Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-2881-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-2881-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
07 Apr 2022
Development and technical paper |
| 07 Apr 2022
| 07 Apr 2022
Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1
Pacific Northwest National Laboratory, Richland, Washington, USA
Bryce E. Harrop
Pacific Northwest National Laboratory, Richland, Washington, USA
Vincent E. Larson
Department of Mathematical Sciences, University of
Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
Pacific Northwest National Laboratory, Richland, Washington, USA
Richard B. Neale
National Center for Atmospheric Research, Boulder, Colorado, USA
Andrew Gettelman
National Center for Atmospheric Research, Boulder, Colorado, USA
Hugh Morrison
National Center for Atmospheric Research, Boulder, Colorado, USA
Hailong Wang
Pacific Northwest National Laboratory, Richland, Washington, USA
Kai Zhang
Pacific Northwest National Laboratory, Richland, Washington, USA
Stephen A. Klein
Lawrence Livermore National Laboratory, Livermore, California, USA
Mark D. Zelinka
Lawrence Livermore National Laboratory, Livermore, California, USA
Yuying Zhang
Lawrence Livermore National Laboratory, Livermore, California, USA
Yun Qian
Pacific Northwest National Laboratory, Richland, Washington, USA
Jin-Ho Yoon
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology, Gwangju, South Korea
Christopher R. Jones
Pacific Northwest National Laboratory, Richland, Washington, USA
Meng Huang
Pacific Northwest National Laboratory, Richland, Washington, USA
Sheng-Lun Tai
Pacific Northwest National Laboratory, Richland, Washington, USA
Balwinder Singh
Pacific Northwest National Laboratory, Richland, Washington, USA
Peter A. Bogenschutz
Lawrence Livermore National Laboratory, Livermore, California, USA
Xue Zheng
Lawrence Livermore National Laboratory, Livermore, California, USA
Wuyin Lin
Brookhaven National Laboratory, Upton, New York, USA
Johannes Quaas
Institute for Meteorology, Universität Leipzig, Leipzig, Germany
Hélène Chepfer
LMD/IPSL, Sorbonne Université, École Polytechnique, CNRS, Paris,
France
Michael A. Brunke
Department of Hydrology and Atmospheric Sciences, University of
Arizona, Tucson, Arizona, USA
Xubin Zeng
Department of Hydrology and Atmospheric Sciences, University of
Arizona, Tucson, Arizona, USA
Johannes Mülmenstädt
Pacific Northwest National Laboratory, Richland, Washington, USA
Samson Hagos
Pacific Northwest National Laboratory, Richland, Washington, USA
Zhibo Zhang
Department of Physics, University of Maryland, Baltimore County,
Baltimore, Maryland, USA
Science Systems and Applications, Inc., Lanham, Maryland, USA
Xiaohong Liu
Department of Atmospheric Sciences, Texas A&M University, College
Station, Texas, USA
Michael S. Pritchard
Department of Earth System Science, University of California, Irvine,
California, USA
Pacific Northwest National Laboratory, Richland, Washington, USA
Jingyu Wang
Department of Humanities and Social Studies Education, National Institute of Education, Nanyang Technological University, Singapore, Singapore
Lawrence Livermore National Laboratory, Livermore, California, USA
Peter M. Caldwell
Lawrence Livermore National Laboratory, Livermore, California, USA
Jiwen Fan
Pacific Northwest National Laboratory, Richland, Washington, USA
Larry K. Berg
Pacific Northwest National Laboratory, Richland, Washington, USA
Jerome D. Fast
Pacific Northwest National Laboratory, Richland, Washington, USA
Mark A. Taylor
Sandia National Laboratory, Albuquerque, New Mexico, USA
Jean-Christophe Golaz
Lawrence Livermore National Laboratory, Livermore, California, USA
Shaocheng Xie
Lawrence Livermore National Laboratory, Livermore, California, USA
Philip J. Rasch
Pacific Northwest National Laboratory, Richland, Washington, USA
L. Ruby Leung
Pacific Northwest National Laboratory, Richland, Washington, USA
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27 citations as recorded by crossref.
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- Stochastic paleoclimatology: Modeling the EPICA ice core climate records N. Keyes et al. 10.1063/5.0128814
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- A protocol for model intercomparison of impacts of marine cloud brightening climate intervention P. Rasch et al. 10.5194/gmd-17-7963-2024
- Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model Y. Qian et al. 10.1007/s00382-023-06977-3
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- Climate Base State Influences on South Asian Monsoon Processes Derived From Analyses of E3SMv2 and CESM2 G. Meehl et al. 10.1029/2023GL104313
- Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign S. Tang et al. 10.5194/acp-24-10073-2024
- An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1 B. Harrop et al. 10.5194/gmd-17-3111-2024
- Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals A. Varble et al. 10.5194/acp-23-13523-2023
- Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions C. Beall et al. 10.5194/acp-24-5287-2024
- Can general circulation models (GCMs) represent cloud liquid water path adjustments to aerosol–cloud interactions? J. Mülmenstädt et al. 10.5194/acp-24-13633-2024
- Causes of Reduced Climate Sensitivity in E3SM From Version 1 to Version 2 Y. Qin et al. 10.1029/2023MS003875
- Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations S. Tang et al. 10.5194/gmd-16-6355-2023
- Evaluation of aerosol–cloud interactions in E3SM using a Lagrangian framework M. Christensen et al. 10.5194/acp-23-2789-2023
- The Sensitivity of the Icosahedral Non-Hydrostatic Numerical Weather Prediction Model over Greece in Reference to Observations as a Basis towards Model Tuning E. Avgoustoglou et al. 10.3390/atmos14111616
- A new method for diagnosing effective radiative forcing from aerosol–cloud interactions in climate models B. Duran et al. 10.5194/acp-25-2123-2025
- The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation J. Golaz et al. 10.1029/2022MS003156
- Detection, attribution, and modeling of climate change: Key open issues N. Scafetta 10.1016/j.gr.2025.05.001
- Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation M. Bonazzola et al. 10.5194/gmd-16-1359-2023
- Wind Gustiness Parameterization and Long-range Weather Prediction R. Fadeev 10.3103/S1068373924130041
- Cloud Phase Simulation at High Latitudes in EAMv2: Evaluation Using CALIPSO Observations and Comparison With EAMv1 M. Zhang et al. 10.1029/2022JD037100
- Evaluating EAMv2 Simulated High Latitude Clouds Using ARM Measurements in the Northern and Southern Hemispheres M. Zhang et al. 10.1029/2022JD038364
- Effective radiative forcing of anthropogenic aerosols in E3SM version 1: historical changes, causality, decomposition, and parameterization sensitivities K. Zhang et al. 10.5194/acp-22-9129-2022
- Understanding changes in cloud simulations from E3SM version 1 to version 2 Y. Zhang et al. 10.5194/gmd-17-169-2024
- Volcanic aerosols lend causality to the indicated substantial susceptibility of clouds to aerosol over global oceans X. Wang et al. 10.1038/s41612-025-00974-5
2 citations as recorded by crossref.
- Aircraft Observations of Turbulence in Cloudy and Cloud‐Free Boundary Layers Over the Western North Atlantic Ocean From ACTIVATE and Implications for the Earth System Model Evaluation and Development M. Brunke et al. 10.1029/2022JD036480
- The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation J. Golaz et al. 10.1029/2022MS003156
Latest update: 20 Jul 2025
Short summary
An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based...
