Articles | Volume 6, issue 1
https://doi.org/10.5194/gmd-6-255-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-255-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
22 Feb 2013
Model description paper |
| 22 Feb 2013
Implementation of the chemistry module MECCA (v2.5) in the modal aerosol version of the Community Atmosphere Model component (v3.6.33) of the Community Earth System Model
M. S. Long
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
W. C. Keene
Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22904, USA
R. Easter
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA
R. Sander
Air Chemistry Department, Max-Planck Institute of Chemistry, 55020 Mainz, Germany
A. Kerkweg
Institute for Atmospheric Physics, University of Mainz, 55099 Mainz, Germany
D. Erickson
Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
X. Liu
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA
S. Ghan
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA
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In-cloud destruction of ozone depends on hydroperoxyl radicals in cloud droplets, where they are produced by oxygenated volatile organic compound (OVOC) oxygenation. Only rudimentary representations of these processes, if any, are currently available in global atmospheric models. By using a comprehensive atmospheric model that includes a complex in-cloud OVOC oxidation scheme, we show that atmospheric oxidants are reduced and models ignoring this process will underpredict clouds as ozone sinks.
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.
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.
Julian Rüdiger, Alexandra Gutmann, Nicole Bobrowski, Marcello Liotta, J. Maarten de Moor, Rolf Sander, Florian Dinger, Jan-Lukas Tirpitz, Martha Ibarra, Armando Saballos, María Martínez, Elvis Mendoza, Arnoldo Ferrufino, John Stix, Juan Valdés, Jonathan M. Castro, and Thorsten Hoffmann
Atmos. Chem. Phys., 21, 3371–3393, https://doi.org/10.5194/acp-21-3371-2021, https://doi.org/10.5194/acp-21-3371-2021, 2021
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We present an innovative approach to study halogen chemistry in the plume of Masaya volcano in Nicaragua. An unique data set was collected using multiple techniques, including drones. These data enabled us to determine the fraction of activation of the respective halogens at various plume ages, where in-mixing of ambient air causes chemical reactions. An atmospheric chemistry box model was employed to further examine the field results and help our understanding of volcanic plume chemistry.
Domenico Taraborrelli, David Cabrera-Perez, Sara Bacer, Sergey Gromov, Jos Lelieveld, Rolf Sander, and Andrea Pozzer
Atmos. Chem. Phys., 21, 2615–2636, https://doi.org/10.5194/acp-21-2615-2021, https://doi.org/10.5194/acp-21-2615-2021, 2021
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Atmospheric pollutants from anthropogenic activities and biomass burning are usually regarded as ozone precursors. Monocyclic aromatics are no exception. Calculations with a comprehensive atmospheric model are consistent with this view but only for air masses close to pollution source regions. However, the same model predicts that aromatics, when transported to remote areas, may effectively destroy ozone. This loss of tropospheric ozone rivals the one attributed to bromine.
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.
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.
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.
Md. Robiul Islam, Thilina Jayarathne, Isobel J. Simpson, Benjamin Werden, John Maben, Ashley Gilbert, Puppala S. Praveen, Sagar Adhikari, Arnico K. Panday, Maheswar Rupakheti, Donald R. Blake, Robert J. Yokelson, Peter F. DeCarlo, William C. Keene, and Elizabeth A. Stone
Atmos. Chem. Phys., 20, 2927–2951, https://doi.org/10.5194/acp-20-2927-2020, https://doi.org/10.5194/acp-20-2927-2020, 2020
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The Kathmandu Valley experiences high levels of air pollution. In this study, atmospheric gases and particulate matter were characterized by online and off-line measurements, with an emphasis on understanding their sources. The major sources of particulate matter and trace gases were identified as garbage burning, biomass burning, and vehicles. The majority of secondary organic aerosol was attributed to anthropogenic precursors, while a minority was attributed to biogenic gases.
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.
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.
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.
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.
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).
Min Zhong, Eri Saikawa, Alexander Avramov, Chen Chen, Boya Sun, Wenlu Ye, William C. Keene, Robert J. Yokelson, Thilina Jayarathne, Elizabeth A. Stone, Maheswar Rupakheti, and Arnico K. Panday
Atmos. Chem. Phys., 19, 8209–8228, https://doi.org/10.5194/acp-19-8209-2019, https://doi.org/10.5194/acp-19-8209-2019, 2019
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Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, the capital city of Nepal. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and found that they have significant impacts on air quality surrounding the valley. Our results highlight the importance of improving local emissions estimates for air quality modeling.
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.
Rolf Sander, Andreas Baumgaertner, David Cabrera-Perez, Franziska Frank, Sergey Gromov, Jens-Uwe Grooß, Hartwig Harder, Vincent Huijnen, Patrick Jöckel, Vlassis A. Karydis, Kyle E. Niemeyer, Andrea Pozzer, Hella Riede, Martin G. Schultz, Domenico Taraborrelli, and Sebastian Tauer
Geosci. Model Dev., 12, 1365–1385, https://doi.org/10.5194/gmd-12-1365-2019, https://doi.org/10.5194/gmd-12-1365-2019, 2019
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We present the atmospheric chemistry box model CAABA/MECCA which
now includes a number of new features: skeletal mechanism
reduction, the MOM chemical mechanism for volatile organic
compounds, an option to include reactions from the Master
Chemical Mechanism (MCM) and other chemical mechanisms, updated
isotope tagging, improved and new photolysis modules, and the new
feature of coexisting multiple chemistry mechanisms.
CAABA/MECCA is a community model published under the GPL.
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.
Lu Hu, Christoph A. Keller, Michael S. Long, Tomás Sherwen, Benjamin Auer, Arlindo Da Silva, Jon E. Nielsen, Steven Pawson, Matthew A. Thompson, Atanas L. Trayanov, Katherine R. Travis, Stuart K. Grange, Mat J. Evans, and Daniel J. Jacob
Geosci. Model Dev., 11, 4603–4620, https://doi.org/10.5194/gmd-11-4603-2018, https://doi.org/10.5194/gmd-11-4603-2018, 2018
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We present a full-year online global simulation of tropospheric chemistry at 12.5 km resolution. To the best of our knowledge, such a resolution in a state-of-the-science global simulation of tropospheric chemistry is unprecedented. This simulation will serve as the Nature Run for observing system simulation experiments to support the future geostationary satellite constellation for tropospheric chemistry, and can also be used for various air quality applications.
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.
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.
Zacharias Marinou Nikolaou, Jyh-Yuan Chen, Yiannis Proestos, Jos Lelieveld, and Rolf Sander
Geosci. Model Dev., 11, 3391–3407, https://doi.org/10.5194/gmd-11-3391-2018, https://doi.org/10.5194/gmd-11-3391-2018, 2018
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Chemistry is an important component of the atmosphere that describes many important physical processes. However, atmospheric chemical mechanisms include hundreds of species and reactions, posing a significant computational load. In this work, we use a powerful reduction method in order to develop a computationally faster chemical mechanism from a detailed mechanism. This enables accelerated simulations, which can be used to examine a wider range of processes in increased detail.
Prasad Kasibhatla, Tomás Sherwen, Mathew J. Evans, Lucy J. Carpenter, Chris Reed, Becky Alexander, Qianjie Chen, Melissa P. Sulprizio, James D. Lee, Katie A. Read, William Bloss, Leigh R. Crilley, William C. Keene, Alexander A. P. Pszenny, and Alma Hodzic
Atmos. Chem. Phys., 18, 11185–11203, https://doi.org/10.5194/acp-18-11185-2018, https://doi.org/10.5194/acp-18-11185-2018, 2018
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Recent measurements of NOx and HONO suggest that photolysis of particulate nitrate in sea-salt aerosols is important in terms of marine boundary layer oxidant chemistry. We present the first global-scale assessment of the significance of this new chemical pathway for NOx, O3, and OH in the marine boundary layer. We also present a preliminary assessment of the potential impact of photolysis of particulate nitrate associated with other aerosol types on continental boundary layer chemistry.
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
Chinmay Mallik, Laura Tomsche, Efstratios Bourtsoukidis, John N. Crowley, Bettina Derstroff, Horst Fischer, Sascha Hafermann, Imke Hüser, Umar Javed, Stephan Keßel, Jos Lelieveld, Monica Martinez, Hannah Meusel, Anna Novelli, Gavin J. Phillips, Andrea Pozzer, Andreas Reiffs, Rolf Sander, Domenico Taraborrelli, Carina Sauvage, Jan Schuladen, Hang Su, Jonathan Williams, and Hartwig Harder
Atmos. Chem. Phys., 18, 10825–10847, https://doi.org/10.5194/acp-18-10825-2018, https://doi.org/10.5194/acp-18-10825-2018, 2018
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OH and HO2 control the transformation of air pollutants and O3 formation. Their implication for air quality over the climatically sensitive Mediterranean region was studied during a field campaign in Cyprus. Production of OH, HO2, and recycled OH was lower in aged marine air masses. Box model simulations of OH and HO2 agreed with measurements except at high terpene concentrations when model RO2 due to terpenes caused large HO2 loss. Autoxidation schemes for RO2 improved the agreement.
Sebastian D. Eastham, Michael S. Long, Christoph A. Keller, Elizabeth Lundgren, Robert M. Yantosca, Jiawei Zhuang, Chi Li, Colin J. Lee, Matthew Yannetti, Benjamin M. Auer, Thomas L. Clune, Jules Kouatchou, William M. Putman, Matthew A. Thompson, Atanas L. Trayanov, Andrea M. Molod, Randall V. Martin, and Daniel J. Jacob
Geosci. Model Dev., 11, 2941–2953, https://doi.org/10.5194/gmd-11-2941-2018, https://doi.org/10.5194/gmd-11-2941-2018, 2018
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Global atmospheric chemical transport models are crucial tools in atmospheric science, used to address problems ranging from climate change to acid rain. GEOS-Chem High Performance (GCHP) is a new implementation of the widely used GEOS-Chem model, designed for massively parallel architectures. GCHP v11-02c is shown to be highly scalable from 6 to over 500 cores, enabling the routine simulation of global atmospheric chemistry from the surface to the stratopause at resolutions of ~50 km or finer.
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.
Karen Yu, Christoph A. Keller, Daniel J. Jacob, Andrea M. Molod, Sebastian D. Eastham, and Michael S. Long
Geosci. Model Dev., 11, 305–319, https://doi.org/10.5194/gmd-11-305-2018, https://doi.org/10.5194/gmd-11-305-2018, 2018
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Global simulations of atmospheric chemistry are generally conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it is unable to reproduce the GCM transport exactly. We investigate the cascade of errors associated with the off-line approach using the GEOS-5 GCM and GEOS-Chem CTM and discuss improvements in the use of archived meteorology.
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.
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.
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.
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.
Bettina Derstroff, Imke Hüser, Efstratios Bourtsoukidis, John N. Crowley, Horst Fischer, Sergey Gromov, Hartwig Harder, Ruud H. H. Janssen, Jürgen Kesselmeier, Jos Lelieveld, Chinmay Mallik, Monica Martinez, Anna Novelli, Uwe Parchatka, Gavin J. Phillips, Rolf Sander, Carina Sauvage, Jan Schuladen, Christof Stönner, Laura Tomsche, and Jonathan Williams
Atmos. Chem. Phys., 17, 9547–9566, https://doi.org/10.5194/acp-17-9547-2017, https://doi.org/10.5194/acp-17-9547-2017, 2017
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The aim of the study was to examine aged air masses being transported from the European continent towards Cyprus. Longer-lived oxygenated volatile organic compounds (OVOCs) such as methanol were mainly impacted by long-distance transport and showed higher values in air masses from eastern Europe than in a flow regime from the west. The impact of the transport through the marine boundary layer as well as the influence of the residual layer/free troposphere on OVOCs were studied.
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.
Stephan Keßel, David Cabrera-Perez, Abraham Horowitz, Patrick R. Veres, Rolf Sander, Domenico Taraborrelli, Maria Tucceri, John N. Crowley, Andrea Pozzer, Christof Stönner, Luc Vereecken, Jos Lelieveld, and Jonathan Williams
Atmos. Chem. Phys., 17, 8789–8804, https://doi.org/10.5194/acp-17-8789-2017, https://doi.org/10.5194/acp-17-8789-2017, 2017
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In this study we identify an often overlooked stable oxide of carbon, namely carbon suboxide (C3O2), in ambient air. We have made C3O2 and in the laboratory determined its absorption cross section data and the rate of reaction with two important atmospheric oxidants, OH and O3. By incorporating known sources and sinks in a global model we have generated a first global picture of the distribution of this species in the atmosphere.
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.
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.
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.
David Cabrera-Perez, Domenico Taraborrelli, Rolf Sander, and Andrea Pozzer
Atmos. Chem. Phys., 16, 6931–6947, https://doi.org/10.5194/acp-16-6931-2016, https://doi.org/10.5194/acp-16-6931-2016, 2016
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The global atmospheric budget and distribution of monocyclic aromatic compounds is estimated, using an atmospheric chemistry general circulation model. Simulation results are evaluated with observations with the goal of understanding emission, production and removal of these compounds. Anthropogenic and biomass burning are the main sources of aromatic compounds to the atmosphere. The main sink is photochemical decomposition and in lesser importance dry deposition.
Patrick Jöckel, Holger Tost, Andrea Pozzer, Markus Kunze, Oliver Kirner, Carl A. M. Brenninkmeijer, Sabine Brinkop, Duy S. Cai, Christoph Dyroff, Johannes Eckstein, Franziska Frank, Hella Garny, Klaus-Dirk Gottschaldt, Phoebe Graf, Volker Grewe, Astrid Kerkweg, Bastian Kern, Sigrun Matthes, Mariano Mertens, Stefanie Meul, Marco Neumaier, Matthias Nützel, Sophie Oberländer-Hayn, Roland Ruhnke, Theresa Runde, Rolf Sander, Dieter Scharffe, and Andreas Zahn
Geosci. Model Dev., 9, 1153–1200, https://doi.org/10.5194/gmd-9-1153-2016, https://doi.org/10.5194/gmd-9-1153-2016, 2016
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With an advanced numerical global chemistry climate model (CCM) we performed several detailed
combined hind-cast and projection simulations of the period 1950 to 2100 to assess the
past, present, and potential future dynamical and chemical state of the Earth atmosphere.
The manuscript documents the model and the various applied model set-ups and provides
a first evaluation of the simulation results from a global perspective as a quality check of the data.
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.
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.
A. J. G. Baumgaertner, P. Jöckel, A. Kerkweg, R. Sander, and H. Tost
Geosci. Model Dev., 9, 125–135, https://doi.org/10.5194/gmd-9-125-2016, https://doi.org/10.5194/gmd-9-125-2016, 2016
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The Community Earth System Model (CESM1) is connected to the the Modular Earth Submodel System (MESSy) as a new base model. This allows MESSy users the option to utilize either the state-of-the art spectral element atmosphere dynamical core or the finite volume core of CESM1. Additionally, this makes several other component models available to MESSy users.
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.
A. Lupascu, R. Easter, R. Zaveri, M. Shrivastava, M. Pekour, J. Tomlinson, Q. Yang, H. Matsui, A. Hodzic, Q. Zhang, and J. D. Fast
Atmos. Chem. Phys., 15, 12283–12313, https://doi.org/10.5194/acp-15-12283-2015, https://doi.org/10.5194/acp-15-12283-2015, 2015
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.
R. Sander
Atmos. Chem. Phys., 15, 4399–4981, https://doi.org/10.5194/acp-15-4399-2015, https://doi.org/10.5194/acp-15-4399-2015, 2015
M. S. Long, R. Yantosca, J. E. Nielsen, C. A. Keller, A. da Silva, M. P. Sulprizio, S. Pawson, and D. J. Jacob
Geosci. Model Dev., 8, 595–602, https://doi.org/10.5194/gmd-8-595-2015, https://doi.org/10.5194/gmd-8-595-2015, 2015
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This paper presents results from the modularization of the GEOS-Chem chemical transport model, and its coupling as the chemical operator within the NASA-GMAO GEOS-5 Earth system model (ESM). The key findings are that chemistry within the modular GEOS-Chem system shows consistent, high strong-scaling properties across the range of distributed processors, transport is the limiting component prohibiting efficient scalability, and GEOS-Chem is able to generate suitable chemical results in an ESM.
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).
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.
B. H. Samset, G. Myhre, A. Herber, Y. Kondo, S.-M. Li, N. Moteki, M. Koike, N. Oshima, J. P. Schwarz, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, M. Chin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, M. Schulz, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 14, 12465–12477, https://doi.org/10.5194/acp-14-12465-2014, https://doi.org/10.5194/acp-14-12465-2014, 2014
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Far from black carbon (BC) emission sources, present climate models are unable to reproduce flight measurements. By comparing recent models with data, we find that the atmospheric lifetime of BC may be overestimated in models. By adjusting modeled BC concentrations to measurements in remote regions - over oceans and at high altitudes - we arrive at a reduced estimate for BC radiative forcing over the industrial era.
R. Sander, P. Jöckel, O. Kirner, A. T. Kunert, J. Landgraf, and A. Pozzer
Geosci. Model Dev., 7, 2653–2662, https://doi.org/10.5194/gmd-7-2653-2014, https://doi.org/10.5194/gmd-7-2653-2014, 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
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
K. Hens, A. Novelli, M. Martinez, J. Auld, R. Axinte, B. Bohn, H. Fischer, P. Keronen, D. Kubistin, A. C. Nölscher, R. Oswald, P. Paasonen, T. Petäjä, E. Regelin, R. Sander, V. Sinha, M. Sipilä, D. Taraborrelli, C. Tatum Ernest, J. Williams, J. Lelieveld, and H. Harder
Atmos. Chem. Phys., 14, 8723–8747, https://doi.org/10.5194/acp-14-8723-2014, https://doi.org/10.5194/acp-14-8723-2014, 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
W. C. Keene, J. L. Moody, J. N. Galloway, J. M. Prospero, O. R. Cooper, S. Eckhardt, and J. R. Maben
Atmos. Chem. Phys., 14, 8119–8135, https://doi.org/10.5194/acp-14-8119-2014, https://doi.org/10.5194/acp-14-8119-2014, 2014
R. P. Aryal, K. J. Voss, P. A. Terman, W. C. Keene, J. L. Moody, E. J. Welton, and B. N. Holben
Atmos. Chem. Phys., 14, 7617–7629, https://doi.org/10.5194/acp-14-7617-2014, https://doi.org/10.5194/acp-14-7617-2014, 2014
C. A. Keller, M. S. Long, R. M. Yantosca, A. M. Da Silva, S. Pawson, and D. J. Jacob
Geosci. Model Dev., 7, 1409–1417, https://doi.org/10.5194/gmd-7-1409-2014, https://doi.org/10.5194/gmd-7-1409-2014, 2014
R. A. Zaveri, R. C. Easter, J. E. Shilling, and J. H. Seinfeld
Atmos. Chem. Phys., 14, 5153–5181, https://doi.org/10.5194/acp-14-5153-2014, https://doi.org/10.5194/acp-14-5153-2014, 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
S. Bleicher, J. C. Buxmann, R. Sander, T. P. Riedel, J. A. Thornton, U. Platt, and C. Zetzsch
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-10135-2014, https://doi.org/10.5194/acpd-14-10135-2014, 2014
Revised manuscript has not been submitted
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
J. A. Adame, M. Martínez, M. Sorribas, P. J. Hidalgo, H. Harder, J.-M. Diesch, F. Drewnick, W. Song, J. Williams, V. Sinha, M. A. Hernández-Ceballos, J. Vilà-Guerau de Arellano, R. Sander, Z. Hosaynali-Beygi, H. Fischer, J. Lelieveld, and B. De la Morena
Atmos. Chem. Phys., 14, 2325–2342, https://doi.org/10.5194/acp-14-2325-2014, https://doi.org/10.5194/acp-14-2325-2014, 2014
J. L. Moody, W. C. Keene, O. R. Cooper, K. J. Voss, R. Aryal, S. Eckhardt, B. Holben, J. R. Maben, M. A. Izaguirre, and J. N. Galloway
Atmos. Chem. Phys., 14, 691–717, https://doi.org/10.5194/acp-14-691-2014, https://doi.org/10.5194/acp-14-691-2014, 2014
R. Sander, A. A. P. Pszenny, W. C. Keene, E. Crete, B. Deegan, M. S. Long, J. R. Maben, and A. H. Young
Earth Syst. Sci. Data, 5, 385–392, https://doi.org/10.5194/essd-5-385-2013, https://doi.org/10.5194/essd-5-385-2013, 2013
H. Keller-Rudek, G. K. Moortgat, R. Sander, and R. Sörensen
Earth Syst. Sci. Data, 5, 365–373, https://doi.org/10.5194/essd-5-365-2013, https://doi.org/10.5194/essd-5-365-2013, 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
E. Regelin, H. Harder, M. Martinez, D. Kubistin, C. Tatum Ernest, H. Bozem, T. Klippel, Z. Hosaynali-Beygi, H. Fischer, R. Sander, P. Jöckel, R. Königstedt, and J. Lelieveld
Atmos. Chem. Phys., 13, 10703–10720, https://doi.org/10.5194/acp-13-10703-2013, https://doi.org/10.5194/acp-13-10703-2013, 2013
J. Brioude, D. Arnold, A. Stohl, M. Cassiani, D. Morton, P. Seibert, W. Angevine, S. Evan, A. Dingwell, J. D. Fast, R. C. Easter, I. Pisso, J. Burkhart, and G. Wotawa
Geosci. Model Dev., 6, 1889–1904, https://doi.org/10.5194/gmd-6-1889-2013, https://doi.org/10.5194/gmd-6-1889-2013, 2013
S. J. Ghan
Atmos. Chem. Phys., 13, 9971–9974, https://doi.org/10.5194/acp-13-9971-2013, https://doi.org/10.5194/acp-13-9971-2013, 2013
J.-F. Lamarque, F. Dentener, J. McConnell, C.-U. Ro, M. Shaw, R. Vet, D. Bergmann, P. Cameron-Smith, S. Dalsoren, R. Doherty, G. Faluvegi, S. J. Ghan, B. Josse, Y. H. Lee, I. A. MacKenzie, D. Plummer, D. T. Shindell, R. B. Skeie, D. S. Stevenson, S. Strode, G. Zeng, M. Curran, D. Dahl-Jensen, S. Das, D. Fritzsche, and M. Nolan
Atmos. Chem. Phys., 13, 7997–8018, https://doi.org/10.5194/acp-13-7997-2013, https://doi.org/10.5194/acp-13-7997-2013, 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
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
P. Stier, N. A. J. Schutgens, N. Bellouin, H. Bian, O. Boucher, M. Chin, S. Ghan, N. Huneeus, S. Kinne, G. Lin, X. Ma, G. Myhre, J. E. Penner, C. A. Randles, B. Samset, M. Schulz, T. Takemura, F. Yu, H. Yu, and C. Zhou
Atmos. Chem. Phys., 13, 3245–3270, https://doi.org/10.5194/acp-13-3245-2013, https://doi.org/10.5194/acp-13-3245-2013, 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
Y. H. Lee, J.-F. Lamarque, M. G. Flanner, C. Jiao, D. T. Shindell, T. Berntsen, M. M. Bisiaux, J. Cao, W. J. Collins, M. Curran, R. Edwards, G. Faluvegi, S. Ghan, L. W. Horowitz, J. R. McConnell, J. Ming, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. B. Skeie, K. Sudo, T. Takemura, F. Thevenon, B. Xu, and J.-H. Yoon
Atmos. Chem. Phys., 13, 2607–2634, https://doi.org/10.5194/acp-13-2607-2013, https://doi.org/10.5194/acp-13-2607-2013, 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
A. Kirkevåg, T. Iversen, Ø. Seland, C. Hoose, J. E. Kristjánsson, H. Struthers, A. M. L. Ekman, S. Ghan, J. Griesfeller, E. D. Nilsson, and M. Schulz
Geosci. Model Dev., 6, 207–244, https://doi.org/10.5194/gmd-6-207-2013, https://doi.org/10.5194/gmd-6-207-2013, 2013
J.-F. Lamarque, D. T. Shindell, B. Josse, P. J. Young, I. Cionni, V. Eyring, D. Bergmann, P. Cameron-Smith, W. J. Collins, R. Doherty, S. Dalsoren, G. Faluvegi, G. Folberth, S. J. Ghan, L. W. Horowitz, Y. H. Lee, I. A. MacKenzie, T. Nagashima, V. Naik, D. Plummer, M. Righi, S. T. Rumbold, M. Schulz, R. B. Skeie, D. S. Stevenson, S. Strode, K. Sudo, S. Szopa, A. Voulgarakis, and G. Zeng
Geosci. Model Dev., 6, 179–206, https://doi.org/10.5194/gmd-6-179-2013, https://doi.org/10.5194/gmd-6-179-2013, 2013
R. Sander and J. Bottenheim
Earth Syst. Sci. Data, 4, 215–282, https://doi.org/10.5194/essd-4-215-2012, https://doi.org/10.5194/essd-4-215-2012, 2012
Related subject area
Climate and Earth system modeling
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
TorchClim v1.0: a deep-learning plugin for climate model physics
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Architectural Insights and Training Methodology Optimization of Pangu-Weather
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Robust handling of extremes in quantile mapping – "Murder your darlings"
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
Short-term effects of hurricanes on nitrate-nitrogen runoff loading: a case study of Hurricane Ida using E3SM land model (v2.1)
CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
Evaluation of global fire simulations in CMIP6 Earth system models
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Design, evaluation and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Introducing the MESMER-M-TPv0.1.0 module: Spatially Explicit Earth System Model Emulation for Monthly Precipitation and Temperature
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
A computationally light-weight model for ensemble forecasting of environmental hazard: General TAMSAT-ALERT v1.2.1
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.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
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.
Deifilia Aurora To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
EGUsphere, https://doi.org/10.5194/egusphere-2024-1714, https://doi.org/10.5194/egusphere-2024-1714, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers three-dimensional 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 accessibility of training and working with the model.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
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. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
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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 range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
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We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-97, https://doi.org/10.5194/gmd-2024-97, 2024
Revised manuscript accepted for GMD
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Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-70, https://doi.org/10.5194/gmd-2024-70, 2024
Revised manuscript accepted for GMD
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Hurricanes may worsen the 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 LMRB during Hurricane Ida in 2021, but less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni G. Seijo-Ellis, Donata Giglio, Gustavo M. Marques, and Frank O. Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1378, https://doi.org/10.5194/egusphere-2024-1378, 2024
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A CESM/MOM6 regional configuration of the Caribbean Sea was developed as a response to the rising need of high-resolution models for climate impact studies. The configuration is validated for the period of 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 across the multiple passages in the Caribbean Sea agree with observations.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
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.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
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. Discuss., https://doi.org/10.5194/gmd-2024-85, https://doi.org/10.5194/gmd-2024-85, 2024
Revised manuscript accepted for GMD
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This study provides the first comprehensive assessment of historical fire simulations from 19 CMIP6 ESMs. Most models reproduce global total, spatial pattern, seasonality, and regional historical changes well, but fail to simulate the recent decline in global burned area and underestimate the fire sensitivity to wet-dry conditions. They addressed three critical issues in CMIP5. We present targeted guidance for fire scheme development and methodologies to generate reliable fire projections.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Giovanni Di Virgilio, Jason 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 Riley, and Jyothi Lingala
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-87, https://doi.org/10.5194/gmd-2024-87, 2024
Revised manuscript accepted for GMD
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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.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleußner
EGUsphere, https://doi.org/10.5194/egusphere-2024-278, https://doi.org/10.5194/egusphere-2024-278, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Their joint distribution largely determines the division into climate regimes. Yet, projecting 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 to generate monthly means of local precipitation and temperature at low computational costs.
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.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Emily Black, John Ellis, and Ross Maidment
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-75, https://doi.org/10.5194/gmd-2024-75, 2024
Revised manuscript accepted for GMD
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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 forecasting data into probabilistic hazard assessments. As such, it complements existing systems and enhances their utility for actionable hazard assessment.
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