/acp-20-2407-2020, 2020
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In cloud research, it is necessary to classify clouds. The World Meteorological Organization proposes distinguishing stratiform and cumuliform clouds in three altitude layers. The paper explains why previous approaches to classify clouds fail for many applications and proposes a new classification on the basis of new approaches for satellite retrievals to derive cloud-base height, in combination with cloud inhomogeneity. It is demonstrated that this discriminates cloud characteristics well.
Fan Mei, Jian Wang, Jennifer M. Comstock, Ralf Weigel, Martina Krämer, Christoph Mahnke, John E. Shilling, Johannes Schneider, Christiane Schulz, Charles N. Long, Manfred Wendisch, Luiz A. T. Machado, Beat Schmid, Trismono Krisna, Mikhail Pekour, John Hubbe, Andreas Giez, Bernadett Weinzierl, Martin Zoeger, Mira L. Pöhlker, Hans Schlager, Micael A. Cecchini, Meinrat O. Andreae, Scot T. Martin, Suzane S. de Sá, Jiwen Fan, Jason Tomlinson, Stephen Springston, Ulrich Pöschl, Paulo Artaxo, Christopher Pöhlker, Thomas Klimach, Andreas Minikin, Armin Afchine, and Stephan Borrmann
Atmos. Meas. Tech., 13, 661–684, https://doi.org/10.5194/amt-13-661-2020, https://doi.org/10.5194/amt-13-661-2020, 2020
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In 2014, the US DOE G1 aircraft and the German HALO aircraft overflew the Amazon basin to study how aerosols influence cloud cycles under a clean condition and around a tropical megacity. This paper describes how to meaningfully compare similar measurements from two research aircraft and identify the potential measurement issue. We also discuss the uncertainty range for each measurement for further usage in model evaluation and satellite data validation.
Hailong Wang, Jeremy G. Fyke, Jan T. M. Lenaerts, Jesse M. Nusbaumer, Hansi Singh, David Noone, Philip J. Rasch, and Rudong Zhang
The Cryosphere, 14, 429–444, https://doi.org/10.5194/tc-14-429-2020, https://doi.org/10.5194/tc-14-429-2020, 2020
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Using a climate model with unique water source tagging, we found that sea-ice anomalies in the Southern Ocean and accompanying SST changes have a significant influence on Antarctic precipitation and its source attribution through their direct impact on moisture sources and indirect impact on moisture transport. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies on regional Antarctic precipitation.
Yufei Zou, Yuhang Wang, Yun Qian, Hanqin Tian, Jia Yang, and Ernesto Alvarado
Atmos. Chem. Phys., 20, 995–1020, https://doi.org/10.5194/acp-20-995-2020, https://doi.org/10.5194/acp-20-995-2020, 2020
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Fire is a natural phenomenon that has a long history of interactions with the environment and human activity. The complex interactions were less represented in previous fire and climate models. Here we use a new global fire model with improved modeling capability to study how fire responds and contributes to climate change. The modeling results show increased global fire activity in the future driven by climate change, which in turn modulates local and remote climate and ecosystems.
Edward Gryspeerdt, Johannes Mülmenstädt, Andrew Gettelman, Florent F. Malavelle, Hugh Morrison, David Neubauer, Daniel G. Partridge, Philip Stier, Toshihiko Takemura, Hailong Wang, Minghuai Wang, and Kai Zhang
Atmos. Chem. Phys., 20, 613–623, https://doi.org/10.5194/acp-20-613-2020, https://doi.org/10.5194/acp-20-613-2020, 2020
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Aerosol radiative forcing is a key uncertainty in our understanding of the human forcing of the climate, with much of this uncertainty coming from aerosol impacts on clouds. Observation-based estimates of the radiative forcing are typically smaller than those from global models, but it is not clear if they are more reliable. This work shows how the forcing components in global climate models can be identified, highlighting similarities between the two methods and areas for future investigation.
Hongbin Yu, Yang Yang, Hailong Wang, Qian Tan, Mian Chin, Robert C. Levy, Lorraine A. Remer, Steven J. Smith, Tianle Yuan, and Yingxi Shi
Atmos. Chem. Phys., 20, 139–161, https://doi.org/10.5194/acp-20-139-2020, https://doi.org/10.5194/acp-20-139-2020, 2020
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Emissions and long-range transport of mineral dust and
combustion-related aerosol from burning fossil fuels and biomass vary from year to year, driven by the evolution of the economy and changes in meteorological conditions and environmental regulations. This study offers both satellite and model perspectives on interannual variability and possible trends in combustion aerosol and dust in major continental outflow regions over the past 15 years (2003–2017).
Johannes Mülmenstädt, Edward Gryspeerdt, Marc Salzmann, Po-Lun Ma, Sudhakar Dipu, and Johannes Quaas
Atmos. Chem. Phys., 19, 15415–15429, https://doi.org/10.5194/acp-19-15415-2019, https://doi.org/10.5194/acp-19-15415-2019, 2019
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The effect of aerosol–cloud interactions (ACIs) on Earth's energy budget continues to be highly uncertain. We decompose the effective radiative forcing by ACIs (ERFaci) into the instantaneous forcing due to anthropogenic increases in the number of cloud droplets and fast responses of cloud properties to the droplet number perturbation in the ECHAM–HAMMOZ aerosol–climate model. This decomposition maps onto the IPCC's Fifth Assessment Report analysis of ERFaci more directly than previous work.
Laura Bianco, Irina V. Djalalova, James M. Wilczak, Joseph B. Olson, Jaymes S. Kenyon, Aditya Choukulkar, Larry K. Berg, Harindra J. S. Fernando, Eric P. Grimit, Raghavendra Krishnamurthy, Julie K. Lundquist, Paytsar Muradyan, Mikhail Pekour, Yelena Pichugina, Mark T. Stoelinga, and David D. Turner
Geosci. Model Dev., 12, 4803–4821, https://doi.org/10.5194/gmd-12-4803-2019, https://doi.org/10.5194/gmd-12-4803-2019, 2019
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During the second Wind Forecast Improvement Project, improvements to the parameterizations were applied to the High Resolution Rapid Refresh model and its nested version. The impacts of the new parameterizations on the forecast of 80 m wind speeds and power are assessed, using sodars and profiling lidars observations for comparison. Improvements are evaluated as a function of the model’s initialization time, forecast horizon, time of the day, season, site elevation, and meteorological phenomena.
Zhiyuan Hu, Jianping Huang, Chun Zhao, Yuanyuan Ma, Qinjian Jin, Yun Qian, L. Ruby Leung, Jianrong Bi, and Jianmin Ma
Atmos. Chem. Phys., 19, 12709–12730, https://doi.org/10.5194/acp-19-12709-2019, https://doi.org/10.5194/acp-19-12709-2019, 2019
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This study investigates aerosol chemical compositions and relative contributions to total aerosols in the western US. The results show that trans-Pacific aerosols have a maximum concentration in the boreal spring, with the greatest contribution from dust. Over western North America, the trans-Pacific aerosols dominate the column-integrated aerosol mass and number concentration. However, near the surface, aerosols mainly originated from local emissions.
Fang Li, Maria Val Martin, Meinrat O. Andreae, Almut Arneth, Stijn Hantson, Johannes W. Kaiser, Gitta Lasslop, Chao Yue, Dominique Bachelet, Matthew Forrest, Erik Kluzek, Xiaohong Liu, Stephane Mangeon, Joe R. Melton, Daniel S. Ward, Anton Darmenov, Thomas Hickler, Charles Ichoku, Brian I. Magi, Stephen Sitch, Guido R. van der Werf, Christine Wiedinmyer, and Sam S. Rabin
Atmos. Chem. Phys., 19, 12545–12567, https://doi.org/10.5194/acp-19-12545-2019, https://doi.org/10.5194/acp-19-12545-2019, 2019
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Fire emissions are critical for atmospheric composition, climate, carbon cycle, and air quality. We provide the first global multi-model fire emission reconstructions for 1700–2012, including carbon and 33 species of trace gases and aerosols, based on the nine state-of-the-art global fire models that participated in FireMIP. We also provide information on the recent status and limitations of the model-based reconstructions and identify the main uncertainty sources in their long-term changes.
Mingchen Ma, Yang Gao, Yuhang Wang, Shaoqing Zhang, L. Ruby Leung, Cheng Liu, Shuxiao Wang, Bin Zhao, Xing Chang, Hang Su, Tianqi Zhang, Lifang Sheng, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 19, 12195–12207, https://doi.org/10.5194/acp-19-12195-2019, https://doi.org/10.5194/acp-19-12195-2019, 2019
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Ozone pollution has become severe in China, and extremely high ozone episodes occurred in summer 2017 over the North China Plain. While meteorology impacts are clear, we find that enhanced biogenic emissions, previously ignored by the community, driven by high vapor pressure deficit, land cover change and urban landscape contribute substantially to ozone formation. This study has significant implications for ozone pollution control with more frequent heat waves and urbanization growth in future.
Stefan Rahimi, Xiaohong Liu, Chenglai Wu, William K. Lau, Hunter Brown, Mingxuan Wu, and Yun Qian
Atmos. Chem. Phys., 19, 12025–12049, https://doi.org/10.5194/acp-19-12025-2019, https://doi.org/10.5194/acp-19-12025-2019, 2019
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Light-absorbing particles impact the Earth system in a variety of ways. They can warm the atmosphere by their very presence, or they can warm the atmosphere after they deposit on snow, warm it, and warm the overlying atmosphere. This paper focuses on these two processes as they pertain to black carbon and dust's impacts on the South Asian monsoon. It will be shown that these two aerosols have a significant effect on the monsoon.
Jacob Schacht, Bernd Heinold, Johannes Quaas, John Backman, Ribu Cherian, Andre Ehrlich, Andreas Herber, Wan Ting Katty Huang, Yutaka Kondo, Andreas Massling, P. R. Sinha, Bernadett Weinzierl, Marco Zanatta, and Ina Tegen
Atmos. Chem. Phys., 19, 11159–11183, https://doi.org/10.5194/acp-19-11159-2019, https://doi.org/10.5194/acp-19-11159-2019, 2019
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The Arctic is warming faster than the rest of Earth. Black carbon (BC) aerosol contributes to this Arctic amplification by direct and indirect aerosol radiative effects while distributed in air or deposited on snow and ice. The aerosol-climate model ECHAM-HAM is used to estimate direct aerosol radiative effect (DRE). Airborne and near-surface BC measurements are used to evaluate the model and give an uncertainty range for the burden and DRE of Arctic BC caused by different emission inventories.
Douglas S. Hamilton, Rachel A. Scanza, Yan Feng, Joseph Guinness, Jasper F. Kok, Longlei Li, Xiaohong Liu, Sagar D. Rathod, Jessica S. Wan, Mingxuan Wu, and Natalie M. Mahowald
Geosci. Model Dev., 12, 3835–3862, https://doi.org/10.5194/gmd-12-3835-2019, https://doi.org/10.5194/gmd-12-3835-2019, 2019
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MIMI v1.0 was designed for use within Earth system models to simulate the 3-D emission, atmospheric processing, and deposition of iron and its soluble fraction. Understanding the iron cycle is important due to its role as an essential micronutrient for ocean phytoplankton; its supply limits primary productivity in many of the world's oceans. Human activity has perturbed the iron cycle, and MIMI is capable of diagnosing many of these impacts; hence, it is important for future climate studies.
Lei Lin, Andrew Gettelman, Yangyang Xu, Chenglai Wu, Zhili Wang, Nan Rosenbloom, Susan C. Bates, and Wenjie Dong
Geosci. Model Dev., 12, 3773–3793, https://doi.org/10.5194/gmd-12-3773-2019, https://doi.org/10.5194/gmd-12-3773-2019, 2019
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Here we evaluate the performance of the Community Atmosphere Model version 6 (CAM6) released in 2018, with the default 1º horizontal resolution and a higher-resolution simulation (approximately 0.25º), against various precipitation observational datasets over Asia. With the prognostic treatment of precipitation processes (which is missing in CAM5) and the new microphysics module, CAM6 is able to better simulate climatological mean and extreme precipitation over Asia.
Jan Kretzschmar, Marc Salzmann, Johannes Mülmenstädt, and Johannes Quaas
Atmos. Chem. Phys., 19, 10571–10589, https://doi.org/10.5194/acp-19-10571-2019, https://doi.org/10.5194/acp-19-10571-2019, 2019
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This study aims to explore Arctic cloud properties in the atmospheric circulation model ECHAM6. We compare cloud properties in the model to satellite observations using a satellite simulator and show that ECHAM6 overestimates low-level liquid-containing clouds. In sensitivity studies, we show that this bias can be related to cloud microphysics and surface fluxes.
Hailing Jia, Xiaoyan Ma, Johannes Quaas, Yan Yin, and Tom Qiu
Atmos. Chem. Phys., 19, 8879–8896, https://doi.org/10.5194/acp-19-8879-2019, https://doi.org/10.5194/acp-19-8879-2019, 2019
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We systematically assess how and to what extent satellite retrieval biases may affect correlations, as well as explore the underlying physical mechanisms. It is noted that the retrieval biases of both cloud and aerosol can result in a serious overestimation of the slope of CER–AI. Positive correlations more likely to occur in the case of drier cloud top and stronger turbulence in clouds, implying entrainment mixing might be a possible physical interpretation for such a positive CER–AI slope.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
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Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Chun Zhao, Mingyue Xu, Yu Wang, Meixin Zhang, Jianping Guo, Zhiyuan Hu, L. Ruby Leung, Michael Duda, and William Skamarock
Geosci. Model Dev., 12, 2707–2726, https://doi.org/10.5194/gmd-12-2707-2019, https://doi.org/10.5194/gmd-12-2707-2019, 2019
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Simulations at global uniform and variable resolutions share similar characteristics of precipitation and wind in the refined region. The experiments reveal the significant impacts of resolution on simulating the distribution and intensity of precipitation and updrafts. This study provides evidence supporting the use of convection-permitting global variable-resolution simulations to study extreme precipitation.
Qi Tang, Stephen A. Klein, Shaocheng Xie, Wuyin Lin, Jean-Christophe Golaz, Erika L. Roesler, Mark A. Taylor, Philip J. Rasch, David C. Bader, Larry K. Berg, Peter Caldwell, Scott E. Giangrande, Richard B. Neale, Yun Qian, Laura D. Riihimaki, Charles S. Zender, Yuying Zhang, and Xue Zheng
Geosci. Model Dev., 12, 2679–2706, https://doi.org/10.5194/gmd-12-2679-2019, https://doi.org/10.5194/gmd-12-2679-2019, 2019
Chandan Sarangi, Yun Qian, Karl Rittger, Kathryn J. Bormann, Ying Liu, Hailong Wang, Hui Wan, Guangxing Lin, and Thomas H. Painter
Atmos. Chem. Phys., 19, 7105–7128, https://doi.org/10.5194/acp-19-7105-2019, https://doi.org/10.5194/acp-19-7105-2019, 2019
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Radiative forcing induced by deposition of light-absorbing particles (LAPs) on snow is an important surface forcing. Here, we have used high-resolution WRF-Chem (coupled with online snow–LAP–radiation model) simulations for 2013–2014 to estimate the spatial variation in LAP-induced snow albedo darkening effect in high-mountain Asia. Significant improvement in simulated LAP–snow properties with use of a higher spatial resolution for the same model configuration is illustrated over this region.
Tongwen Wu, Yixiong Lu, Yongjie Fang, Xiaoge Xin, Laurent Li, Weiping Li, Weihua Jie, Jie Zhang, Yiming Liu, Li Zhang, Fang Zhang, Yanwu Zhang, Fanghua Wu, Jianglong Li, Min Chu, Zaizhi Wang, Xueli Shi, Xiangwen Liu, Min Wei, Anning Huang, Yaocun Zhang, and Xiaohong Liu
Geosci. Model Dev., 12, 1573–1600, https://doi.org/10.5194/gmd-12-1573-2019, https://doi.org/10.5194/gmd-12-1573-2019, 2019
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This work presents advancements of the BCC model transition from CMIP5 to CMIP6, especially in the model resolution and its physics. Compared with BCC CMIP5 models, the BCC CMIP6 model shows significant improvements in historical simulations in many aspects including tropospheric air temperature and circulation at global and regional scales in East Asia, climate variability at different timescales (QBO, MJO, and diurnal cycle of precipitation), and the long-term trend of global air temperature.
Edward Gryspeerdt, Tom Goren, Odran Sourdeval, Johannes Quaas, Johannes Mülmenstädt, Sudhakar Dipu, Claudia Unglaub, Andrew Gettelman, and Matthew Christensen
Atmos. Chem. Phys., 19, 5331–5347, https://doi.org/10.5194/acp-19-5331-2019, https://doi.org/10.5194/acp-19-5331-2019, 2019
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The liquid water path (LWP) is the strongest control on cloud albedo, such that a small change in LWP can have a large radiative impact. By changing the droplet number concentration (Nd) aerosols may be able to change the LWP, but the sign and magnitude of the effect is unclear. This work uses satellite data to investigate the relationship between Nd and LWP at a global scale and in response to large aerosol perturbations, suggesting that a strong decrease in LWP at high Nd may be overestimated.
Luca Bertagna, Michael Deakin, Oksana Guba, Daniel Sunderland, Andrew M. Bradley, Irina K. Tezaur, Mark A. Taylor, and Andrew G. Salinger
Geosci. Model Dev., 12, 1423–1441, https://doi.org/10.5194/gmd-12-1423-2019, https://doi.org/10.5194/gmd-12-1423-2019, 2019
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We use Kokkos, a C++ library for on-node parallelism, to achieve a performance-portable implementation of HOMME, the atmosphere component of the Earth Energy Exascale System Model. The increasing diversity of high-performance computing (HPC) architectures and the demand for higher resolutions create new challenges when writing efficient code. With Kokkos, we obtain a single code base that performs well on current HPC platforms and enables portable performance to future HPC architectures.
Nicola Bodini, Julie K. Lundquist, Raghavendra Krishnamurthy, Mikhail Pekour, Larry K. Berg, and Aditya Choukulkar
Atmos. Chem. Phys., 19, 4367–4382, https://doi.org/10.5194/acp-19-4367-2019, https://doi.org/10.5194/acp-19-4367-2019, 2019
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To improve the parameterization of the turbulence dissipation rate (ε) in numerical weather prediction models, we have assessed its temporal and spatial variability at various scales in the Columbia River Gorge during the WFIP2 field experiment. The turbulence dissipation rate shows large spatial variability, even at the microscale, with larger values in sites located downwind of complex orographic structures or in wind farm wakes. Distinct diurnal and seasonal cycles in ε have also been found.
Doug M. Smith, James A. Screen, Clara Deser, Judah Cohen, John C. Fyfe, Javier García-Serrano, Thomas Jung, Vladimir Kattsov, Daniela Matei, Rym Msadek, Yannick Peings, Michael Sigmond, Jinro Ukita, Jin-Ho Yoon, and Xiangdong Zhang
Geosci. Model Dev., 12, 1139–1164, https://doi.org/10.5194/gmd-12-1139-2019, https://doi.org/10.5194/gmd-12-1139-2019, 2019
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The Polar Amplification Model Intercomparison Project (PAMIP) is an endorsed contribution to the sixth Coupled Model Intercomparison Project (CMIP6). It will investigate the causes and global consequences of polar amplification through coordinated multi-model numerical experiments. This paper documents the experimental protocol.
Joseph A. Finlon, Greg M. McFarquhar, Stephen W. Nesbitt, Robert M. Rauber, Hugh Morrison, Wei Wu, and Pengfei Zhang
Atmos. Chem. Phys., 19, 3621–3643, https://doi.org/10.5194/acp-19-3621-2019, https://doi.org/10.5194/acp-19-3621-2019, 2019
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A new approach describing the relationship between ice crystal mass (m) and dimension (D) is derived, characterizing it as a set of
equally realizableparameters based on the natural variability in cloud conditions observed by aircraft over the Great Plains. Results from this approach address shortcomings of microphysical parameterization schemes and remote sensing retrievals that employ a single m–D relation for a given ice species or environment.
Christoph Böhm, Odran Sourdeval, Johannes Mülmenstädt, Johannes Quaas, and Susanne Crewell
Atmos. Meas. Tech., 12, 1841–1860, https://doi.org/10.5194/amt-12-1841-2019, https://doi.org/10.5194/amt-12-1841-2019, 2019
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The cloud base height (CBH) is important for air traffic, for describing the energy budget of the Earth and for other applications. Ground-based CBH measurements are only available for individual sites and mostly limited to land. Satellites are a powerful tool for global coverage. While the cloud top height is derived operationally, the derivation of CBH from space is more difficult as the clouds hide their base. Here, we present a method to retrieve the CBH from multi-angle satellite data.
Antonio Di Noia, Otto P. Hasekamp, Bastiaan van Diedenhoven, and Zhibo Zhang
Atmos. Meas. Tech., 12, 1697–1716, https://doi.org/10.5194/amt-12-1697-2019, https://doi.org/10.5194/amt-12-1697-2019, 2019
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We present a neural network algorithm for the retrieval of cloud physical properties from multi-angle polarimetric measurements. We have trained the algorithm on a large dataset of synthetic measurements and applied it to a year of POLDER-3 data. A comparison against MODIS cloud products reveals that our algorithm is capable of performing cloud property retrievals on a global scale and possibly improves the estimates of cloud effective radius over land with respect to existing POLDER-3 products.
Colin M. Zarzycki, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Paul A. Ullrich, David M. Hall, Mark A. Taylor, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Xi Chen, Lucas Harris, Marco Giorgetta, Daniel Reinert, Christian Kühnlein, Robert Walko, Vivian Lee, Abdessamad Qaddouri, Monique Tanguay, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Sang-Hun Park, Joseph B. Klemp, and William C. Skamarock
Geosci. Model Dev., 12, 879–892, https://doi.org/10.5194/gmd-12-879-2019, https://doi.org/10.5194/gmd-12-879-2019, 2019
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We summarize the results of the Dynamical Core Model Intercomparison Project's idealized supercell test case. Supercells are storm-scale weather phenomena that are a key target for next-generation, non-hydrostatic weather prediction models. We show that the dynamical cores of most global numerical models converge between approximately 1 and 0.5 km grid spacing for this test, although differences in final solution exist, particularly due to differing grid discretizations and numerical diffusion.
Yang Yang, Steven J. Smith, Hailong Wang, Catrin M. Mills, and Philip J. Rasch
Atmos. Chem. Phys., 19, 2405–2420, https://doi.org/10.5194/acp-19-2405-2019, https://doi.org/10.5194/acp-19-2405-2019, 2019
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Black carbon (BC) particles exert a potentially large warming influence on the
Earth system. We evaluate regional climate responses, non-linearity, and short-term transient responses to BC emission perturbations. We found that climate responses do not scale linearity with emissions and BC impacts temperature much faster than greenhouse gas forcing. Removing present-day BC emissions results in discernible surface temperature changes for only limited regions of the globe.
Daniel T. McCoy, Paul R. Field, Gregory S. Elsaesser, Alejandro Bodas-Salcedo, Brian H. Kahn, Mark D. Zelinka, Chihiro Kodama, Thorsten Mauritsen, Benoit Vanniere, Malcolm Roberts, Pier L. Vidale, David Saint-Martin, Aurore Voldoire, Rein Haarsma, Adrian Hill, Ben Shipway, and Jonathan Wilkinson
Atmos. Chem. Phys., 19, 1147–1172, https://doi.org/10.5194/acp-19-1147-2019, https://doi.org/10.5194/acp-19-1147-2019, 2019
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The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
Zhibo Zhang, Hua Song, Po-Lun Ma, Vincent E. Larson, Minghuai Wang, Xiquan Dong, and Jianwu Wang
Atmos. Chem. Phys., 19, 1077–1096, https://doi.org/10.5194/acp-19-1077-2019, https://doi.org/10.5194/acp-19-1077-2019, 2019
Junxi Zhang, Yang Gao, L. Ruby Leung, Kun Luo, Huan Liu, Jean-Francois Lamarque, Jianren Fan, Xiaohong Yao, Huiwang Gao, and Tatsuya Nagashima
Atmos. Chem. Phys., 19, 887–900, https://doi.org/10.5194/acp-19-887-2019, https://doi.org/10.5194/acp-19-887-2019, 2019
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ACCMIP simulations were used to study NOy deposition over East Asia in the future. Both dry and wet NOy deposition show significant decreases in the 2100s under RCP4.5 and RCP8.5 due to large anthropogenic emission reduction. The changes in climate only significantly affect the wet deposition primarily linked to changes in precipitation. Over the coastal seas of China, weaker transport of NOy from land due to emission reduction infers a larger impact from shipping and lightning emissions.
Ge Zhang, Yang Gao, Wenju Cai, L. Ruby Leung, Shuxiao Wang, Bin Zhao, Minghuai Wang, Huayao Shan, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 19, 565–576, https://doi.org/10.5194/acp-19-565-2019, https://doi.org/10.5194/acp-19-565-2019, 2019
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Based on observed data, this study reveals a distinct seesaw feature of abnormally high and low PM2.5 concentrations in December 2015 and January 2016 over North China. The mechanism of the seesaw pattern was found to be linked to a super El Niño and the Arctic Oscillation (AO). During the mature phase of El Niño in December 2015, the weakened East Asian winter monsoon favors strong haze formation; however, the circulation pattern was reversed in the next month due to the phase change of the AO.
Tao Zhang, Minghua Zhang, Wuyin Lin, Yanluan Lin, Wei Xue, Haiyang Yu, Juanxiong He, Xiaoge Xin, Hsi-Yen Ma, Shaocheng Xie, and Weimin Zheng
Geosci. Model Dev., 11, 5189–5201, https://doi.org/10.5194/gmd-11-5189-2018, https://doi.org/10.5194/gmd-11-5189-2018, 2018
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Tuning of uncertain parameters in global atmospheric general circulation models has extreme computational cost. In this study, we provide an automatic tuning method by combining an auto-optimization algorithm with hindcasts to improve climate simulations in CAM5. The tuning improved the overall performance of a well-calibrated model by about 10 %. The computational cost of the entire auto-tuning procedure is just equivalent to a single 20-year simulation of CAM5.
Johannes Mülmenstädt, Odran Sourdeval, David S. Henderson, Tristan S. L'Ecuyer, Claudia Unglaub, Leonore Jungandreas, Christoph Böhm, Lynn M. Russell, and Johannes Quaas
Earth Syst. Sci. Data, 10, 2279–2293, https://doi.org/10.5194/essd-10-2279-2018, https://doi.org/10.5194/essd-10-2279-2018, 2018
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One of the key pieces of information about a cloud is how high its base is. Unlike cloud top, cloud base is hard to observe from a satellite perspective – the cloud blocks the view. But without using satellites, it is difficult to compile global datasets. Here we describe how we worked around the limitations of a cloud-detecting laser satellite to observe global cloud base heights. This dataset will expand our knowledge of the cloudy atmosphere and its interaction with the planetary surface.
Hunter Brown, Xiaohong Liu, Yan Feng, Yiquan Jiang, Mingxuan Wu, Zheng Lu, Chenglai Wu, Shane Murphy, and Rudra Pokhrel
Atmos. Chem. Phys., 18, 17745–17768, https://doi.org/10.5194/acp-18-17745-2018, https://doi.org/10.5194/acp-18-17745-2018, 2018
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In climate models, organic carbon (OC) in wildfire smoke has been treated as an atmospheric cooling component by reflecting sunlight back to space. This study incorporates the observationally identified absorbing brown carbon component of OC into the Community Earth System Model, improving the agreement between the model and observations and effectively increasing absorption of solar radiation. This change contributes to altered atmospheric dynamics and changes in cloud cover in the model.
Anna Possner, Hailong Wang, Robert Wood, Ken Caldeira, and Thomas P. Ackerman
Atmos. Chem. Phys., 18, 17475–17488, https://doi.org/10.5194/acp-18-17475-2018, https://doi.org/10.5194/acp-18-17475-2018, 2018
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We quantify aerosol–cloud radiative interactions in a regime of deep open-cell stratocumuli (boundary layer depth 1.5 km), a regime which remains largely unexplored within this context and yet is more dominant than cases of shallow stratocumuli previously studied. We simulate substantial increases in albedo in a regime where ship tracks are not found and argue that such changes may escape detection and attribution through remote sensing due to the large natural variability in the system.
Peng Wu, Baike Xi, Xiquan Dong, and Zhibo Zhang
Atmos. Chem. Phys., 18, 17405–17420, https://doi.org/10.5194/acp-18-17405-2018, https://doi.org/10.5194/acp-18-17405-2018, 2018
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Prescribed autoconversion and accretion enhancement factors in GCM warm-rain parameterizations contribute partially to the too-frequent and too-light problem in precipitation simulation. The two factors should be regime- and resolution-dependent. A decreased autoconversion enhancement factor and increased accretion enhancement factor in the Morrison and Gettleman (2008) scheme can improve the simulated precipitation frequency and intensity. The two factors for other schemes are also suggested.
Jiahui Zhang, Dao-Yi Gong, Rui Mao, Jing Yang, Ziyin Zhang, and Yun Qian
Atmos. Chem. Phys., 18, 16775–16791, https://doi.org/10.5194/acp-18-16775-2018, https://doi.org/10.5194/acp-18-16775-2018, 2018
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The Chinese Spring Festival (also known as the Chinese New Year or Lunar New Year) is the most important festival in China. This paper reports that during the Chinese Spring Festival, the precipitation over southern China has been significantly reduced. The precipitation reduction is due to anomalous northerly winds. We suppose that anomalous atmospheric circulation is likely related to the human activity during holidays. It is an interesting phenomenon.
Benjamin S. Grandey, Daniel Rothenberg, Alexander Avramov, Qinjian Jin, Hsiang-He Lee, Xiaohong Liu, Zheng Lu, Samuel Albani, and Chien Wang
Atmos. Chem. Phys., 18, 15783–15810, https://doi.org/10.5194/acp-18-15783-2018, https://doi.org/10.5194/acp-18-15783-2018, 2018
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Anthropogenic emissions of aerosol particles likely cool the climate system. We investigate the uncertainty in the strength of the cooling effect by exploring the representation of aerosols in a global climate model. We conclude that the specific representation of aerosols in global climate models has important implications for climate modelling. Important factors include the representation of aerosol mixing state, size distribution, and optical properties.
Odran Sourdeval, Edward Gryspeerdt, Martina Krämer, Tom Goren, Julien Delanoë, Armin Afchine, Friederike Hemmer, and Johannes Quaas
Atmos. Chem. Phys., 18, 14327–14350, https://doi.org/10.5194/acp-18-14327-2018, https://doi.org/10.5194/acp-18-14327-2018, 2018
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The number concentration of ice crystals (Ni) is a key cloud property that remains very uncertain due to difficulties in determining it using satellites. This lack of global observational constraints limits our ability to constrain this property in models responsible for predicting future climate. This pair of papers fills this gap by showing and analyzing the first rigorously evaluated global climatology of Ni, leading to new information shedding light on the processes that control high clouds.
Alf Kirkevåg, Alf Grini, Dirk Olivié, Øyvind Seland, Kari Alterskjær, Matthias Hummel, Inger H. H. Karset, Anna Lewinschal, Xiaohong Liu, Risto Makkonen, Ingo Bethke, Jan Griesfeller, Michael Schulz, and Trond Iversen
Geosci. Model Dev., 11, 3945–3982, https://doi.org/10.5194/gmd-11-3945-2018, https://doi.org/10.5194/gmd-11-3945-2018, 2018
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A new aerosol treatment is described and tested in a global climate model. With updated emissions, aerosol chemistry, and microphysics compared to its predecessor, black carbon (BC) mass concentrations aloft better fit observations, surface concentrations of BC and sea salt are less biased, and sulfate and mineral dust slightly more, while the results for organics are inconclusive. Man-made aerosols now yield a stronger cooling effect on climate that is strong compared to results from IPCC.
Ben Kravitz, Philip J. Rasch, Hailong Wang, Alan Robock, Corey Gabriel, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Duoying Ji, Andy Jones, Andrew Lenton, John C. Moore, Helene Muri, Ulrike Niemeier, Steven Phipps, Hauke Schmidt, Shingo Watanabe, Shuting Yang, and Jin-Ho Yoon
Atmos. Chem. Phys., 18, 13097–13113, https://doi.org/10.5194/acp-18-13097-2018, https://doi.org/10.5194/acp-18-13097-2018, 2018
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Marine cloud brightening has been proposed as a means of geoengineering/climate intervention, or deliberately altering the climate system to offset anthropogenic climate change. In idealized simulations that highlight contrasts between land and ocean, we find that the globe warms, including the ocean due to transport of heat from land. This study reinforces that no net energy input into the Earth system does not mean that temperature will necessarily remain unchanged.
Jeffrey D. Mirocha, Matthew J. Churchfield, Domingo Muñoz-Esparza, Raj K. Rai, Yan Feng, Branko Kosović, Sue Ellen Haupt, Barbara Brown, Brandon L. Ennis, Caroline Draxl, Javier Sanz Rodrigo, William J. Shaw, Larry K. Berg, Patrick J. Moriarty, Rodman R. Linn, Veerabhadra R. Kotamarthi, Ramesh Balakrishnan, Joel W. Cline, Michael C. Robinson, and Shreyas Ananthan
Wind Energ. Sci., 3, 589–613, https://doi.org/10.5194/wes-3-589-2018, https://doi.org/10.5194/wes-3-589-2018, 2018
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This paper validates the use of idealized large-eddy simulations with periodic lateral boundary conditions to provide boundary-layer flow quantities of interest for wind energy applications. Sensitivities to model formulation, forcing parameter values, and grid configurations were also examined, both to ascertain the robustness of the technique and to characterize inherent uncertainties, as required for the evaluation of more general wind plant flow simulation approaches under development.
Matthew Gibbons, Qilong Min, and Jiwen Fan
Atmos. Chem. Phys., 18, 12161–12184, https://doi.org/10.5194/acp-18-12161-2018, https://doi.org/10.5194/acp-18-12161-2018, 2018
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The effects of dust aerosols on ice formation within a tropical Atlantic thunderstorm system were investigated using a 3-D weather model and compared with observations. Updated ice formation mechanisms directly connect available dust particles with ice particle formation. The resulting clouds were lower and narrower and produced less rain at the surface compared to cleaner conditions, due to ice formation occurring at warmer temperatures. These results agree well with observed changes.
Cenlin He, Mark G. Flanner, Fei Chen, Michael Barlage, Kuo-Nan Liou, Shichang Kang, Jing Ming, and Yun Qian
Atmos. Chem. Phys., 18, 11507–11527, https://doi.org/10.5194/acp-18-11507-2018, https://doi.org/10.5194/acp-18-11507-2018, 2018
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Snow albedo plays a key role in the Earth and climate system. It can be affected by impurities and snow properties. This study implements new parameterizations into a widely used snow model to account for effects of snow shape and black carbon–snow mixing state on snow albedo reduction in the Tibetan Plateau. This study points toward an imperative need for extensive measurements and improved model characterization of snow grain shape and aerosol–snow mixing state in Tibet and elsewhere.
Qianqian Song, Zhibo Zhang, Hongbin Yu, Seiji Kato, Ping Yang, Peter Colarco, Lorraine A. Remer, and Claire L. Ryder
Atmos. Chem. Phys., 18, 11303–11322, https://doi.org/10.5194/acp-18-11303-2018, https://doi.org/10.5194/acp-18-11303-2018, 2018
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Mineral dust is the most abundant atmospheric aerosol component in terms of dry mass. In this study, we integrate recent aircraft measurements of dust microphysical and optical properties with satellite retrievals of aerosol and radiative fluxes to quantify the dust direct radiative effects on the shortwave and longwave radiation at both the top of the atmosphere and the surface in the tropical North Atlantic during summer months.
Hua Song, Zhibo Zhang, Po-Lun Ma, Steven Ghan, and Minghuai Wang
Geosci. Model Dev., 11, 3147–3158, https://doi.org/10.5194/gmd-11-3147-2018, https://doi.org/10.5194/gmd-11-3147-2018, 2018
Junxi Zhang, Yang Gao, Kun Luo, L. Ruby Leung, Yang Zhang, Kai Wang, and Jianren Fan
Atmos. Chem. Phys., 18, 9861–9877, https://doi.org/10.5194/acp-18-9861-2018, https://doi.org/10.5194/acp-18-9861-2018, 2018
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We used a regional model to investigate the impact of atmosphere with high temperature and low wind speed on ozone concentration. When these compound events (heat waves and stagnant weather) occur simultaneously, a striking ozone enhancement is revealed. This type of compound event is projected to increase more dominantly compared to single events in the future over the US, Europe, and China, implying the importance of reducing emissions in order to alleviate the impact from the compound events.
Daniel J. Miller, Zhibo Zhang, Steven Platnick, Andrew S. Ackerman, Frank Werner, Celine Cornet, and Kirk Knobelspiesse
Atmos. Meas. Tech., 11, 3689–3715, https://doi.org/10.5194/amt-11-3689-2018, https://doi.org/10.5194/amt-11-3689-2018, 2018
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Prior satellite comparisons of bispectral and polarimetric cloud droplet size retrievals exhibited systematic biases. However, similar airborne instrument retrievals have been found to be quite similar to one another. This study explains this discrepancy in terms of differing sensitivity to vertical profile, as well as spatial and angular resolution. This is accomplished by using a satellite retrieval simulator – an LES cloud model coupled to radiative transfer and cloud retrieval algorithms.
Christine A. Shields, Jonathan J. Rutz, Lai-Yung Leung, F. Martin Ralph, Michael Wehner, Brian Kawzenuk, Juan M. Lora, Elizabeth McClenny, Tashiana Osborne, Ashley E. Payne, Paul Ullrich, Alexander Gershunov, Naomi Goldenson, Bin Guan, Yun Qian, Alexandre M. Ramos, Chandan Sarangi, Scott Sellars, Irina Gorodetskaya, Karthik Kashinath, Vitaliy Kurlin, Kelly Mahoney, Grzegorz Muszynski, Roger Pierce, Aneesh C. Subramanian, Ricardo Tome, Duane Waliser, Daniel Walton, Gary Wick, Anna Wilson, David Lavers, Prabhat, Allison Collow, Harinarayan Krishnan, Gudrun Magnusdottir, and Phu Nguyen
Geosci. Model Dev., 11, 2455–2474, https://doi.org/10.5194/gmd-11-2455-2018, https://doi.org/10.5194/gmd-11-2455-2018, 2018
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ARTMIP (Atmospheric River Tracking Method Intercomparison Project) is a community effort with the explicit goal of understanding the uncertainties, and the implications of those uncertainties, in atmospheric river science solely due to detection algorithm. ARTMIP strives to quantify these differences and provide guidance on appropriate algorithmic choices for the science question posed. Project goals, experimental design, and preliminary results are provided.
Paul Petersik, Marc Salzmann, Jan Kretzschmar, Ribu Cherian, Daniel Mewes, and Johannes Quaas
Atmos. Chem. Phys., 18, 8589–8599, https://doi.org/10.5194/acp-18-8589-2018, https://doi.org/10.5194/acp-18-8589-2018, 2018
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Our study presents the first estimate of RFari using a global atmospheric model with a parameterization for subgrid-scale variability in RH that is consistent with the assumptions in the model. We find that the revision has a strong influence on the simulated radiative forcing (~ 31 %). In addition, we examine its effects on optical properties of the atmosphere and find an increase in AOD by about 7.8 %.
Kai Zhang, Philip J. Rasch, Mark A. Taylor, Hui Wan, Ruby Leung, Po-Lun Ma, Jean-Christophe Golaz, Jon Wolfe, Wuyin Lin, Balwinder Singh, Susannah Burrows, Jin-Ho Yoon, Hailong Wang, Yun Qian, Qi Tang, Peter Caldwell, and Shaocheng Xie
Geosci. Model Dev., 11, 1971–1988, https://doi.org/10.5194/gmd-11-1971-2018, https://doi.org/10.5194/gmd-11-1971-2018, 2018
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The conservation of total water is an important numerical feature for global Earth system models. Even small conservation problems in the water budget can lead to systematic errors in century-long simulations for sea level rise projection. This study quantifies and reduces various sources of water conservation error in the atmosphere component of the Energy Exascale Earth System Model.
Hewen Niu, Shichang Kang, Hailong Wang, Rudong Zhang, Xixi Lu, Yun Qian, Rukumesh Paudyal, Shijin Wang, Xiaofei Shi, and Xingguo Yan
Atmos. Chem. Phys., 18, 6441–6460, https://doi.org/10.5194/acp-18-6441-2018, https://doi.org/10.5194/acp-18-6441-2018, 2018
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Deposition of light-absorbing carbonaceous aerosol on the surface of glaciers can greatly alter the energy fluxes of glaciers. Two years of continuous observations of carbonaceous aerosols in a glacierized region are analyzed. We mainly studied the light absorption properties of carbonaceous aerosol and have employed a global aerosol–climate model to estimate source attributions of atmospheric black carbon.
Luiz A. T. Machado, Alan J. P. Calheiros, Thiago Biscaro, Scott Giangrande, Maria A. F. Silva Dias, Micael A. Cecchini, Rachel Albrecht, Meinrat O. Andreae, Wagner F. Araujo, Paulo Artaxo, Stephan Borrmann, Ramon Braga, Casey Burleyson, Cristiano W. Eichholz, Jiwen Fan, Zhe Feng, Gilberto F. Fisch, Michael P. Jensen, Scot T. Martin, Ulrich Pöschl, Christopher Pöhlker, Mira L. Pöhlker, Jean-François Ribaud, Daniel Rosenfeld, Jaci M. B. Saraiva, Courtney Schumacher, Ryan Thalman, David Walter, and Manfred Wendisch
Atmos. Chem. Phys., 18, 6461–6482, https://doi.org/10.5194/acp-18-6461-2018, https://doi.org/10.5194/acp-18-6461-2018, 2018
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This overview discuss the main precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin. It presents a review of the knowledge acquired about cloud processes and rainfall formation in Amazonas. In addition, this study provides a characterization of the seasonal variation and rainfall sensitivities to topography, surface cover, and aerosol concentration. Airplane measurements were evaluated to characterize and contrast cloud microphysical properties.
Edward Gryspeerdt, Johannes Quaas, Tom Goren, Daniel Klocke, and Matthias Brueck
Atmos. Chem. Phys., 18, 6157–6169, https://doi.org/10.5194/acp-18-6157-2018, https://doi.org/10.5194/acp-18-6157-2018, 2018
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Cirrus clouds can form by a variety of mechanisms, such as orographic uplift, through convective systems or through large-scale rising motions. In this work, an automated classification of cirrus clouds based on satellite and reanalysis data is presented to separate cirrus by these different formation mechanisms. The classification provides information on the ice origin and cloud-scale updraughts that could not be determined using satellite or reanalysis data alone.
Longtao Wu, Yu Gu, Jonathan H. Jiang, Hui Su, Nanpeng Yu, Chun Zhao, Yun Qian, Bin Zhao, Kuo-Nan Liou, and Yong-Sang Choi
Atmos. Chem. Phys., 18, 5529–5547, https://doi.org/10.5194/acp-18-5529-2018, https://doi.org/10.5194/acp-18-5529-2018, 2018
Heming Bai, Cheng Gong, Minghuai Wang, Zhibo Zhang, and Tristan L'Ecuyer
Atmos. Chem. Phys., 18, 1763–1783, https://doi.org/10.5194/acp-18-1763-2018, https://doi.org/10.5194/acp-18-1763-2018, 2018
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Precipitation susceptibility to aerosol perturbation plays a key role in understanding aerosol–cloud interactions and for constraining aerosol indirect effects. Here, multisensor aerosol and cloud products from A-Train satellites are analyzed to estimate precipitation susceptibility. Compared to precipitation intensity susceptibility, precipitation frequency susceptibility demonstrates relatively robust features across different retrieval products.
Tianyi Fan, Xiaohong Liu, Po-Lun Ma, Qiang Zhang, Zhanqing Li, Yiquan Jiang, Fang Zhang, Chuanfeng Zhao, Xin Yang, Fang Wu, and Yuying Wang
Atmos. Chem. Phys., 18, 1395–1417, https://doi.org/10.5194/acp-18-1395-2018, https://doi.org/10.5194/acp-18-1395-2018, 2018
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We found that 22–28 % of the low AOD bias in eastern China simulated by the Community Atmosphere Model version 5 can be improved by using a new emission inventory. The concentrations of primary aerosols are closely related to the emission, while the seasonal variations of secondary aerosols depend more on atmospheric processes. This study highlights the importance of improving both the emission and atmospheric processes in modeling the atmospheric aerosols and their radiative effects.
Bin Zhao, Kuo-Nan Liou, Yu Gu, Jonathan H. Jiang, Qinbin Li, Rong Fu, Lei Huang, Xiaohong Liu, Xiangjun Shi, Hui Su, and Cenlin He
Atmos. Chem. Phys., 18, 1065–1078, https://doi.org/10.5194/acp-18-1065-2018, https://doi.org/10.5194/acp-18-1065-2018, 2018
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The interactions between aerosols and ice clouds represent one of the largest uncertainties among anthropogenic forcings on climate change. We find that the responses of ice crystal effective radius, a key parameter determining ice clouds' net radiative effect, to aerosol loadings are modulated by water vapor amount and vary from a significant negative correlation in moist conditions (consistent with the “Twomey effect” for liquid clouds) to a strong positive correlation in dry conditions.
Chenglai Wu, Xiaohong Liu, Zhaohui Lin, Stefan R. Rahimi-Esfarjani, and Zheng Lu
Atmos. Chem. Phys., 18, 511–533, https://doi.org/10.5194/acp-18-511-2018, https://doi.org/10.5194/acp-18-511-2018, 2018
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This study utilizes the newly developed variable-resolution Community Earth System Model (VR-CESM) with a refined high resolution (0.125º) to quantify the impacts of absorbing aerosol (BC and dust) deposition on snowpack and hydrologic cycles in the Rocky Mountains. BC and dust in snow significantly reduce the snowpack around the mountains. BC and dust in snow also accelerate the hydrologic cycles in the mountainous regions, with runoff increased in spring but reduced in summer.
Peter A. Bogenschutz, Andrew Gettelman, Cecile Hannay, Vincent E. Larson, Richard B. Neale, Cheryl Craig, and Chih-Chieh Chen
Geosci. Model Dev., 11, 235–255, https://doi.org/10.5194/gmd-11-235-2018, https://doi.org/10.5194/gmd-11-235-2018, 2018
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This paper compares results of developmental versions of a widely used climate model. The simulations only differ in the choice of how to model the sub-grid-scale physics in the atmospheric model. This work is novel because it is the first time that a particular physics option has been tested in a fully coupled climate model. Here, we demonstrate that this physics option has the ability to produce credible coupled climate simulations, with improved metrics in certain fields.
Yawen Liu, Kai Zhang, Yun Qian, Yuhang Wang, Yufei Zou, Yongjia Song, Hui Wan, Xiaohong Liu, and Xiu-Qun Yang
Atmos. Chem. Phys., 18, 31–47, https://doi.org/10.5194/acp-18-31-2018, https://doi.org/10.5194/acp-18-31-2018, 2018
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Fire aerosols have large impact on weather and climate through their effect on clouds and radiation, but it is difficult to quantify. Here we investigated the short-term effective radiative forcing of fire aerosols using the nudged hindcast ensemble simulations from global aerosol-climate model. Results show large effects of fire aerosols on both liquid and ice cloud and large ensemble spread of regional mean shortwave cloud radiative forcing over southern Mexico and the central US.
Scott E. Giangrande, Zhe Feng, Michael P. Jensen, Jennifer M. Comstock, Karen L. Johnson, Tami Toto, Meng Wang, Casey Burleyson, Nitin Bharadwaj, Fan Mei, Luiz A. T. Machado, Antonio O. Manzi, Shaocheng Xie, Shuaiqi Tang, Maria Assuncao F. Silva Dias, Rodrigo A. F de Souza, Courtney Schumacher, and Scot T. Martin
Atmos. Chem. Phys., 17, 14519–14541, https://doi.org/10.5194/acp-17-14519-2017, https://doi.org/10.5194/acp-17-14519-2017, 2017
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The Amazon forest is the largest tropical rain forest on the planet, featuring
prolific and diverse cloud conditions. The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) experiment was motivated by demands to gain a better understanding of aerosol and cloud interactions on climate and the global circulation. The routine DOE ARM observations from this 2-year campaign are summarized to help quantify controls on clouds and precipitation over this undersampled region.
Yoko Tsushima, Florent Brient, Stephen A. Klein, Dimitra Konsta, Christine C. Nam, Xin Qu, Keith D. Williams, Steven C. Sherwood, Kentaroh Suzuki, and Mark D. Zelinka
Geosci. Model Dev., 10, 4285–4305, https://doi.org/10.5194/gmd-10-4285-2017, https://doi.org/10.5194/gmd-10-4285-2017, 2017
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Cloud feedback is the largest uncertainty associated with estimates of climate sensitivity. Diagnostics have been developed to evaluate cloud processes in climate models. For this understanding to be reflected in better estimates of cloud feedbacks, it is vital to continue to develop such tools and to exploit them fully during the model development process. Code repositories have been created to store and document the programs which will allow climate modellers to compute these diagnostics.
Jeremy Fyke, Jan T. M. Lenaerts, and Hailong Wang
The Cryosphere, 11, 2595–2609, https://doi.org/10.5194/tc-11-2595-2017, https://doi.org/10.5194/tc-11-2595-2017, 2017
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In this CESM modeling study, we uncover regional relationships in snowfall across Antarctica that are corroborated by regional modeling and ice core records. These relationships are driven by variability in large-scale atmospheric moisture transport and dampen overall Antarctic snowfall variability, with implications for Antarctic-sourced sea level variability and detection of an emergent anthropogenic signal in Antarctic mass trends.
Maria Sand, Bjørn H. Samset, Yves Balkanski, Susanne Bauer, Nicolas Bellouin, Terje K. Berntsen, Huisheng Bian, Mian Chin, Thomas Diehl, Richard Easter, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Jean-François Lamarque, Guangxing Lin, Xiaohong Liu, Gan Luo, Gunnar Myhre, Twan van Noije, Joyce E. Penner, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Fangqun Yu, Kai Zhang, and Hua Zhang
Atmos. Chem. Phys., 17, 12197–12218, https://doi.org/10.5194/acp-17-12197-2017, https://doi.org/10.5194/acp-17-12197-2017, 2017
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The role of aerosols in the changing polar climate is not well understood and the aerosols are poorly constrained in the models. In this study we have compared output from 16 different aerosol models with available observations at both poles. We show that the model median is representative of the observations, but the model spread is large. The Arctic direct aerosol radiative effect over the industrial area is positive during spring due to black carbon and negative during summer due to sulfate.
Bethan White, Edward Gryspeerdt, Philip Stier, Hugh Morrison, Gregory Thompson, and Zak Kipling
Atmos. Chem. Phys., 17, 12145–12175, https://doi.org/10.5194/acp-17-12145-2017, https://doi.org/10.5194/acp-17-12145-2017, 2017
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Aerosols influence cloud and precipitation by modifying cloud droplet number concentrations (CDNCs). We simulate three different types of convective cloud using two different cloud microphysics parameterisations. The simulated cloud and precipitation depends much more strongly on the choice of microphysics scheme than on CDNC. The uncertainty differs between types of convection. Our results highlight a large uncertainty in cloud and precipitation responses to aerosol in current models.
Louis Marelle, Jean-Christophe Raut, Kathy S. Law, Larry K. Berg, Jerome D. Fast, Richard C. Easter, Manish Shrivastava, and Jennie L. Thomas
Geosci. Model Dev., 10, 3661–3677, https://doi.org/10.5194/gmd-10-3661-2017, https://doi.org/10.5194/gmd-10-3661-2017, 2017
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We develop the WRF-Chem 3.5.1 model to improve simulations of aerosols and ozone in the Arctic. Both species are important air pollutants and climate forcers, but models often struggle to reproduce observations in the Arctic. Our developments concern pollutant emissions, mixing, chemistry, and removal, including processes related to snow and sea ice. The effect of these changes are quantitatively validated against observations, showing significant improvements compared to the original model.
Jean-Christophe Raut, Louis Marelle, Jerome D. Fast, Jennie L. Thomas, Bernadett Weinzierl, Katharine S. Law, Larry K. Berg, Anke Roiger, Richard C. Easter, Katharina Heimerl, Tatsuo Onishi, Julien Delanoë, and Hans Schlager
Atmos. Chem. Phys., 17, 10969–10995, https://doi.org/10.5194/acp-17-10969-2017, https://doi.org/10.5194/acp-17-10969-2017, 2017
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We study the cross-polar transport of plumes from Siberian fires to the Arctic in summer, both in terms of transport pathways and efficiency of deposition processes. Those plumes containing soot may originate from anthropogenic and biomass burning sources in mid-latitude regions and may impact the Arctic climate by depositing on snow and ice surfaces. We evaluate the role of the respective source contributions, investigate the transport of plumes and treat pathway-dependent removal of particles.
Gavin A. Schmidt, David Bader, Leo J. Donner, Gregory S. Elsaesser, Jean-Christophe Golaz, Cecile Hannay, Andrea Molod, Richard B. Neale, and Suranjana Saha
Geosci. Model Dev., 10, 3207–3223, https://doi.org/10.5194/gmd-10-3207-2017, https://doi.org/10.5194/gmd-10-3207-2017, 2017
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The development of coupled ocean atmosphere climate models is a complex process that inevitably includes multiple calibration steps (sometimes called
tuning). Tuning uses degrees of freedom allowed by uncertainties in model approximations to modify parameters to make the simulation better align with some selected observed target(s). We describe how these tuning targets, parameters, and philosophy vary across six US modeling centers in order to increase the transparency of the practice.
Randal D. Koster, Alan K. Betts, Paul A. Dirmeyer, Marc Bierkens, Katrina E. Bennett, Stephen J. Déry, Jason P. Evans, Rong Fu, Felipe Hernandez, L. Ruby Leung, Xu Liang, Muhammad Masood, Hubert Savenije, Guiling Wang, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 3777–3798, https://doi.org/10.5194/hess-21-3777-2017, https://doi.org/10.5194/hess-21-3777-2017, 2017
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Large-scale hydrological variability can affect society in profound ways; floods and droughts, for example, often cause major damage and hardship. A recent gathering of hydrologists at a symposium to honor the career of Professor Eric Wood motivates the present survey of recent research on this variability. The surveyed literature and the illustrative examples provided in the paper show that research into hydrological variability continues to be strong, vibrant, and multifaceted.
Yang Yang, Hailong Wang, Steven J. Smith, Richard Easter, Po-Lun Ma, Yun Qian, Hongbin Yu, Can Li, and Philip J. Rasch
Atmos. Chem. Phys., 17, 8903–8922, https://doi.org/10.5194/acp-17-8903-2017, https://doi.org/10.5194/acp-17-8903-2017, 2017
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Sulfate has significant impacts on air quality and climate. Local sulfate pollution could result from remote influences, making domestic mitigation efforts inefficient. Using CESM with a sulfur source-tagging technique, we found that, over regions with relatively low emissions, sulfate concentrations are primarily attributed to non-local sources and sulfate indirect radiative forcing over the Southern Hemisphere is more sensitive to emission perturbation than the polluted Northern Hemisphere.
Joseph Ching, Jerome Fast, Matthew West, and Nicole Riemer
Atmos. Chem. Phys., 17, 7445–7458, https://doi.org/10.5194/acp-17-7445-2017, https://doi.org/10.5194/acp-17-7445-2017, 2017
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The composition of individual aerosols affects their cloud condensation nuclei (CCN) properties, but is challenging to represent in models. This study quantifies the error in CCN calculations when per-particle information is neglected by using a metric for the composition diversity within a population. With more particle-level measurements from field campaigns, the approach is useful for quantifying uncertainties in composition-dependent quantities regarding aerosol–cloud–climate interactions.
Sudhakar Dipu, Johannes Quaas, Ralf Wolke, Jens Stoll, Andreas Mühlbauer, Odran Sourdeval, Marc Salzmann, Bernd Heinold, and Ina Tegen
Geosci. Model Dev., 10, 2231–2246, https://doi.org/10.5194/gmd-10-2231-2017, https://doi.org/10.5194/gmd-10-2231-2017, 2017
Shi Zhong, Yun Qian, Chun Zhao, Ruby Leung, Hailong Wang, Ben Yang, Jiwen Fan, Huiping Yan, Xiu-Qun Yang, and Dongqing Liu
Atmos. Chem. Phys., 17, 5439–5457, https://doi.org/10.5194/acp-17-5439-2017, https://doi.org/10.5194/acp-17-5439-2017, 2017
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An online climate–chemistry coupled model (WRF-Chem) is integrated for 5 years at cloud-permitting scale to quantify the impacts of urbanization-induced changes in land cover and pollutants emission on regional climate in the Yangtze River Delta region in eastern China. Urbanization over this region increases the frequency of extreme precipitation and heat wave in summer. The results could help China government in making policies in mitigating the environmental impact of urbanization.
Chenglai Wu, Xiaohong Liu, Minghui Diao, Kai Zhang, Andrew Gettelman, Zheng Lu, Joyce E. Penner, and Zhaohui Lin
Atmos. Chem. Phys., 17, 4731–4749, https://doi.org/10.5194/acp-17-4731-2017, https://doi.org/10.5194/acp-17-4731-2017, 2017
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This study utilizes a novel approach to directly compare the CAM5-simulated cloud macro- and microphysics with the collocated HIPPO observations for the period of 2009 to 2011. The model cannot capture the large spatial variabilities of observed RH, which is responsible for much of the model missing low-level warm clouds. A large portion of the RH bias results from the discrepancy in water vapor. The model underestimates the observed number concentration and ice water content.
Andrew Gettelman, Chih-Chieh Chen, Mark Z. Jacobson, Mary A. Cameron, Donald J. Wuebbles, and Arezoo Khodayari
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-218, https://doi.org/10.5194/acp-2017-218, 2017
Revised manuscript not accepted
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Aviation emissions create several impacts on climate. Condensation trails (contrails) are aviation produced cirrus clouds. Aircraft also emit aerosols, including soot (black carbon) and sulfate. Analyses of the climate effects of 2050 aviation emissions have been conducted with two coupled Chemistry Climate Models (CCMs) including experiments with coupled ocean models.
Yang Yang, Hailong Wang, Steven J. Smith, Po-Lun Ma, and Philip J. Rasch
Atmos. Chem. Phys., 17, 4319–4336, https://doi.org/10.5194/acp-17-4319-2017, https://doi.org/10.5194/acp-17-4319-2017, 2017
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The source attributions of black carbon (BC) in China are quantified using the Community Earth System Model by source tagging. BC impacts neighboring regions greatly. Transport is important in increasing BC during regional polluted days. Emissions outside China contribute 35 % of BC direct radiative forcing in China. Efficiency analysis shows that reduction in BC emissions over eastern China could have a greater benefit for regional air quality in China, especially in the winter haze season.
Xiangyu Luo, Hong-Yi Li, L. Ruby Leung, Teklu K. Tesfa, Augusto Getirana, Fabrice Papa, and Laura L. Hess
Geosci. Model Dev., 10, 1233–1259, https://doi.org/10.5194/gmd-10-1233-2017, https://doi.org/10.5194/gmd-10-1233-2017, 2017
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This study shows that alleviating vegetation-caused biases in DEM data, refining channel cross-sectional geometry and Manning roughness coefficients, as well as accounting for backwater effects can effectively improve the modeling of streamflow, river stages and flood extent in the Amazon Basin. The obtained understanding could be helpful to hydrological modeling in basins with evident inundation, which has important implications for improving land–atmosphere interactions in Earth system models.
Piyushkumar N. Patel, Johannes Quaas, and Raj Kumar
Atmos. Chem. Phys., 17, 3687–3698, https://doi.org/10.5194/acp-17-3687-2017, https://doi.org/10.5194/acp-17-3687-2017, 2017
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Radiative forcing by aerosol–cloud interactions (RFaci) remains highly uncertain and difficult to quantify on the basis of current knowledge. The present study reassesses the estimated RFaci by using a new statistical fitting approach, which improves the quantification of RFaci with less uncertainty. The present work helps to improve the parameterisation of RFaci in the present climate model.
Teklu K. Tesfa and Lai-Yung Ruby Leung
Geosci. Model Dev., 10, 873–888, https://doi.org/10.5194/gmd-10-873-2017, https://doi.org/10.5194/gmd-10-873-2017, 2017
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Motivated by the significant topographic influence on land surface processes, this study explored two methods to discretize watersheds into two types of subgrid structures to capture spatial heterogeneity for land surface models. Adopting geomorphologic concepts in watershed discretization yields improved capability in capturing subgrid topographic heterogeneity, which also allowed climatic and land cover variability to be better represented with a nominal increase in computational requirements.
Gunnar Myhre, Wenche Aas, Ribu Cherian, William Collins, Greg Faluvegi, Mark Flanner, Piers Forster, Øivind Hodnebrog, Zbigniew Klimont, Marianne T. Lund, Johannes Mülmenstädt, Cathrine Lund Myhre, Dirk Olivié, Michael Prather, Johannes Quaas, Bjørn H. Samset, Jordan L. Schnell, Michael Schulz, Drew Shindell, Ragnhild B. Skeie, Toshihiko Takemura, and Svetlana Tsyro
Atmos. Chem. Phys., 17, 2709–2720, https://doi.org/10.5194/acp-17-2709-2017, https://doi.org/10.5194/acp-17-2709-2017, 2017
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Over the past decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990–2015, as simulated by seven global atmospheric composition models. The global mean radiative forcing is more strongly positive than reported in IPCC AR5.
Ben Kravitz, Douglas G. MacMartin, Philip J. Rasch, and Hailong Wang
Atmos. Chem. Phys., 17, 2525–2541, https://doi.org/10.5194/acp-17-2525-2017, https://doi.org/10.5194/acp-17-2525-2017, 2017
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We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state.
Hui Wan, Kai Zhang, Philip J. Rasch, Balwinder Singh, Xingyuan Chen, and Jim Edwards
Geosci. Model Dev., 10, 537–552, https://doi.org/10.5194/gmd-10-537-2017, https://doi.org/10.5194/gmd-10-537-2017, 2017
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Solution reproductibility testing is an important task for assuring the software quality of a climate model. A new method is developed using the concept of numerical convergence with respect to temporal resolution. The method is objective, easy to implement, and computationally efficient. This paper describes the new test and demonstrates its utility in the Community Atmosphere Model version 5 (CAM5).
Mark J. Webb, Timothy Andrews, Alejandro Bodas-Salcedo, Sandrine Bony, Christopher S. Bretherton, Robin Chadwick, Hélène Chepfer, Hervé Douville, Peter Good, Jennifer E. Kay, Stephen A. Klein, Roger Marchand, Brian Medeiros, A. Pier Siebesma, Christopher B. Skinner, Bjorn Stevens, George Tselioudis, Yoko Tsushima, and Masahiro Watanabe
Geosci. Model Dev., 10, 359–384, https://doi.org/10.5194/gmd-10-359-2017, https://doi.org/10.5194/gmd-10-359-2017, 2017
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The Cloud Feedback Model Intercomparison Project (CFMIP) aims to improve understanding of cloud-climate feedback mechanisms and evaluation of cloud processes and cloud feedbacks in climate models. CFMIP also aims to improve understanding of circulation, regional-scale precipitation and non-linear changes. CFMIP is contributing to the 6th phase of the Coupled Model Intercomparison Project (CMIP6) by coordinating a hierarchy of targeted experiments with cloud-related model outputs.
Jiwen Fan, L. Ruby Leung, Daniel Rosenfeld, and Paul J. DeMott
Atmos. Chem. Phys., 17, 1017–1035, https://doi.org/10.5194/acp-17-1017-2017, https://doi.org/10.5194/acp-17-1017-2017, 2017
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How orographic mixed-phase clouds respond to changes in cloud condensation nuclei (CCN) and ice nucleating particles (INPs) is highly uncertain. We conducted this study to improve understanding of these processes. We found a new mechanism through which CCN can invigorate orographic mixed-phase clouds and drastically intensify snow precipitation when CCN concentrations are high. Our findings have very important implications for orographic precipitation in polluted regions.
Frank Werner, Galina Wind, Zhibo Zhang, Steven Platnick, Larry Di Girolamo, Guangyu Zhao, Nandana Amarasinghe, and Kerry Meyer
Atmos. Meas. Tech., 9, 5869–5894, https://doi.org/10.5194/amt-9-5869-2016, https://doi.org/10.5194/amt-9-5869-2016, 2016
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A research–level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. This yields reliable estimates of important cloud variables at a horizontal resolution of 30 m. Comparisons of the ASTER retrieval results with the operational cloud products from the Moderate Resolution Imaging Spectroradiometer (MODIS) show a high agreement for 48 example cloud fields.
Yiquan Jiang, Zheng Lu, Xiaohong Liu, Yun Qian, Kai Zhang, Yuhang Wang, and Xiu-Qun Yang
Atmos. Chem. Phys., 16, 14805–14824, https://doi.org/10.5194/acp-16-14805-2016, https://doi.org/10.5194/acp-16-14805-2016, 2016
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Aerosols from open fires could significantly perturb the global radiation balance and induce climate change. In this study, the CAM5 global climate model is used to investigate the spatial and seasonal characteristics of radiative effects due to fire aerosol–radiation interactions, fire aerosol-cloud interactions and fire aerosol-surface albedo interactions, including radiative effects from all fire aerosols, fire black carbon and fire particulate organic matter.
Reindert J. Haarsma, Malcolm J. Roberts, Pier Luigi Vidale, Catherine A. Senior, Alessio Bellucci, Qing Bao, Ping Chang, Susanna Corti, Neven S. Fučkar, Virginie Guemas, Jost von Hardenberg, Wilco Hazeleger, Chihiro Kodama, Torben Koenigk, L. Ruby Leung, Jian Lu, Jing-Jia Luo, Jiafu Mao, Matthew S. Mizielinski, Ryo Mizuta, Paulo Nobre, Masaki Satoh, Enrico Scoccimarro, Tido Semmler, Justin Small, and Jin-Song von Storch
Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, https://doi.org/10.5194/gmd-9-4185-2016, 2016
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Recent progress in computing power has enabled climate models to simulate more processes in detail and on a smaller scale. Here we present a common protocol for these high-resolution runs that will foster the analysis and understanding of the impact of model resolution on the simulated climate. These runs will also serve as a more reliable source for assessing climate risks that are associated with small-scale weather phenomena such as tropical cyclones.
Shuaiqi Tang, Shaocheng Xie, Yunyan Zhang, Minghua Zhang, Courtney Schumacher, Hannah Upton, Michael P. Jensen, Karen L. Johnson, Meng Wang, Maike Ahlgrimm, Zhe Feng, Patrick Minnis, and Mandana Thieman
Atmos. Chem. Phys., 16, 14249–14264, https://doi.org/10.5194/acp-16-14249-2016, https://doi.org/10.5194/acp-16-14249-2016, 2016
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Data observed during the Green Ocean Amazon (GoAmazon2014/5) experiment are used to derive the large-scale fields in this study. The morning propagating convective systems are active during the wet season but rare during the dry season. The afternoon convections are active in both seasons, with heating and moistening in the lower level corresponding to the vertical convergence of eddy fluxes. Case study shows distinguish large-scale environments for three types of convective systems in Amazonia.
Nicolas Bellouin, Laura Baker, Øivind Hodnebrog, Dirk Olivié, Ribu Cherian, Claire Macintosh, Bjørn Samset, Anna Esteve, Borgar Aamaas, Johannes Quaas, and Gunnar Myhre
Atmos. Chem. Phys., 16, 13885–13910, https://doi.org/10.5194/acp-16-13885-2016, https://doi.org/10.5194/acp-16-13885-2016, 2016
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This study uses global climate models to quantify how strongly man-made emissions of selected pollutants modify the energy budget of the Earth. The pollutants studied interact directly and indirectly with sunlight and terrestrial radiation and remain a relatively short time in the atmosphere, leading to regional and seasonal variations in their impacts. This new data set is useful to compare the potential climate impacts of different pollutants in support of policies to reduce climate change.
Tianjun Zhou, Andrew G. Turner, James L. Kinter, Bin Wang, Yun Qian, Xiaolong Chen, Bo Wu, Bin Wang, Bo Liu, Liwei Zou, and Bian He
Geosci. Model Dev., 9, 3589–3604, https://doi.org/10.5194/gmd-9-3589-2016, https://doi.org/10.5194/gmd-9-3589-2016, 2016
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This paper tells why to launch the Global Monsoons Model Inter-comparison Project (GMMIP) and how to achieve its scientific goals on monsoon variability. It addresses the scientific questions to be answered, describes three tiered experiments comprehensively and proposes a basic analysis framework to guide future research. It will help the monsoon research communities to understand the objectives of the GMMIP and the modelling groups involved in the GMMIP conduct the experiments successfully.
Cheng Zhou, Joyce E. Penner, Guangxing Lin, Xiaohong Liu, and Minghuai Wang
Atmos. Chem. Phys., 16, 12411–12424, https://doi.org/10.5194/acp-16-12411-2016, https://doi.org/10.5194/acp-16-12411-2016, 2016
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We examined the different ice nucleation parameterization factors that affect the simulated ice number concentrations in cirrus clouds in the upper troposphere using the CAM5 model. We examined the effect from three different updraft velocities (from low to high), two different water vapour accommodation coefficients (α = 0.1 or 1), the effect of including vapour deposition onto pre-existing ice particles during ice nucleation, and the effect of including SOA as heterogeneous ice nuclei.
B. Quennehen, J.-C. Raut, K. S. Law, N. Daskalakis, G. Ancellet, C. Clerbaux, S.-W. Kim, M. T. Lund, G. Myhre, D. J. L. Olivié, S. Safieddine, R. B. Skeie, J. L. Thomas, S. Tsyro, A. Bazureau, N. Bellouin, M. Hu, M. Kanakidou, Z. Klimont, K. Kupiainen, S. Myriokefalitakis, J. Quaas, S. T. Rumbold, M. Schulz, R. Cherian, A. Shimizu, J. Wang, S.-C. Yoon, and T. Zhu
Atmos. Chem. Phys., 16, 10765–10792, https://doi.org/10.5194/acp-16-10765-2016, https://doi.org/10.5194/acp-16-10765-2016, 2016
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This paper evaluates the ability of six global models and one regional model in reproducing short-lived pollutants (defined here as ozone and its precursors, aerosols and black carbon) concentrations over Asia using satellite, ground-based and airborne observations.
Key findings are that models homogeneously reproduce the trace gas observations although nitrous oxides are underestimated, whereas the aerosol distributions are heterogeneously reproduced, implicating important uncertainties.
Dan Chen, Zhiquan Liu, Jerome Fast, and Junmei Ban
Atmos. Chem. Phys., 16, 10707–10724, https://doi.org/10.5194/acp-16-10707-2016, https://doi.org/10.5194/acp-16-10707-2016, 2016
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Extreme haze events occurred frequently over China recently, and adequately predicting peak PM2.5 concentrations is still challenging. In this study, the sulfate–nitrate–ammonium relevant heterogeneous reactions were parameterized for the first time in the WRF-Chem model. We evaluated the performance of WRF-Chem and used the model to investigate the sensitivity of heterogeneous reactions on simulated peak sulfate, nitrate, and ammonium concentrations in the vicinity of Beijing during October 2014.
Ivan Ortega, Sean Coburn, Larry K. Berg, Kathy Lantz, Joseph Michalsky, Richard A. Ferrare, Johnathan W. Hair, Chris A. Hostetler, and Rainer Volkamer
Atmos. Meas. Tech., 9, 3893–3910, https://doi.org/10.5194/amt-9-3893-2016, https://doi.org/10.5194/amt-9-3893-2016, 2016
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We present an inherently calibrated retrieval to measure aerosol optical depth (AOD) and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity by the University of Colorado two-dimensional (2-D) MAX-DOAS. The retrievals are maximally sensitive at low AOD and do not require absolute radiance calibration. We compare results with data from independent sensors.
Chih-Chieh Chen and Andrew Gettelman
Atmos. Chem. Phys., 16, 7317–7333, https://doi.org/10.5194/acp-16-7317-2016, https://doi.org/10.5194/acp-16-7317-2016, 2016
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The impact of aviation emissions through 2050 is simulated by a comprehensive global climate model. Four different future emission scenarios of the same flight tracks are considered. The results reveal that the global radiative forcing of contrail cirrus is positive and can increase by a factor of 7 in 2050 from the 2006 level. The aviation aerosols can produce negative forcing, mainly over the oceans, and increase by a factor of 4 in 2050 from the 2006 level.
Micael A. Cecchini, Luiz A. T. Machado, Jennifer M. Comstock, Fan Mei, Jian Wang, Jiwen Fan, Jason M. Tomlinson, Beat Schmid, Rachel Albrecht, Scot T. Martin, and Paulo Artaxo
Atmos. Chem. Phys., 16, 7029–7041, https://doi.org/10.5194/acp-16-7029-2016, https://doi.org/10.5194/acp-16-7029-2016, 2016
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This work focuses on the analysis of anthropogenic impacts on Amazonian clouds. The experiment was conducted around Manaus (Brazil), which is a city with 2 million inhabitants and is surrounded by the Amazon forest in every direction. The clouds that form over the pristine atmosphere of the forest are understood as the background clouds and the ones that form over the city pollution are the anthropogenically impacted ones. The paper analyses microphysical characteristics of both types of clouds.
Chun Zhao, Maoyi Huang, Jerome D. Fast, Larry K. Berg, Yun Qian, Alex Guenther, Dasa Gu, Manish Shrivastava, Ying Liu, Stacy Walters, Gabriele Pfister, Jiming Jin, John E. Shilling, and Carsten Warneke
Geosci. Model Dev., 9, 1959–1976, https://doi.org/10.5194/gmd-9-1959-2016, https://doi.org/10.5194/gmd-9-1959-2016, 2016
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In this study, the latest version of MEGAN is coupled within CLM4 in WRF-Chem. In this implementation, MEGAN shares a consistent vegetation map with CLM4. This improved modeling framework is used to investigate the impact of two land surface schemes on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models.
Ben Kravitz, Douglas G. MacMartin, Hailong Wang, and Philip J. Rasch
Earth Syst. Dynam., 7, 469–497, https://doi.org/10.5194/esd-7-469-2016, https://doi.org/10.5194/esd-7-469-2016, 2016
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Most simulations of solar geoengineering prescribe a particular strategy and evaluate its modeled effects. Here we first choose example climate objectives and then design a strategy to meet those objectives in climate models. We show that certain objectives can be met simultaneously even in the presence of uncertainty, and the strategy for meeting those objectives can be ported to other models. This is part of a broader illustration of how uncertainties in solar geoengineering can be managed.
Matthew Gibbons, Qilong Min, and Jiwen Fan
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-368, https://doi.org/10.5194/acp-2016-368, 2016
Revised manuscript not accepted
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Observations suggest cloud systems evolve differently under dusty conditions compared to other aerosols. We have used numerical modeling to study one such case. Dust increases the formation of small sized ice in the mid-troposphere. This enhanced convective intensity, shifted precipitation top height to higher altitudes, and glaciated clouds at lower altitudes. Consistent with observations, average cloud height was lowered due to a greater number of heavy particles forming near the cloud tops.
Bin Zhao, Kuo-Nan Liou, Yu Gu, Cenlin He, Wee-Liang Lee, Xing Chang, Qinbin Li, Shuxiao Wang, Hsien-Liang R. Tseng, Lai-Yung R. Leung, and Jiming Hao
Atmos. Chem. Phys., 16, 5841–5852, https://doi.org/10.5194/acp-16-5841-2016, https://doi.org/10.5194/acp-16-5841-2016, 2016
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We examine the impact of buildings on surface solar fluxes in Beijing by accounting for their 3-D structures. We find that inclusion of buildings changes surface solar fluxes by within ±1 W m−2, ±1–10 W m−2, and up to ±100 W m−2 at grid resolutions of 4 km, 800 m, and 90 m, respectively. We can resolve pairs of positive-negative flux deviations on different sides of buildings at ≤ 800 m resolutions. We should treat building-effect on solar fluxes differently in models with different resolutions.
Zhiyuan Hu, Chun Zhao, Jianping Huang, L. Ruby Leung, Yun Qian, Hongbin Yu, Lei Huang, and Olga V. Kalashnikova
Geosci. Model Dev., 9, 1725–1746, https://doi.org/10.5194/gmd-9-1725-2016, https://doi.org/10.5194/gmd-9-1725-2016, 2016
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This study conducts the simulation of WRF-Chem with the quasi-global configuration for 2010–2014, and evaluates the simulation with multiple observation datasets for the first time. This study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA to further understand the impact of transported pollutants on the regional air quality and climate.
S. T. Martin, P. Artaxo, L. A. T. Machado, A. O. Manzi, R. A. F. Souza, C. Schumacher, J. Wang, M. O. Andreae, H. M. J. Barbosa, J. Fan, G. Fisch, A. H. Goldstein, A. Guenther, J. L. Jimenez, U. Pöschl, M. A. Silva Dias, J. N. Smith, and M. Wendisch
Atmos. Chem. Phys., 16, 4785–4797, https://doi.org/10.5194/acp-16-4785-2016, https://doi.org/10.5194/acp-16-4785-2016, 2016
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The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment took place in central Amazonia throughout 2014 and 2015. The experiment focused on the complex links among vegetation, atmospheric chemistry, and aerosol production on the one hand and their connections to aerosols, clouds, and precipitation on the other, especially when altered by urban pollution. This article serves as an introduction to the special issue of publications presenting findings of this experiment.
Peter A. Bosler, Erika L. Roesler, Mark A. Taylor, and Miranda R. Mundt
Geosci. Model Dev., 9, 1383–1398, https://doi.org/10.5194/gmd-9-1383-2016, https://doi.org/10.5194/gmd-9-1383-2016, 2016
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This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets.
The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem.
A new algorithm, "Stride Search," is introduced which is capable of searching for storms at all latitudes including the poles and has better performance than the commonly used grid point search.
N. I. Kristiansen, A. Stohl, D. J. L. Olivié, B. Croft, O. A. Søvde, H. Klein, T. Christoudias, D. Kunkel, S. J. Leadbetter, Y. H. Lee, K. Zhang, K. Tsigaridis, T. Bergman, N. Evangeliou, H. Wang, P.-L. Ma, R. C. Easter, P. J. Rasch, X. Liu, G. Pitari, G. Di Genova, S. Y. Zhao, Y. Balkanski, S. E. Bauer, G. S. Faluvegi, H. Kokkola, R. V. Martin, J. R. Pierce, M. Schulz, D. Shindell, H. Tost, and H. Zhang
Atmos. Chem. Phys., 16, 3525–3561, https://doi.org/10.5194/acp-16-3525-2016, https://doi.org/10.5194/acp-16-3525-2016, 2016
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Processes affecting aerosol removal from the atmosphere are not fully understood. In this study we investigate to what extent atmospheric transport models can reproduce observed loss of aerosols. We compare measurements of radioactive isotopes, that attached to ambient sulfate aerosols during the 2011 Fukushima nuclear accident, to 19 models using identical emissions. Results indicate aerosol removal that is too fast in most models, and apply to aerosols that have undergone long-range transport.
Shipeng Zhang, Minghuai Wang, Steven J. Ghan, Aijun Ding, Hailong Wang, Kai Zhang, David Neubauer, Ulrike Lohmann, Sylvaine Ferrachat, Toshihiko Takeamura, Andrew Gettelman, Hugh Morrison, Yunha Lee, Drew T. Shindell, Daniel G. Partridge, Philip Stier, Zak Kipling, and Congbin Fu
Atmos. Chem. Phys., 16, 2765–2783, https://doi.org/10.5194/acp-16-2765-2016, https://doi.org/10.5194/acp-16-2765-2016, 2016
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The variation of aerosol indirect effects (AIE) in several climate models is investigated across different dynamical regimes. Regimes with strong large-scale ascent are shown to be as important as stratocumulus regimes in studying AIE. AIE over regions with high monthly large-scale surface precipitation rate contributes the most to the total aerosol indirect forcing. These results point to the need to reduce the uncertainty in AIE in different dynamical regimes.
Zhibo Zhang, Kerry Meyer, Hongbin Yu, Steven Platnick, Peter Colarco, Zhaoyan Liu, and Lazaros Oreopoulos
Atmos. Chem. Phys., 16, 2877–2900, https://doi.org/10.5194/acp-16-2877-2016, https://doi.org/10.5194/acp-16-2877-2016, 2016
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The frequency of occurrence and shortwave direct radiative effects (DRE) of above-cloud aerosols (ACAs) over global oceans are investigated using 8 years of collocated CALIOP and MODIS observations. We estimated that ACAs have a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m−2 (range of −0.03 to 0.06 W m−2) at TOA. The DREs at surface and within atmosphere are −0.15 W m−2 (range of −0.09 to −0.21 W m−2), and 0.17 W m−2 (range of 0.11 to 0.24 W m−2), respectively.
Zak Kipling, Philip Stier, Colin E. Johnson, Graham W. Mann, Nicolas Bellouin, Susanne E. Bauer, Tommi Bergman, Mian Chin, Thomas Diehl, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Harri Kokkola, Xiaohong Liu, Gan Luo, Twan van Noije, Kirsty J. Pringle, Knut von Salzen, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Toshihiko Takemura, Kostas Tsigaridis, and Kai Zhang
Atmos. Chem. Phys., 16, 2221–2241, https://doi.org/10.5194/acp-16-2221-2016, https://doi.org/10.5194/acp-16-2221-2016, 2016
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The vertical distribution of atmospheric aerosol is an important factor in its effects on climate. In this study we use a sophisticated model of the many interacting processes affecting aerosol in the atmosphere to show that the vertical distribution is typically dominated by only a few of these processes. Constraining these physical processes may help to reduce the large differences between models. However, the important processes are not always the same for different types of aerosol.
Kai Zhang, Chun Zhao, Hui Wan, Yun Qian, Richard C. Easter, Steven J. Ghan, Koichi Sakaguchi, and Xiaohong Liu
Geosci. Model Dev., 9, 607–632, https://doi.org/10.5194/gmd-9-607-2016, https://doi.org/10.5194/gmd-9-607-2016, 2016
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A sub-grid treatment based on Weibull distribution is introduced to CAM5 to take into account the impact of unresolved variability of surface wind speed on sea salt and dust emissions. Simulations show that sub-grid wind variability has relatively small impacts on the global mean sea salt emissions, but considerable influence on dust emissions. Dry convective eddies and mesoscale flows associated with complex topography are the major causes of dust emission enhancement.
X. Liu, P.-L. Ma, H. Wang, S. Tilmes, B. Singh, R. C. Easter, S. J. Ghan, and P. J. Rasch
Geosci. Model Dev., 9, 505–522, https://doi.org/10.5194/gmd-9-505-2016, https://doi.org/10.5194/gmd-9-505-2016, 2016
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In this study, we describe and evaluate a new four-mode version of the Modal Aerosol Module (MAM4) in the Community Atmosphere Model version 5 (CAM5). Compared to the current three-mode version of MAM in CAM5, MAM4 significantly improves the simulation of seasonal variation of BC concentrations in the polar regions, by increasing the BC concentrations in all seasons and particularly in cold seasons.
P. H. Lauritzen, J. T. Bacmeister, P. F. Callaghan, and M. A. Taylor
Geosci. Model Dev., 8, 3975–3986, https://doi.org/10.5194/gmd-8-3975-2015, https://doi.org/10.5194/gmd-8-3975-2015, 2015
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This paper documents the NCAR global model topography generation software. The software generates elevation and related data for global atmospheric models based in GTOPO30 or GMTED2010/MODIS source data.
K. Thayer-Calder, A. Gettelman, C. Craig, S. Goldhaber, P. A. Bogenschutz, C.-C. Chen, H. Morrison, J. Höft, E. Raut, B. M. Griffin, J. K. Weber, V. E. Larson, M. C. Wyant, M. Wang, Z. Guo, and S. J. Ghan
Geosci. Model Dev., 8, 3801–3821, https://doi.org/10.5194/gmd-8-3801-2015, https://doi.org/10.5194/gmd-8-3801-2015, 2015
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This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that is implemented in CAM v5.3. We show mean climate and tropical variability results from global simulations. The model has a degradation in precipitation skill but improvements in shortwave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. We also show estimation of computational expense and sensitivity to number of subcolumns.
R. Zhang, H. Wang, D. A. Hegg, Y. Qian, S. J. Doherty, C. Dang, P.-L. Ma, P. J. Rasch, and Q. Fu
Atmos. Chem. Phys., 15, 12805–12822, https://doi.org/10.5194/acp-15-12805-2015, https://doi.org/10.5194/acp-15-12805-2015, 2015
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We use a global climate model with an explicit source tagging technique to quantify contributions of emissions from various geographical regions and sectors to BC in North America. Model results are evaluated against measurements of near-surface and in-snow BC. We found strong spatial variations of BC and its radiative forcing that can be quantitatively attributed to the various source origins, and also identified a significant source of BC in snow that is likely missing in most climate models.
D. M. Westervelt, L. W. Horowitz, V. Naik, J.-C. Golaz, and D. L. Mauzerall
Atmos. Chem. Phys., 15, 12681–12703, https://doi.org/10.5194/acp-15-12681-2015, https://doi.org/10.5194/acp-15-12681-2015, 2015
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Decreases in aerosols over the 21st century as projected by the Representative Concentration Pathways (RCPs) lead to increases up to 0.5 - 1 ºC in global temperature and up to 0.05 - 0.1 mm/day in global precipitation, depending strongly on present-day aerosol radiative forcing. In East Asia, future aerosol decreases could be responsible for 10-20% of the total temperature increase (30-40% with strong present-day aerosol forcing), even under the high greenhouse gas emissions scenario (RCP8.5).
A. Gettelman
Atmos. Chem. Phys., 15, 12397–12411, https://doi.org/10.5194/acp-15-12397-2015, https://doi.org/10.5194/acp-15-12397-2015, 2015
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Aerosols affect cloud properties, and the radiative effects of clouds. Human emissions of aerosol particles and precursors may alter the radiative effects of clouds. This is generally a cooling effect that offsets other warming effects of human emissions of gases. Simulating these aerosol effects on clouds are highly dependent on the formulation of the microphysical (cloud droplet scale) processes. This work uses model simulations to show these effects are large, and depend on certain processes.
C. He, K.-N. Liou, Y. Takano, R. Zhang, M. Levy Zamora, P. Yang, Q. Li, and L. R. Leung
Atmos. Chem. Phys., 15, 11967–11980, https://doi.org/10.5194/acp-15-11967-2015, https://doi.org/10.5194/acp-15-11967-2015, 2015
B. Kravitz, A. Robock, S. Tilmes, O. Boucher, J. M. English, P. J. Irvine, A. Jones, M. G. Lawrence, M. MacCracken, H. Muri, J. C. Moore, U. Niemeier, S. J. Phipps, J. Sillmann, T. Storelvmo, H. Wang, and S. Watanabe
Geosci. Model Dev., 8, 3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, https://doi.org/10.5194/gmd-8-3379-2015, 2015
A. Stohl, B. Aamaas, M. Amann, L. H. Baker, N. Bellouin, T. K. Berntsen, O. Boucher, R. Cherian, W. Collins, N. Daskalakis, M. Dusinska, S. Eckhardt, J. S. Fuglestvedt, M. Harju, C. Heyes, Ø. Hodnebrog, J. Hao, U. Im, M. Kanakidou, Z. Klimont, K. Kupiainen, K. S. Law, M. T. Lund, R. Maas, C. R. MacIntosh, G. Myhre, S. Myriokefalitakis, D. Olivié, J. Quaas, B. Quennehen, J.-C. Raut, S. T. Rumbold, B. H. Samset, M. Schulz, Ø. Seland, K. P. Shine, R. B. Skeie, S. Wang, K. E. Yttri, and T. Zhu
Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, https://doi.org/10.5194/acp-15-10529-2015, 2015
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This paper presents a summary of the findings of the ECLIPSE EU project. The project has investigated the climate and air quality impacts of short-lived climate pollutants (especially methane, ozone, aerosols) and has designed a global mitigation strategy that maximizes co-benefits between air quality and climate policy. Transient climate model simulations allowed quantifying the impacts on temperature (e.g., reduction in global warming by 0.22K for the decade 2041-2050) and precipitation.
A. H. Baker, D. M. Hammerling, M. N. Levy, H. Xu, J. M. Dennis, B. E. Eaton, J. Edwards, C. Hannay, S. A. Mickelson, R. B. Neale, D. Nychka, J. Shollenberger, J. Tribbia, M. Vertenstein, and D. Williamson
Geosci. Model Dev., 8, 2829–2840, https://doi.org/10.5194/gmd-8-2829-2015, https://doi.org/10.5194/gmd-8-2829-2015, 2015
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Climate simulation codes are especially complex, and their ongoing state of development requires frequent software quality assurance to both
preserve code quality and instil model confidence. To formalize and simplify this previously subjective and expensive process, we
have developed a new tool for evaluating climate consistency.
The tool has proven its utility in detecting errors in software and hardware
environments and providing rapid feedback to model developers.
V. N. Aswathy, O. Boucher, M. Quaas, U. Niemeier, H. Muri, J. Mülmenstädt, and J. Quaas
Atmos. Chem. Phys., 15, 9593–9610, https://doi.org/10.5194/acp-15-9593-2015, https://doi.org/10.5194/acp-15-9593-2015, 2015
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Simulations conducted in the GeoMIP and IMPLICC model intercomparison studies for climate engineering by stratospheric sulfate injection and marine cloud brightening via sea salt are analysed and compared to the reference scenario RCP4.5. The focus is on extremes in surface temperature and precipitation. It is found that the extreme changes mostly follow the mean changes and that extremes are also in general well mitigated, except for in polar regions.
S. Eckhardt, B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J. H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I. E. Nielsen, J. K. Nøjgaard, J. Quaas, P. K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. von Salzen, and A. Stohl
Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, https://doi.org/10.5194/acp-15-9413-2015, 2015
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The concentrations of sulfate, black carbon and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality. In this study, we evaluate sulfate and BC concentrations from different updated models and emissions against a comprehensive pan-Arctic measurement data set. We find that the models improved but still struggle to get the maximum concentrations.
L. H. Baker, W. J. Collins, D. J. L. Olivié, R. Cherian, Ø. Hodnebrog, G. Myhre, and J. Quaas
Atmos. Chem. Phys., 15, 8201–8216, https://doi.org/10.5194/acp-15-8201-2015, https://doi.org/10.5194/acp-15-8201-2015, 2015
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We investigate the impact of removing land-based anthropogenic emissions of three aerosol species, using four fully-coupled atmosphere-ocean global climate models. Removing SO2 emissions leads to warming globally, strongest in the Northern Hemisphere (NH), and an increase in NH precipitation. Organic and black carbon (OC, BC) have a weaker impact, and less certainty on the response; OC (BC) removal shows a weak overall warming (cooling), and both show small increases in precipitation globally.
R. Zhang, H. Wang, Y. Qian, P. J. Rasch, R. C. Easter, P.-L. Ma, B. Singh, J. Huang, and Q. Fu
Atmos. Chem. Phys., 15, 6205–6223, https://doi.org/10.5194/acp-15-6205-2015, https://doi.org/10.5194/acp-15-6205-2015, 2015
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We use the CAM5 model with a novel source-tagging technique to characterize the fate of BC particles emitted from various geographical regions and sectors and their transport pathways to the Himalayas and Tibetan Plateau (HTP). We show a comprehensive picture of the seasonal and regional dependence of BC source attributions, and find strong seasonal and spatial variations in BC-in-snow radiative forcing in the HTP that can be quantitatively attributed to the various regional/sectoral sources.
N. Sudarchikova, U. Mikolajewicz, C. Timmreck, D. O'Donnell, G. Schurgers, D. Sein, and K. Zhang
Clim. Past, 11, 765–779, https://doi.org/10.5194/cp-11-765-2015, https://doi.org/10.5194/cp-11-765-2015, 2015
W.-L. Lee, Y. Gu, K. N. Liou, L. R. Leung, and H.-H. Hsu
Atmos. Chem. Phys., 15, 5405–5413, https://doi.org/10.5194/acp-15-5405-2015, https://doi.org/10.5194/acp-15-5405-2015, 2015
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This paper investigates 3-D mountain effects on solar flux distributions and their impact on surface hydrology over the western United States, specifically the Rocky Mountains and the Sierra Nevada, using the global CCSM4 (CAM4/CLM4) with a 0.23°×0.31° resolution for simulations over 6 years. We show that deviations in the net surface fluxes are not only affected by 3-D mountains but also influenced by feedbacks of cloud and snow in association with the long-term simulations.
S. Tilmes, J.-F. Lamarque, L. K. Emmons, D. E. Kinnison, P.-L. Ma, X. Liu, S. Ghan, C. Bardeen, S. Arnold, M. Deeter, F. Vitt, T. Ryerson, J. W. Elkins, F. Moore, J. R. Spackman, and M. Val Martin
Geosci. Model Dev., 8, 1395–1426, https://doi.org/10.5194/gmd-8-1395-2015, https://doi.org/10.5194/gmd-8-1395-2015, 2015
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The Community Atmosphere Model (CAM), version 5, is now coupled to extensive tropospheric and stratospheric chemistry, called CAM5-chem, and is available in addition to CAM4-chem in the Community Earth System Model (CESM) version 1.2. Both configurations are well suited as tools for atmospheric chemistry modeling studies in the troposphere and lower stratosphere.
P. H. Lauritzen, A. J. Conley, J.-F. Lamarque, F. Vitt, and M. A. Taylor
Geosci. Model Dev., 8, 1299–1313, https://doi.org/10.5194/gmd-8-1299-2015, https://doi.org/10.5194/gmd-8-1299-2015, 2015
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This test extends the evaluation of transport schemes from prescribed advection of inert scalars to reactive species. It consists of transporting two reacting chlorine-like species in an idealized flow field. The sources/sinks are given by a simple but non-linear toy chemistry that mimics photolysis-driven processes near the solar terminator. As a result, strong gradients in the spatial distribution of the species develop near the edge of the terminator.
B. Lebassi-Habtezion and P. M. Caldwell
Geosci. Model Dev., 8, 817–828, https://doi.org/10.5194/gmd-8-817-2015, https://doi.org/10.5194/gmd-8-817-2015, 2015
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In this study we explore the problem in running default CAM5-SCM, which initializes the aerosol to zero, and test three potential fixes in four different cloud regimes: DYCOMSRF02, MPACE-B, RICO, and ARM95. Stratiform cloud cases (DYCOMS RF02 and MPACE-B) were found to have a strong dependence on aerosol concentration, while convective cases (RICO and ARM95) were relatively insensitive to aerosol specification.
Y. Fang, C. Liu, and L. R. Leung
Geosci. Model Dev., 8, 781–789, https://doi.org/10.5194/gmd-8-781-2015, https://doi.org/10.5194/gmd-8-781-2015, 2015
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1. A gradient projection method was used to reduce the computation time of carbon-nitrogen spin-up processes in CLM4.
2. Point-scale simulations showed that the cyclic stability of total carbon for some cases differs from that of the periodic atmospheric forcing, and some cases even showed instability.
3. The instability issue is resolved after the hydrology scheme in CLM4 is replaced with a flow model for variably saturated porous media.
P. Hess, D. Kinnison, and Q. Tang
Atmos. Chem. Phys., 15, 2341–2365, https://doi.org/10.5194/acp-15-2341-2015, https://doi.org/10.5194/acp-15-2341-2015, 2015
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Using a series of model simulations, we find that at widespread NH extratropical locations, interannual tropospheric ozone variability is largely determined by the transport of ozone from the stratosphere. This has implications in the interpretation of measured tropospheric ozone variability in light of changes in the emissions of ozone precursors and in the response of tropospheric ozone to climate change.
L. K. Berg, M. Shrivastava, R. C. Easter, J. D. Fast, E. G. Chapman, Y. Liu, and R. A. Ferrare
Geosci. Model Dev., 8, 409–429, https://doi.org/10.5194/gmd-8-409-2015, https://doi.org/10.5194/gmd-8-409-2015, 2015
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This work presents a new methodology for representing regional-scale impacts of cloud processing on both aerosol and trace gases in sub-grid-scale convective clouds. Using the new methodology, we can better simulate the aerosol lifecycle over large areas. The results presented in this work highlight the potential change in column-integrated amounts of black carbon, organic aerosol, and sulfate aerosol, which were found to range from -50% for black carbon to +40% for sulfate.
X. Shi, X. Liu, and K. Zhang
Atmos. Chem. Phys., 15, 1503–1520, https://doi.org/10.5194/acp-15-1503-2015, https://doi.org/10.5194/acp-15-1503-2015, 2015
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The ice nucleation scheme in the Community Atmosphere Model (CAM5) was improved by considering the effects of pre-existing ice crystals and some other modifications. Subsequently, the comparison between different ice nucleation parameterizations is investigated. Experiment using the ice nucleation parameterization of Kärcher et al. (2006) predicts a much smaller anthropogenic aerosol indirect forcing than that using the parameterizations of Liu and Penner (2005) and Barahona and Nenes (2009).
M. Wang, B. Xu, J. Cao, X. Tie, H. Wang, R. Zhang, Y. Qian, P. J. Rasch, S. Zhao, G. Wu, H. Zhao, D. R. Joswiak, J. Li, and Y. Xie
Atmos. Chem. Phys., 15, 1191–1204, https://doi.org/10.5194/acp-15-1191-2015, https://doi.org/10.5194/acp-15-1191-2015, 2015
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Carbonaceous aerosols recorded in a Tibetan glacier present a distinct seasonal dependence and an increasing trend after 1980, which has important implications for the accelerated glacier melting. We use a global aerosol--climate model to quantify the aerosol source--receptor relationships, showing that emissions in South Asia had the largest contribution. The emission inventories and historical fuel consumption in South Asia are consistent with our ice-core analysis and model results.
M. P. Jensen, T. Toto, D. Troyan, P. E. Ciesielski, D. Holdridge, J. Kyrouac, J. Schatz, Y. Zhang, and S. Xie
Atmos. Meas. Tech., 8, 421–434, https://doi.org/10.5194/amt-8-421-2015, https://doi.org/10.5194/amt-8-421-2015, 2015
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A major component of the 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state. This manuscript describes the details of the MC3E radiosonde operations including the instrumentation, data processing and analysis of the impacts of bias correction and algorithm assumptions on the determination of forcing data sets.
R. A. Scanza, N. Mahowald, S. Ghan, C. S. Zender, J. F. Kok, X. Liu, Y. Zhang, and S. Albani
Atmos. Chem. Phys., 15, 537–561, https://doi.org/10.5194/acp-15-537-2015, https://doi.org/10.5194/acp-15-537-2015, 2015
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The main purpose of this study was to build a framework in the Community Atmosphere Models version 4 and 5 within the Community Earth System Model to simulate dust aerosols as their component minerals. With this framework, we investigate the direct radiative forcing that results from the mineral speciation. We find that adding mineralogy results in a small positive forcing at the top of the atmosphere, while simulations without mineralogy have a small negative forcing.
R. L. Storer, B. M. Griffin, J. Höft, J. K. Weber, E. Raut, V. E. Larson, M. Wang, and P. J. Rasch
Geosci. Model Dev., 8, 1–19, https://doi.org/10.5194/gmd-8-1-2015, https://doi.org/10.5194/gmd-8-1-2015, 2015
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Representing clouds in climate models is a challenging problem. It is particularly difficult to represent deep convective clouds and, historically, deep convective parameterization is separate from the representation of other cloud types. Here we use a single-column cloud model to simulate three deep convective cases, and two shallow cloud cases. The results look reasonable, demonstrating that it may be possible to use one parameterization within a climate model for all cloud types.
S. M. Burrows, O. Ogunro, A. A. Frossard, L. M. Russell, P. J. Rasch, and S. M. Elliott
Atmos. Chem. Phys., 14, 13601–13629, https://doi.org/10.5194/acp-14-13601-2014, https://doi.org/10.5194/acp-14-13601-2014, 2014
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The air over the ocean is full of sea spray particles ejected by bubbles that burst in the wake of breaking waves. The smallest of such particles, less than a micrometer in diameter, include organic matter derived from ocean biota. This paper introduces a method to calculate the chemical composition of spray particles. Ocean organic matter is divided into several classes using a global model. Basic chemistry relationships predict the amount of organic material in emitted spray.
N. Hiranuma, M. Paukert, I. Steinke, K. Zhang, G. Kulkarni, C. Hoose, M. Schnaiter, H. Saathoff, and O. Möhler
Atmos. Chem. Phys., 14, 13145–13158, https://doi.org/10.5194/acp-14-13145-2014, https://doi.org/10.5194/acp-14-13145-2014, 2014
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A new heterogeneous ice nucleation parameterization is developed and implemented in cloud models. The results of our simulations suggest stronger influence of dust particles lifted to the upper troposphere on heterogeneous nucleation and more ice nucleation at temperature and humidity conditions relevant to both mixed-phase and cirrus clouds when compared to the existing parametrical frameworks.
O. Guba, M. A. Taylor, P. A. Ullrich, J. R. Overfelt, and M. N. Levy
Geosci. Model Dev., 7, 2803–2816, https://doi.org/10.5194/gmd-7-2803-2014, https://doi.org/10.5194/gmd-7-2803-2014, 2014
C. Zhao, Z. Hu, Y. Qian, L. Ruby Leung, J. Huang, M. Huang, J. Jin, M. G. Flanner, R. Zhang, H. Wang, H. Yan, Z. Lu, and D. G. Streets
Atmos. Chem. Phys., 14, 11475–11491, https://doi.org/10.5194/acp-14-11475-2014, https://doi.org/10.5194/acp-14-11475-2014, 2014
S. Yu, R. Mathur, J. Pleim, D. Wong, R. Gilliam, K. Alapaty, C. Zhao, and X. Liu
Atmos. Chem. Phys., 14, 11247–11285, https://doi.org/10.5194/acp-14-11247-2014, https://doi.org/10.5194/acp-14-11247-2014, 2014
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
D. Müller, C. A. Hostetler, R. A. Ferrare, S. P. Burton, E. Chemyakin, A. Kolgotin, J. W. Hair, A. L. Cook, D. B. Harper, R. R. Rogers, R. W. Hare, C. S. Cleckner, M. D. Obland, J. Tomlinson, L. K. Berg, and B. Schmid
Atmos. Meas. Tech., 7, 3487–3496, https://doi.org/10.5194/amt-7-3487-2014, https://doi.org/10.5194/amt-7-3487-2014, 2014
Y. Wang, X. Liu, C. Hoose, and B. Wang
Atmos. Chem. Phys., 14, 10411–10430, https://doi.org/10.5194/acp-14-10411-2014, https://doi.org/10.5194/acp-14-10411-2014, 2014
E. Kassianov, J. Barnard, M. Pekour, L. K. Berg, J. Shilling, C. Flynn, F. Mei, and A. Jefferson
Atmos. Meas. Tech., 7, 3247–3261, https://doi.org/10.5194/amt-7-3247-2014, https://doi.org/10.5194/amt-7-3247-2014, 2014
T. Eidhammer, H. Morrison, A. Bansemer, A. Gettelman, and A. J. Heymsfield
Atmos. Chem. Phys., 14, 10103–10118, https://doi.org/10.5194/acp-14-10103-2014, https://doi.org/10.5194/acp-14-10103-2014, 2014
H. Wan, P. J. Rasch, K. Zhang, Y. Qian, H. Yan, and C. Zhao
Geosci. Model Dev., 7, 1961–1977, https://doi.org/10.5194/gmd-7-1961-2014, https://doi.org/10.5194/gmd-7-1961-2014, 2014
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, A. Gettelman, P. Räisänen, and M. D. Zelinka
Atmos. Chem. Phys., 14, 8701–8721, https://doi.org/10.5194/acp-14-8701-2014, https://doi.org/10.5194/acp-14-8701-2014, 2014
K. Zhang, H. Wan, X. Liu, S. J. Ghan, G. J. Kooperman, P.-L. Ma, P. J. Rasch, D. Neubauer, and U. Lohmann
Atmos. Chem. Phys., 14, 8631–8645, https://doi.org/10.5194/acp-14-8631-2014, https://doi.org/10.5194/acp-14-8631-2014, 2014
D. Barahona, A. Molod, J. Bacmeister, A. Nenes, A. Gettelman, H. Morrison, V. Phillips, and A. Eichmann
Geosci. Model Dev., 7, 1733–1766, https://doi.org/10.5194/gmd-7-1733-2014, https://doi.org/10.5194/gmd-7-1733-2014, 2014
Z. Zhang, K. Meyer, S. Platnick, L. Oreopoulos, D. Lee, and H. Yu
Atmos. Meas. Tech., 7, 1777–1789, https://doi.org/10.5194/amt-7-1777-2014, https://doi.org/10.5194/amt-7-1777-2014, 2014
A. J. Scarino, M. D. Obland, J. D. Fast, S. P. Burton, R. A. Ferrare, C. A. Hostetler, L. K. Berg, B. Lefer, C. Haman, J. W. Hair, R. R. Rogers, C. Butler, A. L. Cook, and D. B. Harper
Atmos. Chem. Phys., 14, 5547–5560, https://doi.org/10.5194/acp-14-5547-2014, https://doi.org/10.5194/acp-14-5547-2014, 2014
T. K. Tesfa, H.-Y. Li, L. R. Leung, M. Huang, Y. Ke, Y. Sun, and Y. Liu
Geosci. Model Dev., 7, 947–963, https://doi.org/10.5194/gmd-7-947-2014, https://doi.org/10.5194/gmd-7-947-2014, 2014
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 2014
P.-L. Ma, P. J. Rasch, J. D. Fast, R. C. Easter, W. I. Gustafson Jr., X. Liu, S. J. Ghan, and B. Singh
Geosci. Model Dev., 7, 755–778, https://doi.org/10.5194/gmd-7-755-2014, https://doi.org/10.5194/gmd-7-755-2014, 2014
M. S. Long, W. C. Keene, R. C. Easter, R. Sander, X. Liu, A. Kerkweg, and D. Erickson
Atmos. Chem. Phys., 14, 3397–3425, https://doi.org/10.5194/acp-14-3397-2014, https://doi.org/10.5194/acp-14-3397-2014, 2014
C. Jiao, M. G. Flanner, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, K. S. Carslaw, M. Chin, N. De Luca, T. Diehl, S. J. Ghan, T. Iversen, A. Kirkevåg, D. Koch, X. Liu, G. W. Mann, J. E. Penner, G. Pitari, M. Schulz, Ø. Seland, R. B. Skeie, S. D. Steenrod, P. Stier, T. Takemura, K. Tsigaridis, T. van Noije, Y. Yun, and K. Zhang
Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, https://doi.org/10.5194/acp-14-2399-2014, 2014
P. H. Lauritzen, P. A. Ullrich, C. Jablonowski, P. A. Bosler, D. Calhoun, A. J. Conley, T. Enomoto, L. Dong, S. Dubey, O. Guba, A. B. Hansen, E. Kaas, J. Kent, J.-F. Lamarque, M. J. Prather, D. Reinert, V. V. Shashkin, W. C. Skamarock, B. Sørensen, M. A. Taylor, and M. A. Tolstykh
Geosci. Model Dev., 7, 105–145, https://doi.org/10.5194/gmd-7-105-2014, https://doi.org/10.5194/gmd-7-105-2014, 2014
G. de Boer, M. D. Shupe, P. M. Caldwell, S. E. Bauer, O. Persson, J. S. Boyle, M. Kelley, S. A. Klein, and M. Tjernström
Atmos. Chem. Phys., 14, 427–445, https://doi.org/10.5194/acp-14-427-2014, https://doi.org/10.5194/acp-14-427-2014, 2014
J. Fan, L. R. Leung, P. J. DeMott, J. M. Comstock, B. Singh, D. Rosenfeld, J. M. Tomlinson, A. White, K. A. Prather, P. Minnis, J. K. Ayers, and Q. Min
Atmos. Chem. Phys., 14, 81–101, https://doi.org/10.5194/acp-14-81-2014, https://doi.org/10.5194/acp-14-81-2014, 2014
C.-C. Chen and A. Gettelman
Atmos. Chem. Phys., 13, 12525–12536, https://doi.org/10.5194/acp-13-12525-2013, https://doi.org/10.5194/acp-13-12525-2013, 2013
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, K. Wyser, and M. D. Zelinka
Atmos. Chem. Phys., 13, 12043–12058, https://doi.org/10.5194/acp-13-12043-2013, https://doi.org/10.5194/acp-13-12043-2013, 2013
Y. Sun, Z. Hou, M. Huang, F. Tian, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 17, 4995–5011, https://doi.org/10.5194/hess-17-4995-2013, https://doi.org/10.5194/hess-17-4995-2013, 2013
K. N. Liou, Y. Gu, L. R. Leung, W. L. Lee, and R. G. Fovell
Atmos. Chem. Phys., 13, 11709–11721, https://doi.org/10.5194/acp-13-11709-2013, https://doi.org/10.5194/acp-13-11709-2013, 2013
N. Voisin, L. Liu, M. Hejazi, T. Tesfa, H. Li, M. Huang, Y. Liu, and L. R. Leung
Hydrol. Earth Syst. Sci., 17, 4555–4575, https://doi.org/10.5194/hess-17-4555-2013, https://doi.org/10.5194/hess-17-4555-2013, 2013
Y. Fang, M. Huang, C. Liu, H. Li, and L. R. Leung
Geosci. Model Dev., 6, 1977–1988, https://doi.org/10.5194/gmd-6-1977-2013, https://doi.org/10.5194/gmd-6-1977-2013, 2013
C. Zhao, X. Liu, Y. Qian, J. Yoon, Z. Hou, G. Lin, S. McFarlane, H. Wang, B. Yang, P.-L. Ma, H. Yan, and J. Bao
Atmos. Chem. Phys., 13, 10969–10987, https://doi.org/10.5194/acp-13-10969-2013, https://doi.org/10.5194/acp-13-10969-2013, 2013
C. Zhao, S. Chen, L. R. Leung, Y. Qian, J. F. Kok, R. A. Zaveri, and J. Huang
Atmos. Chem. Phys., 13, 10733–10753, https://doi.org/10.5194/acp-13-10733-2013, https://doi.org/10.5194/acp-13-10733-2013, 2013
A. Gettelman, H. Morrison, C. R. Terai, and R. Wood
Atmos. Chem. Phys., 13, 9855–9867, https://doi.org/10.5194/acp-13-9855-2013, https://doi.org/10.5194/acp-13-9855-2013, 2013
N. Voisin, H. Li, D. Ward, M. Huang, M. Wigmosta, and L. R. Leung
Hydrol. Earth Syst. Sci., 17, 3605–3622, https://doi.org/10.5194/hess-17-3605-2013, https://doi.org/10.5194/hess-17-3605-2013, 2013
Y. Ke, L. R. Leung, M. Huang, and H. Li
Geosci. Model Dev., 6, 1609–1622, https://doi.org/10.5194/gmd-6-1609-2013, https://doi.org/10.5194/gmd-6-1609-2013, 2013
H. Wan, P. J. Rasch, K. Zhang, J. Kazil, and L. R. Leung
Geosci. Model Dev., 6, 861–874, https://doi.org/10.5194/gmd-6-861-2013, https://doi.org/10.5194/gmd-6-861-2013, 2013
H. Wang, R. C. Easter, P. J. Rasch, M. Wang, X. Liu, S. J. Ghan, Y. Qian, J.-H. Yoon, P.-L. Ma, and V. Vinoj
Geosci. Model Dev., 6, 765–782, https://doi.org/10.5194/gmd-6-765-2013, https://doi.org/10.5194/gmd-6-765-2013, 2013
H. Wan, M. A. Giorgetta, G. Zängl, M. Restelli, D. Majewski, L. Bonaventura, K. Fröhlich, D. Reinert, P. Rípodas, L. Kornblueh, and J. Förstner
Geosci. Model Dev., 6, 735–763, https://doi.org/10.5194/gmd-6-735-2013, https://doi.org/10.5194/gmd-6-735-2013, 2013
K. Zhang, X. Liu, M. Wang, J. M. Comstock, D. L. Mitchell, S. Mishra, and G. G. Mace
Atmos. Chem. Phys., 13, 4963–4982, https://doi.org/10.5194/acp-13-4963-2013, https://doi.org/10.5194/acp-13-4963-2013, 2013
D. T. Shindell, J.-F. Lamarque, M. Schulz, M. Flanner, C. Jiao, M. Chin, P. J. Young, Y. H. Lee, L. Rotstayn, N. Mahowald, G. Milly, G. Faluvegi, Y. Balkanski, W. J. Collins, A. J. Conley, S. Dalsoren, R. Easter, S. Ghan, L. Horowitz, X. Liu, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. Skeie, K. Sudo, S. Szopa, T. Takemura, A. Voulgarakis, J.-H. Yoon, and F. Lo
Atmos. Chem. Phys., 13, 2939–2974, https://doi.org/10.5194/acp-13-2939-2013, https://doi.org/10.5194/acp-13-2939-2013, 2013
B. H. Samset, G. Myhre, M. Schulz, Y. Balkanski, S. Bauer, T. K. Berntsen, H. Bian, N. Bellouin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, S. Kinne, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 13, 2423–2434, https://doi.org/10.5194/acp-13-2423-2013, https://doi.org/10.5194/acp-13-2423-2013, 2013
M. S. Long, W. C. Keene, R. Easter, R. Sander, A. Kerkweg, D. Erickson, X. Liu, and S. Ghan
Geosci. Model Dev., 6, 255–262, https://doi.org/10.5194/gmd-6-255-2013, https://doi.org/10.5194/gmd-6-255-2013, 2013
N. Bellouin, J. Quaas, J.-J. Morcrette, and O. Boucher
Atmos. Chem. Phys., 13, 2045–2062, https://doi.org/10.5194/acp-13-2045-2013, https://doi.org/10.5194/acp-13-2045-2013, 2013
Ø. Hodnebrog, T. K. Berntsen, O. Dessens, M. Gauss, V. Grewe, I. S. A. Isaksen, B. Koffi, G. Myhre, D. Olivié, M. J. Prather, F. Stordal, S. Szopa, Q. Tang, P. van Velthoven, and J. E. Williams
Atmos. Chem. Phys., 12, 12211–12225, https://doi.org/10.5194/acp-12-12211-2012, https://doi.org/10.5194/acp-12-12211-2012, 2012
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Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
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We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
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The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Philipp Weiss, Ross Herbert, and Philip Stier
EGUsphere, https://doi.org/10.5194/egusphere-2024-3325, https://doi.org/10.5194/egusphere-2024-3325, 2024
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Aerosols strongly influence Earth's climate as they interact with radiation and clouds. New Earth system models run at resolutions of a few kilometers. To simulate the Earth system with interactive aerosols, we developed a new aerosol module. It represents aerosols as an ensemble of log-normal modes with given sizes and compositions. We present a year-long simulation with four modes at a resolution of five kilometers. It captures key aerosol processes like dust storms or tropical cyclones.
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-155, https://doi.org/10.5194/gmd-2024-155, 2024
Revised manuscript accepted for GMD
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This work presents an automatic tool to enhance the performance of climate models by optimizing how computer resources are allocated. Traditional methods are time-consuming and error-prone, often resulting in inefficient simulations. Our tool improves speed and reduces computational costs without needing expert knowledge. The tool has been tested on European climate models, making simulations up to 34 % faster while using fewer resources, helping to make climate simulations more efficient.
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Short summary
An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based...
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