Articles | Volume 16, issue 7
https://doi.org/10.5194/gmd-16-1909-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-1909-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
06 Apr 2023
Development and technical paper |
| 06 Apr 2023
| 06 Apr 2023
Improving the representation of shallow cumulus convection with the simplified-higher-order-closure–mass-flux (SHOC+MF v1.0) approach
Maria J. Chinita
CORRESPONDING AUTHOR
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles,
Los Angeles, California, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Mikael Witte
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles,
Los Angeles, California, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Department of Meteorology, Naval Postgraduate School, Monterey, California, USA
Marcin J. Kurowski
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Joao Teixeira
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles,
Los Angeles, California, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Kay Suselj
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles,
Los Angeles, California, USA
Running Tide Technologies, Inc., Portland, Maine, USA
Georgios Matheou
Department of Mechanical Engineering, University of Connecticut, Storrs, Connecticut, USA
Peter Bogenschutz
Lawrence Livermore National Laboratory, Livermore, California, USA
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Dejian Fu, Susan S. Kulawik, Kazuyuki Miyazaki, Kevin W. Bowman, John R. Worden, Annmarie Eldering, Nathaniel J. Livesey, Joao Teixeira, Fredrick W. Irion, Robert L. Herman, Gregory B. Osterman, Xiong Liu, Pieternel F. Levelt, Anne M. Thompson, and Ming Luo
Atmos. Meas. Tech., 11, 5587–5605, https://doi.org/10.5194/amt-11-5587-2018, https://doi.org/10.5194/amt-11-5587-2018, 2018
Jesse Dorrestijn, Brian H. Kahn, João Teixeira, and Fredrick W. Irion
Atmos. Meas. Tech., 11, 2717–2733, https://doi.org/10.5194/amt-11-2717-2018, https://doi.org/10.5194/amt-11-2717-2018, 2018
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Atmospheric Infrared Sounder (AIRS) satellite observations are used to quantify the scale-dependent variance of temperature and water vapor in the atmosphere. The scale dependence is much more variable than previously thought, using a new methodology based on individual satellite swaths. A break in the scale dependence is found to vary from less than 100 to greater than 1000 km. These new variance scaling results are of high importance for improving climate GCM subgrid parameterizations.
Peter A. Bogenschutz, Andrew Gettelman, Cecile Hannay, Vincent E. Larson, Richard B. Neale, Cheryl Craig, and Chih-Chieh Chen
Geosci. Model Dev., 11, 235–255, https://doi.org/10.5194/gmd-11-235-2018, https://doi.org/10.5194/gmd-11-235-2018, 2018
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This paper compares results of developmental versions of a widely used climate model. The simulations only differ in the choice of how to model the sub-grid-scale physics in the atmospheric model. This work is novel because it is the first time that a particular physics option has been tested in a fully coupled climate model. Here, we demonstrate that this physics option has the ability to produce credible coupled climate simulations, with improved metrics in certain fields.
Brian H. Kahn, Georgios Matheou, Qing Yue, Thomas Fauchez, Eric J. Fetzer, Matthew Lebsock, João Martins, Mathias M. Schreier, Kentaroh Suzuki, and João Teixeira
Atmos. Chem. Phys., 17, 9451–9468, https://doi.org/10.5194/acp-17-9451-2017, https://doi.org/10.5194/acp-17-9451-2017, 2017
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The global-scale patterns of subtropical marine boundary layer clouds are investigated with coincident NASA A-train satellite and reanalysis data. This study is novel in that all data are used at the finest spatial and temporal resolution possible. Our results are consistent with surface-based data and suggest that the combination of satellite and reanalysis data sets have potential to add to the global context of our understanding of the subtropical cumulus-dominated marine boundary layer.
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.
M. K. Witte, P. Y. Chuang, and G. Feingold
Atmos. Chem. Phys., 14, 6729–6738, https://doi.org/10.5194/acp-14-6729-2014, https://doi.org/10.5194/acp-14-6729-2014, 2014
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
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Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
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This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2815, https://doi.org/10.5194/egusphere-2024-2815, 2024
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate that effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense and consists well with radiative model calculations and can be applied to atmospheric models with speed requirements.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
Short summary
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
Short summary
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
Cited articles
Beljaars, A., Balsamo, G., Bechtold, P., Bozzo, A., Forbes, R., Hogan, R.
J., Köhler, M., Morcrette, J. J., Tompkins, A. M., Viterbo, P., and
Wedi, N.: The Numerics of Physical Parametrization in the ECMWF Model,
Front. Earth Sci., 6, 1–18, https://doi.org/10.3389/feart.2018.00137, 2018.
Betts, A. K.: Non-precipitating cumulus convection and its parameterization,
Q. J. Roy. Meteor. Soc., 99, 178–196,
https://doi.org/10.1002/qj.49709941915, 1973.
Blackadar, A. K.: The vertical distribution of wind and turbulent exchange
in a neutral atmosphere, J. Geophys. Res., 67, 3095–3102, 1962.
Bogenschutz, P. A. and Krueger, S. K.: A simplified PDF parameterization of
subgrid-scale clouds and turbulence for cloud-resolving models, J. Adv.
Model. Earth Sy., 5, 195–211, https://doi.org/10.1002/jame.20018, 2013.
Bogenschutz, P. A., Tang, S., Caldwell, P. M., Xie, S., Lin, W., and Chen, Y.-S.: The E3SM version 1 single-column model, Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020, 2020.
Böing, S. J., Jonker, H. J. J., Siebesma, A. P., and Grabowski, W. W.:
Influence of the subcloud layer on the development of a deep convective
ensemble, J. Atmos. Sci., 69, 2682–2698,
https://doi.org/10.1175/JAS-D-11-0317.1, 2012.
Brient, F., Couvreux, F., Villefranque, N., Rio, C., and Honnert, R.:
Object-Oriented Identification of Coherent Structures in Large Eddy
Simulations: Importance of Downdrafts in Stratocumulus, Geophys. Res. Lett.,
46, 2854–2864, https://doi.org/10.1029/2018GL081499, 2019.
Brown, A. R., Cederwall, R. T., Chlond, A., Duynkerke, P. G., Golaz, J. C.,
Khairoutdinov, M., Lewellen, D. C., Lock, A. P., MacVean, M. K., Moeng, C.
H., Neggers, R. A. J., Siebesma, A. P., and Stevens, B.: Large-eddy
simulation of the diurnal cycle of shallow cumulus convection over land, Q. J. Roy. Meteor. Soc., 128, 1075–1093,
https://doi.org/10.1256/003590002320373210, 2002.
Caldwell, P. M., Terai, C. R., Hillman, B., Keen, N. D., Bogenschutz, P.,
Lin, W., Beydoun, H., Taylor, M., Bertagna, L., Bradley, A. M., Clevenger,
T. C., Donahue, A. S., Eldred, C., Foucar, J., Golaz, J. C., Guba, O.,
Jacob, R., Johnson, J., Krishna, J., Liu, W., Pressel, K., Salinger, A. G.,
Singh, B., Steyer, A., Ullrich, P., Wu, D., Yuan, X., Shpund, J., Ma, H. Y.,
and Zender, C. S.: Convection-Permitting Simulations With the E3SM Global
Atmosphere Model, J. Adv. Model. Earth Sy., 13, e2021MS002544,
https://doi.org/10.1029/2021MS002544, 2021.
Cheng, A. and Xu, K. M.: Simulation of shallow cumuli and their transition
to deep convective clouds by cloud-resolving models with different
third-order turbulence closures, Q. J. Roy. Meteor. Soc., 132, 359–382,
https://doi.org/10.1256/qj.05.29, 2006.
Cheng, A. and Xu, K. M.: Simulation of boundary-layer cumulus and
stratocumulus clouds using a cloud-resolving model with low- and third-order
turbulence closures, J. Meteorol. Soc. Japan, 86A, 67–86,
https://doi.org/10.2151/jmsj.86A.67, 2008.
Chinita, M.: Code for SHOC+MF_v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.7011628, 2022a.
Chinita, M.: Data for SHOC+MF_v1.0, Zenodo [data set], https://doi.org/10.5281/zenodo.7011652, 2022b.
Chinita, M. J., Matheou, G., and Teixeira, J.: A joint probability
density-based decomposition of turbulence in the atmospheric boundary layer,
Mon. Weather Rev., 146, 503–523, https://doi.org/10.1175/MWR-D-17-0166.1, 2018.
Chinita, M. J., Matheou, G., and Miranda, P. M. A.: Large-eddy simulation of
very stable boundary layers. Part I: Modeling methodology, Q. J. Roy. Meteor. Soc., 148, 1805–1823, https://doi.org/10.1002/qj.4279,
2022a.
Chinita, M. J., Matheou, G., and Miranda, P. M. A.: Large-eddy simulation of
very stable boundary layers. Part II: Length scales and anisotropy in
stratified atmospheric turbulence, Q. J. Roy. Meteor. Soc., 148, 1824–1839,
https://doi.org/10.1002/qj.4280, 2022b.
Chung, D. and Matheou, G.: Large-eddy simulation of stratified turbulence.
Part I: A vortex-based subgrid-scale model, J. Atmos. Sci., 71, 1863–1879,
https://doi.org/10.1175/JAS-D-13-0126.1, 2014.
Chung, D., Matheou, G., and Teixeira, J.: Steady-state large-eddy
simulations to study the stratocumulus to shallow cumulus cloud transition,
J. Atmos. Sci., 69, 3264–3276, https://doi.org/10.1175/JAS-D-11-0256.1,
2012.
Cohen, Y., Lopez-Gomez, I., Jaruga, A., He, J., Kaul, C. M., and Schneider,
T.: Unified Entrainment and Detrainment Closures for Extended
Eddy-Diffusivity Mass-Flux Schemes, J. Adv. Model. Earth Sy., 12,
e2020MS002162, https://doi.org/10.1029/2020MS002162, 2020.
Couvreux, F., Hourdin, F., and Rio, C.: Resolved versus parametrized
boundary-layer plumes. Part I: A parametrization-oriented conditional
sampling in large-eddy simulations, Bound.-Lay. Meteorol., 134, 441–458,
https://doi.org/10.1007/s10546-009-9456-5, 2010.
Couvreux, F., Bazile, E., Rodier, Q., Maronga, B., Matheou, G., Chinita, M.
J., Edwards, J., van Stratum, B. J. H., van Heerwaarden, C. C., Huang, J.,
Moene, A. F., Cheng, A., Fuka, V., Basu, S., Bou-Zeid, E., Canut, G., and
Vignon, E.: Intercomparison of Large-Eddy Simulations of the Antarctic
Boundary Layer for Very Stable Stratification, Bound.-Lay. Meteorol.,
176, 369–400, https://doi.org/10.1007/s10546-020-00539-4, 2020.
Deardorff, J. W.: The Counter-Gradient Heat Flux in the Lower Atmosphere and
in the Laboratory, J. Atmos. Sci., 23, 503–506, https://doi.org/10.1175/1520-0469(1966)023<0503:tcghfi>2.0.co;2, 1966.
E3SM Project, DOE: Energy Exascale Earth System Model v2.0. (Computer Software), DOE [software], https://doi.org/10.11578/E3SM/dc.20210927.1, 2021.
Firl, G. J. and Randall, D. A.: Fitting and analyzing les using multiple
trivariate Gaussians, J. Atmos. Sci., 72, 1094–1116,
https://doi.org/10.1175/JAS-D-14-0192.1, 2015.
Fitch, A. C.: An improved double-Gaussian closure for the subgrid vertical
velocity probability distribution function, J. Atmos. Sci., 76, 285–304,
https://doi.org/10.1175/JAS-D-18-0149.1, 2019.
Golaz, J. C., Larson, V. E., and Cotton, W. R.: A PDF-based model for
boundary layer clouds. Part I: Method and model description, J. Atmos. Sci.,
59, 3540–3551, https://doi.org/10.1175/1520-0469(2002)059<3540:APBMFB>2.0.CO;2, 2002.
Golaz, J. C., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q.,
Wolfe, J. D., Abeshu, G., Anantharaj, V., Asay-Davis, X. S., Bader, D. C.,
Baldwin, S. A., Bisht, G., Bogenschutz, P. A., Branstetter, M., Brunke, M.
A., Brus, S. R., Burrows, S. M., Cameron-Smith, P. J., Donahue, A. S.,
Deakin, M., Easter, R. C., Evans, K. J., Feng, Y., Flanner, M., Foucar, J.
G., Fyke, J. G., Griffin, B. M., Hannay, C., Harrop, B. E., Hoffman, M. J.,
Hunke, E. C., Jacob, R. L., Jacobsen, D. W., Jeffery, N., Jones, P. W.,
Keen, N. D., Klein, S. A., Larson, V. E., Leung, L. R., Li, H. Y., Lin, W.,
Lipscomb, W. H., Ma, P. L., Mahajan, S., Maltrud, M. E., Mametjanov, A.,
McClean, J. L., McCoy, R. B., Neale, R. B., Price, S. F., Qian, Y., Rasch,
P. J., Reeves Eyre, J. E. J., Riley, W. J., Ringler, T. D., Roberts, A. F.,
Roesler, E. L., Salinger, A. G., Shaheen, Z., Shi, X., Singh, B., Tang, J.,
Taylor, M. A., Thornton, P. E., Turner, A. K., Veneziani, M., Wan, H., Wang,
H., Wang, S., Williams, D. N., Wolfram, P. J., Worley, P. H., Xie, S., Yang,
Y., Yoon, J. H., Zelinka, M. D., Zender, C. S., Zeng, X., Zhang, C., Zhang,
K., Zhang, Y., Zheng, X., Zhou, T., and Zhu, Q.: The DOE E3SM Coupled Model
Version 1: Overview and Evaluation at Standard Resolution, J. Adv. Model. Earth Sy., 11, 2089–2129, https://doi.org/10.1029/2018MS001603, 2019.
Han, J. and Bretherton, C. S.: TKE-based moist eddy-diffusivity mass-flux
(EDMF) parameterization for vertical turbulent mixing, Weather Forecast.,
34, 869–886, https://doi.org/10.1175/WAF-D-18-0146.1, 2019.
Han, J. and Pan, H. L.: Revision of convection and vertical diffusion
schemes in the NCEP Global Forecast System, Weather Forecast., 26, 520–533,
https://doi.org/10.1175/WAF-D-10-05038.1, 2011.
Han, J., Witek, M. L., Teixeira, J., Sun, R., Pan, H. L., Fletcher, J. K.,
and Bretherton, C. S.: Implementation in the NCEP GFS of a hybrid
eddy-diffusivity mass-flux (EDMF) boundary layer parameterization with
dissipative heating and modified stable boundary layer mixing, Weather
Forecast., 31, 341–352, https://doi.org/10.1175/WAF-D-15-0053.1, 2016.
Holtslag, A. A. M. and Boville, B. A.: Local versus nonlocal boundary-layer
diffusion in a global climate model, J. Climate, 6, 1825–1842,
https://doi.org/10.1175/1520-0442(1993)006<1825:LVNBLD>2.0.CO;2, 1993.
Holtslag, A. A. M. and Moeng, C.-H.: Eddy diffusivity and countergradient
transport in the convective atmospheric boundary layer, J. Atmos. Sci., 48, 1690–1698,
https://doi.org/10.1175/1520-0469(1991)048<1690:EDACTI>2.0.CO;2, 1991.
Kohler, M., Ahlgrimm, M., and Beljaars, A.: Unified treatment of dry
convective and stratocumulus-topped boundary layers in the ECMWF model, Q. J. Roy. Meteor. Soc., 137, 43–57, https://doi.org/10.1002/qj.713, 2011.
Kurowski, M. J., Suselj, K., and Grabowski, W. W.: Is Shallow Convection
Sensitive to Environmental Heterogeneities?, Geophys. Res. Lett., 46,
1785–1793, https://doi.org/10.1029/2018GL080847, 2019a.
Kurowski, M. J., Thrastarson, H. T., Suselj, K., and Teixeira, J.: Towards
unifying the planetary boundary layer and shallow convection in CAM5 with
the eddy-diffusivity/mass-flux approach, Atmosphere, 10, 484,
https://doi.org/10.3390/atmos10090484, 2019b.
Lamaakel, O. and Matheou, G.: Galilean invariance of shallow cumulus
convection large-eddy simulations, J. Comput. Phys., 427, 110012,
https://doi.org/10.1016/j.jcp.2020.110012, 2021.
Matheou, G.: Turbulence Structure in a Stratocumulus Cloud, Atmosphere, 9, 392,
https://doi.org/10.3390/atmos9100392, 2018.
Matheou, G. and Chung, D.: Large-eddy simulation of stratified turbulence.
Part II: Application of the stretched-vortex model to the atmospheric
boundary layer, J. Atmos. Sci., 71, 4439–4460,
https://doi.org/10.1175/JAS-D-13-0306.1, 2014.
Matheou, G. and Teixeira, J.: Sensitivity to physical and numerical aspects
of large-eddy simulation of stratocumulus, Mon. Weather Rev., 147,
2621–2639, https://doi.org/10.1175/MWR-D-18-0294.1, 2019.
Matheou, G., Chung, D., and Teixeira, J.: On the synergy between numerics
and subgrid scale modeling in LES of stratified flows: Grid convergence of a
stratocumulus-topped boundary layer., in: Eighth Int. Symp. on Stratified Flows, Vol. 1, San Diego,
CA, NASA Jet Propulsion Laboratory, http://hdl.handle.net/2014/46171 (last access: 20 March 2023), 2016.
Morinishi, Y., Lund, T. S., Vasilyev, O. V, and Moin, P.: Fully Conservative
Higher Order Finite Difference Schemes for Incompressible Flow, J. Comput.
Phys., 143, 90–124, https://doi.org/10.1006/jcph.1998.5962,
1998.
Neggers, R. A. J.: A dual mass flux framework for boundary layer convection.
Part II: Clouds, J. Atmos. Sci., 66, 1489–1506,
https://doi.org/10.1175/2008JAS2636.1, 2009.
Olson, J. B., Kenyon, J. S., Angevine, W. A., Brown, J. M., Pagowski, M.,
and Sušelj, K.: A Description of the MYNN-EDMF Scheme and the Coupling
to Other Components in WRF–ARW, NOAA Technical Memorandum OAR GSD-61,
https://doi.org/10.25923/n9wm-be49, 2019.
Richtmyer, R. and Morton, K.: Difference methods for initial value
problems, 2nd edn., Wiley-Interscience, New York, 405 pp., 1967.
Rio, C. and Hourdin, F.: A thermal plume model for the convective boundary
layer: Representation of cumulus clouds, J. Atmos. Sci., 65, 407–425,
https://doi.org/10.1175/2007JAS2256.1, 2008.
Romps, D. M. and Kuang, Z.: Nature versus nurture in shallow convection, J.
Atmos. Sci., 67, 1655–1666, https://doi.org/10.1175/2009JAS3307.1, 2010.
Schneider, T., Teixeira, J., Bretherton, C. S., Brient, F., Pressel, K. G.,
Schär, C., and Siebesma, A. P.: Climate goals and computing the future
of clouds, Nat. Clim. Change, 7, 3–5, https://doi.org/10.1038/nclimate3190,
2017.
Sherwood, S. C., Bony, S., and Dufresne, J. L.: Spread in model climate
sensitivity traced to atmospheric convective mixing, Nature, 505, 37–42,
https://doi.org/10.1038/nature12829, 2014.
Siebesma, A., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J.,
Duynkerke, P. G., Jiang, H., Khairoutdinov, M., Lewellen, D., Moeng, C. H.,
Sanchez, E., Stevens, B., and Stevens, D. E.: A large eddy simulation
intercomparison study of shallow cumulus convection, J. Atmos. Sci., 60,
1201–1219, https://doi.org/10.1175/1520-0469(2003)60<1201:ALESIS>2.0.CO;2, 2003.
Siebesma, A. P. and Cuijpers, J. W. M.: Evaluation of parametric assumptions
for shallow cumulus convection, J. Atmos. Sci., 52, 650–666,
https://doi.org/10.1175/1520-0469(1995)052<0650:EOPAFS>2.0.CO;2, 1995.
Siebesma, A. P., Soares, P. M. M., and Teixeira, J.: A combined
eddy-diffusivity mass-flux approach for the convective boundary layer, J.
Atmos. Sci., 64, 1230–1248, https://doi.org/10.1175/JAS3888.1, 2007.
Siebesma, P. and Teixeira, J.: An advection-diffusion scheme for the
convective boundary layer: Description and 1D-results, in: Proc. 14th Symp. on Boundary Layers and Turbulence, Aspen, CO,
Amer. Meteor. Soc., 133–136, 2000.
Soares, P. M. M., Miranda, P. M. A., Siebesma, A. P., and Teixeira, J.: An
eddy-diffusivity/mass-flux parametrization for dry and shallow cumulus
convection, Q. J. Roy. Meteor. Soc., 130, 3365–3383,
https://doi.org/10.1256/qj.03.223, 2004.
Stevens, B.: Quasi-steady analysis of a PBL model with an Eddy-diffusivity
profile and nonlocal fluxes, Mon. Weather Rev., 128, 824–836,
https://doi.org/10.1175/1520-0493(2000)128<0824:QSAOAP>2.0.CO;2, 2000.
Suselj, K., Teixeira, J., and Chung, D.: A unified model for moist
convective boundary layers based on a stochastic eddy-diffusivity/mass-flux
parameterization, J. Atmos. Sci., 70, 1929–1953,
https://doi.org/10.1175/JAS-D-12-0106.1, 2013.
Suselj, K., Hogan, T. F., and Teixeira, J.: Implementation of a stochastic
eddy-diffusivity/mass-flux parameterization into the Navy Global
environmental model, Weather Forecast., 29, 1374–1390,
https://doi.org/10.1175/WAF-D-14-00043.1, 2014.
Suselj, K., Kurowski, M. J., and Teixeira, J.: A unified
eddy-diffusivity/mass-flux approach for modeling atmospheric convection, J.
Atmos. Sci., 76, 2505–2537, https://doi.org/10.1175/JAS-D-18-0239.1, 2019a.
Suselj, K., Kurowski, M. J., and Teixeira, J.: On the factors controlling
the development of shallow convection in eddy-diffusivity/mass-flux models,
J. Atmos. Sci., 76, 433–456, https://doi.org/10.1175/JAS-D-18-0121.1,
2019b.
Suselj, K., Teixeira, J., Kurowski, M. J., and Molod, A.: Improving the
representation of subtropical boundary layer clouds in the NASA GEOS model
with the eddy-diffusivity/mass-flux parameterization, Mon. Weather Rev.,
149, 793–809, https://doi.org/10.1175/MWR-D-20-0183.1, 2021.
Takahashi, H., Luo, Z. J., and Stephens, G.: Revisiting the Entrainment
Relationship of Convective Plumes: A Perspective From Global Observations,
Geophys. Res. Lett., 48, e2020GL092349, https://doi.org/10.1029/2020GL092349, 2021.
Tan, Z., Kaul, C. M., Pressel, K. G., Cohen, Y., Schneider, T., and
Teixeira, J.: An Extended Eddy-Diffusivity Mass-Flux Scheme for Unified
Representation of Subgrid-Scale Turbulence and Convection, J. Adv. Model. Earth Sy., 10, 770–800,
https://doi.org/10.1002/2017MS001162, 2018.
Teixeira, J. and Cheinet, S.: A simple mixing length formulation for the
eddy-diffusivity parameterization of dry convection, Bound.-Lay. Meteorol., 110, 435–453,
https://doi.org/10.1023/B:BOUN.0000007230.96303.0d, 2004.
Teixeira, J. and Siebesma, P.: A mass flux/K-diffusion approach to the
parameterization of the convective boundary layer: Global model results,
in: Proc. 14th Symp. on Boundary Layers and Turbulence, Aspen, CO,
Amer. Meteor. Soc., 231–234, 2000.
Teixeira, J., Ferreira, J. P., Miranda, P. M. A., Haack, T., Doyle, J.,
Siebsema, A. P., and Salgado, R.: A new mixing-length formulation for the
parameterization of dry convection: Implementation and evaluation in
mesoscale model, Mon. Weather Rev., 132, 2698–2707,
https://doi.org/10.1175/MWR2808.1, 2004.
Teixeira, J., Stevens, B., Bretherton, C. S., Cederwall, R., Doyle, J. D.,
Golaz, J. C., Holtslag, A. A. M., Klein, S. A., Lundquist, J. K., Randall,
D. A., Siebesma, A. P., and Soares, P. M. M.: Parameterization of the
atmospheric boundary layer: A view from just above the inversion, B. Am.
Meteorol. Soc., 89, 453–458, https://doi.org/10.1175/BAMS-89-4-453, 2008.
Tiedtke, M.: A Comprehensive Mass Flux Scheme for Cumulus Parameterization
in Large-Scale Models, Mon. Weather Rev., 117, 1779–1800, 1989.
Witek, M. L., Teixeira, J., and Matheou, G.: An Integrated TKE-based eddy
diffusivity/mass flux boundary layer closure for the dry convective boundary
layer, J. Atmos. Sci., 68, 1526–1540,
https://doi.org/10.1175/2011JAS3548.1, 2011.
Witte, M. K., Herrington, A., Teixeira, J., Kurowski, M., Chinita, M. J.,
Storer, R. L., Suselj, K., Matheou, G., and Bacmeister, J.: Augmenting the
double-Gaussian representation of atmospheric turbulence and convection via
a coupled stochastic multi-plume mass flux scheme, Mon. Weather Rev., 150, 2339–2355,
https://doi.org/10.1175/MWR-D-21-0215.1, 2022.
Wu, E., Yang, H., Kleissl, J., Suselj, K., Kurowski, M. J., and Teixeira,
J.: On the parameterization of convective downdrafts for marine
stratocumulus clouds, Mon. Weather Rev., 148, 1931–1950,
https://doi.org/10.1175/MWR-D-19-0292.1, 2020.
Yoshimura, H., Mizuta, R., and Murakami, H.: A spectral cumulus
parameterization scheme interpolating between two convective updrafts with
semi-lagrangian calculation of transport by compensatory subsidence, Mon.
Weather Rev., 143, 597–621, https://doi.org/10.1175/MWR-D-14-00068.1, 2015.
Short summary
Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper,...
