Articles | Volume 16, issue 13
https://doi.org/10.5194/gmd-16-3953-2023
© 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-16-3953-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
13 Jul 2023
Model description paper |
| 13 Jul 2023
| 13 Jul 2023
The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results
Lawrence Livermore National Laboratory, Livermore, CA, USA
Jean-Christophe Golaz
Lawrence Livermore National Laboratory, Livermore, CA, USA
Luke P. Van Roekel
Los Alamos National Laboratory, Los Alamos, NM, USA
Mark A. Taylor
Sandia National Laboratories, Albuquerque, NM, USA
Wuyin Lin
Brookhaven National Laboratory, Upton, NY, USA
Benjamin R. Hillman
Sandia National Laboratories, Albuquerque, NM, USA
Paul A. Ullrich
Department of Land, Air and Water Resources, University of California, Davis, CA, USA
Andrew M. Bradley
Sandia National Laboratories, Albuquerque, NM, USA
Oksana Guba
Sandia National Laboratories, Albuquerque, NM, USA
Jonathan D. Wolfe
Los Alamos National Laboratory, Los Alamos, NM, USA
Tian Zhou
Pacific Northwest National Laboratory, Richland, WA, USA
Kai Zhang
Pacific Northwest National Laboratory, Richland, WA, USA
Xue Zheng
Lawrence Livermore National Laboratory, Livermore, CA, USA
Yunyan Zhang
Lawrence Livermore National Laboratory, Livermore, CA, USA
Meng Zhang
Lawrence Livermore National Laboratory, Livermore, CA, USA
Mingxuan Wu
Pacific Northwest National Laboratory, Richland, WA, USA
Hailong Wang
Pacific Northwest National Laboratory, Richland, WA, USA
Cheng Tao
Lawrence Livermore National Laboratory, Livermore, CA, USA
Balwinder Singh
Pacific Northwest National Laboratory, Richland, WA, USA
Alan M. Rhoades
Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Lawrence Livermore National Laboratory, Livermore, CA, USA
Hong-Yi Li
Department of Civil and Environmental Engineering, University of Houston, TX, USA
Argonne National Laboratory, Lemont, IL, USA
Yuying Zhang
Lawrence Livermore National Laboratory, Livermore, CA, USA
Chengzhu Zhang
Lawrence Livermore National Laboratory, Livermore, CA, USA
Charles S. Zender
Departments of Earth System Science and Computer Science, University of California, Irvine, CA, USA
Shaocheng Xie
Lawrence Livermore National Laboratory, Livermore, CA, USA
Erika L. Roesler
Sandia National Laboratories, Albuquerque, NM, USA
Andrew F. Roberts
Los Alamos National Laboratory, Los Alamos, NM, USA
Azamat Mametjanov
Argonne National Laboratory, Lemont, IL, USA
Mathew E. Maltrud
Los Alamos National Laboratory, Los Alamos, NM, USA
Noel D. Keen
Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Robert L. Jacob
Argonne National Laboratory, Lemont, IL, USA
Christiane Jablonowski
Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
Owen K. Hughes
Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
Ryan M. Forsyth
Lawrence Livermore National Laboratory, Livermore, CA, USA
Alan V. Di Vittorio
Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Peter M. Caldwell
Lawrence Livermore National Laboratory, Livermore, CA, USA
Gautam Bisht
Pacific Northwest National Laboratory, Richland, WA, USA
Renata B. McCoy
Lawrence Livermore National Laboratory, Livermore, CA, USA
L. Ruby Leung
Pacific Northwest National Laboratory, Richland, WA, USA
David C. Bader
Lawrence Livermore National Laboratory, Livermore, CA, USA
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Cited
23 citations as recorded by crossref.
- Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model T. Hassan et al.
- U-Surf: a global 1 km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling Y. Cheng et al.
- Present-day correlations are insufficient to predict cloud albedo change by anthropogenic aerosols in E3SM v2 N. Mahfouz et al.
- Using multiple high-resolution datasets to benchmark the energy exascale earth system model (E3SM) for renewable resource assessment H. Lee et al.
- Improved subseasonal-to-seasonal precipitation prediction of climate models with nudging approach for better initialization of Tibetan Plateau-Rocky Mountain Circumglobal wave train and land surface conditions Y. Qin et al.
- The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales K. Smith et al.
- Storylines for the 1997 New Year’s Flood: The role of watershed antecedent conditions and future warming in shaping discharge in the Truckee River watershed G. Yu et al.
- Future implications of enhanced hydroclimate variability and reduced snowpack on California’s water resources A. Beltran-Peña et al.
- CondensNet: enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints X. Wang et al.
- Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0 J. Zhang et al.
- Understanding changes in cloud simulations from E3SM version 1 to version 2 Y. Zhang et al.
- Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0 P. Bogenschutz et al.
- Systematic evaluation of atmospheric forcing, surface datasets, and mesh effects on kilometer-scale land surface and river modeling L. Li et al.
- Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis Q. Yang et al.
- Evolution and prospects of Earth system models: Challenges and opportunities X. Pan et al.
- Evaluating probabilistic deep learning methods for uncertainty quantification of temperature downscaling Y. Lops et al.
- Continental United States climate projections based on thermodynamic modification of historical weather A. Jones et al.
- Changing windstorm characteristics over the US Northeast in a single model large ensemble J. Coburn et al.
- High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future R. Arthur et al.
- A seamless approach for evaluating climate models across spatial scales A. Chang et al.
- Zooming in: SCREAM at 100 m using regional refinement over the San Francisco Bay Area J. Zhang et al.
- Assessment of Climate Change Impacts on Renewable Energy Resources in Western North America H. Lee et al.
- Modeling climate change impacts on urban population exposure to heat stress dynamics in Vancouver and Victoria, Canada F. Azargoshasbi & L. Minet
23 citations as recorded by crossref.
- Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model T. Hassan et al.
- U-Surf: a global 1 km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling Y. Cheng et al.
- Present-day correlations are insufficient to predict cloud albedo change by anthropogenic aerosols in E3SM v2 N. Mahfouz et al.
- Using multiple high-resolution datasets to benchmark the energy exascale earth system model (E3SM) for renewable resource assessment H. Lee et al.
- Improved subseasonal-to-seasonal precipitation prediction of climate models with nudging approach for better initialization of Tibetan Plateau-Rocky Mountain Circumglobal wave train and land surface conditions Y. Qin et al.
- The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales K. Smith et al.
- Storylines for the 1997 New Year’s Flood: The role of watershed antecedent conditions and future warming in shaping discharge in the Truckee River watershed G. Yu et al.
- Future implications of enhanced hydroclimate variability and reduced snowpack on California’s water resources A. Beltran-Peña et al.
- CondensNet: enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints X. Wang et al.
- Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0 J. Zhang et al.
- Understanding changes in cloud simulations from E3SM version 1 to version 2 Y. Zhang et al.
- Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0 P. Bogenschutz et al.
- Systematic evaluation of atmospheric forcing, surface datasets, and mesh effects on kilometer-scale land surface and river modeling L. Li et al.
- Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis Q. Yang et al.
- Evolution and prospects of Earth system models: Challenges and opportunities X. Pan et al.
- Evaluating probabilistic deep learning methods for uncertainty quantification of temperature downscaling Y. Lops et al.
- Continental United States climate projections based on thermodynamic modification of historical weather A. Jones et al.
- Changing windstorm characteristics over the US Northeast in a single model large ensemble J. Coburn et al.
- High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future R. Arthur et al.
- A seamless approach for evaluating climate models across spatial scales A. Chang et al.
- Zooming in: SCREAM at 100 m using regional refinement over the San Francisco Bay Area J. Zhang et al.
- Assessment of Climate Change Impacts on Renewable Energy Resources in Western North America H. Lee et al.
- Modeling climate change impacts on urban population exposure to heat stress dynamics in Vancouver and Victoria, Canada F. Azargoshasbi & L. Minet
Saved (final revised paper)
Latest update: 14 May 2026
Short summary
High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
High-resolution simulations are superior to low-resolution ones in capturing regional climate...
