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Title: An Overview of the Atmospheric Component of the Energy Exascale Earth System Model

Abstract

The Energy Exascale Earth System Model Atmosphere Model version 1, the atmospheric component of the Department of Energy's Energy Exascale Earth System Model is described. The model began as a fork of the well-known Community Atmosphere Model, but it has evolved in new ways, and coding, performance, resolution, physical processes (primarily cloud and aerosols formulations), testing and development procedures now differ significantly. Vertical resolution was increased (from 30 to 72 layers), and the model top extended to 60 km (~0.1 hPa). A simple ozone photochemistry predicts stratospheric ozone, and the model now supports increased and more realistic variability in the upper troposphere and stratosphere. An optional improved treatment of light-absorbing particle deposition to snowpack and ice is available, and stronger connections with Earth system biogeochemistry can be used for some science problems. Satellite and ground-based cloud and aerosol simulators were implemented to facilitate evaluation of clouds, aerosols, and aerosol-cloud interactions. Higher horizontal and vertical resolution, increased complexity, and more predicted and transported variables have increased the model computational cost and changed the simulations considerably. These changes required development of alternate strategies for tuning and evaluation as it was not feasible to “brute force” tune the high-resolution configurations, so short-term hindcasts,more » perturbed parameter ensemble simulations, and regionally refined simulations provided guidance on tuning and parameterization sensitivity to higher resolution. A brief overview of the model and model climate is provided. Model fidelity has generally improved compared to its predecessors and the CMIP5 generation of climate models.« less

Authors:
ORCiD logo [1];  [2]; ORCiD logo [1]; ORCiD logo [3]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [4];  [5]; ORCiD logo [6]; ORCiD logo [7]; ORCiD logo [1] more »; ORCiD logo [4]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [7]; ORCiD logo [5]; ORCiD logo [7]; ORCiD logo [8]; ORCiD logo [5]; ORCiD logo [5]; ORCiD logo [9]; ORCiD logo [10]; ORCiD logo [2]; ORCiD logo [11]; ORCiD logo [4]; ORCiD logo [8]; ORCiD logo [12]; ORCiD logo [2]; ORCiD logo [13]; ORCiD logo [4]; ORCiD logo [1]; ORCiD logo [1] « less
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  3. Brookhaven National Lab. (BNL), Upton, NY (United States)
  4. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  5. National Center for Atmospheric Research, Boulder, CO (United States)
  6. Univ. of Wisconsin‐Milwaukee, Milwaukee, WI (United States). Dept. of Mathematical Sciences
  7. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  8. Argonne National Lab. (ANL), Lemont, IL (United States)
  9. Gwangju Inst. of Science and Technology, Gwangju (South Korea). Dept. of Earth System Science
  10. Univ. of California, Irvine, CA (United States). Dept. of Climate and Space Sciences and Engineering
  11. Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Climate and Space Sciences and Engineering
  12. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  13. Univ. of Wyoming, Laramie, WY (United States). Dept. of Atmospheric Science
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1567936
Alternate Identifier(s):
OSTI ID: 1567939; OSTI ID: 1569665; OSTI ID: 1572474
Report Number(s):
LLNL-JRNL-765204
Journal ID: ISSN 1942-2466; 955346
Grant/Contract Number:  
AC52-07NA27344; KP1703020; AC05‐76RL01830; NA0003525; AC52‐07NA27344; AC05‐00OR22725; AC02‐06CH11357; AC02‐05CH11231; AC02-06CH11357
Resource Type:
Published Article
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 11; Journal Issue: 8; Journal ID: ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; climate; climate modeling; Earth system; general circulation modeling; atmospheric model; climate change

Citation Formats

Rasch, P. J., Xie, S., Ma, P. ‐L., Lin, W., Wang, H., Tang, Q., Burrows, S. M., Caldwell, P., Zhang, K., Easter, R. C., Cameron‐Smith, P., Singh, B., Wan, H., Golaz, J. ‐C., Harrop, B. E., Roesler, E., Bacmeister, J., Larson, V. E., Evans, K. J., Qian, Y., Taylor, M., Leung, L. R., Zhang, Y., Brent, L., Branstetter, M., Hannay, C., Mahajan, S., Mametjanov, A., Neale, R., Richter, J. H., Yoon, J. ‐H., Zender, C. S., Bader, D., Flanner, M., Foucar, J. G., Jacob, R., Keen, N., Klein, S. A., Liu, X., Salinger, A. G., Shrivastava, M., and Yang, Y. An Overview of the Atmospheric Component of the Energy Exascale Earth System Model. United States: N. p., 2019. Web. doi:10.1029/2019MS001629.
Rasch, P. J., Xie, S., Ma, P. ‐L., Lin, W., Wang, H., Tang, Q., Burrows, S. M., Caldwell, P., Zhang, K., Easter, R. C., Cameron‐Smith, P., Singh, B., Wan, H., Golaz, J. ‐C., Harrop, B. E., Roesler, E., Bacmeister, J., Larson, V. E., Evans, K. J., Qian, Y., Taylor, M., Leung, L. R., Zhang, Y., Brent, L., Branstetter, M., Hannay, C., Mahajan, S., Mametjanov, A., Neale, R., Richter, J. H., Yoon, J. ‐H., Zender, C. S., Bader, D., Flanner, M., Foucar, J. G., Jacob, R., Keen, N., Klein, S. A., Liu, X., Salinger, A. G., Shrivastava, M., & Yang, Y. An Overview of the Atmospheric Component of the Energy Exascale Earth System Model. United States. doi:10.1029/2019MS001629.
Rasch, P. J., Xie, S., Ma, P. ‐L., Lin, W., Wang, H., Tang, Q., Burrows, S. M., Caldwell, P., Zhang, K., Easter, R. C., Cameron‐Smith, P., Singh, B., Wan, H., Golaz, J. ‐C., Harrop, B. E., Roesler, E., Bacmeister, J., Larson, V. E., Evans, K. J., Qian, Y., Taylor, M., Leung, L. R., Zhang, Y., Brent, L., Branstetter, M., Hannay, C., Mahajan, S., Mametjanov, A., Neale, R., Richter, J. H., Yoon, J. ‐H., Zender, C. S., Bader, D., Flanner, M., Foucar, J. G., Jacob, R., Keen, N., Klein, S. A., Liu, X., Salinger, A. G., Shrivastava, M., and Yang, Y. Tue . "An Overview of the Atmospheric Component of the Energy Exascale Earth System Model". United States. doi:10.1029/2019MS001629.
@article{osti_1567936,
title = {An Overview of the Atmospheric Component of the Energy Exascale Earth System Model},
author = {Rasch, P. J. and Xie, S. and Ma, P. ‐L. and Lin, W. and Wang, H. and Tang, Q. and Burrows, S. M. and Caldwell, P. and Zhang, K. and Easter, R. C. and Cameron‐Smith, P. and Singh, B. and Wan, H. and Golaz, J. ‐C. and Harrop, B. E. and Roesler, E. and Bacmeister, J. and Larson, V. E. and Evans, K. J. and Qian, Y. and Taylor, M. and Leung, L. R. and Zhang, Y. and Brent, L. and Branstetter, M. and Hannay, C. and Mahajan, S. and Mametjanov, A. and Neale, R. and Richter, J. H. and Yoon, J. ‐H. and Zender, C. S. and Bader, D. and Flanner, M. and Foucar, J. G. and Jacob, R. and Keen, N. and Klein, S. A. and Liu, X. and Salinger, A. G. and Shrivastava, M. and Yang, Y.},
abstractNote = {The Energy Exascale Earth System Model Atmosphere Model version 1, the atmospheric component of the Department of Energy's Energy Exascale Earth System Model is described. The model began as a fork of the well-known Community Atmosphere Model, but it has evolved in new ways, and coding, performance, resolution, physical processes (primarily cloud and aerosols formulations), testing and development procedures now differ significantly. Vertical resolution was increased (from 30 to 72 layers), and the model top extended to 60 km (~0.1 hPa). A simple ozone photochemistry predicts stratospheric ozone, and the model now supports increased and more realistic variability in the upper troposphere and stratosphere. An optional improved treatment of light-absorbing particle deposition to snowpack and ice is available, and stronger connections with Earth system biogeochemistry can be used for some science problems. Satellite and ground-based cloud and aerosol simulators were implemented to facilitate evaluation of clouds, aerosols, and aerosol-cloud interactions. Higher horizontal and vertical resolution, increased complexity, and more predicted and transported variables have increased the model computational cost and changed the simulations considerably. These changes required development of alternate strategies for tuning and evaluation as it was not feasible to “brute force” tune the high-resolution configurations, so short-term hindcasts, perturbed parameter ensemble simulations, and regionally refined simulations provided guidance on tuning and parameterization sensitivity to higher resolution. A brief overview of the model and model climate is provided. Model fidelity has generally improved compared to its predecessors and the CMIP5 generation of climate models.},
doi = {10.1029/2019MS001629},
journal = {Journal of Advances in Modeling Earth Systems},
number = 8,
volume = 11,
place = {United States},
year = {2019},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
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DOI: 10.1029/2019MS001629

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Cited by: 8 works
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  • Journal of Climate, Vol. 19, Issue 11
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A PDF-Based Model for Boundary Layer Clouds. Part I: Method and Model Description
journal, December 2002


Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS)
journal, January 2018

  • Hoesly, Rachel M.; Smith, Steven J.; Feng, Leyang
  • Geoscientific Model Development, Vol. 11, Issue 1
  • DOI: 10.5194/gmd-11-369-2018

Understanding Cloud and Convective Characteristics in Version 1 of the E3SM Atmosphere Model
journal, October 2018

  • Xie, Shaocheng; Lin, Wuyin; Rasch, Philip J.
  • Journal of Advances in Modeling Earth Systems, Vol. 10, Issue 10
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Evaluating adjusted forcing and model spread for historical and future scenarios in the CMIP5 generation of climate models: FORCING IN CMIP5 CLIMATE MODELS
journal, February 2013

  • Forster, Piers M.; Andrews, Timothy; Good, Peter
  • Journal of Geophysical Research: Atmospheres, Vol. 118, Issue 3
  • DOI: 10.1002/jgrd.50174

Impact of numerical choices on water conservation in the E3SM Atmosphere Model version 1 (EAMv1)
journal, January 2018

  • Zhang, Kai; Rasch, Philip J.; Taylor, Mark A.
  • Geoscientific Model Development, Vol. 11, Issue 5
  • DOI: 10.5194/gmd-11-1971-2018

Modeling the QBO-Improvements resulting from higher-model vertical resolution: MODELING THE QBO AND MODEL IMPROVEMENTS
journal, July 2016

  • Geller, Marvin A.; Zhou, Tiehan; Shindell, D.
  • Journal of Advances in Modeling Earth Systems, Vol. 8, Issue 3
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Improving the global precipitation record: GPCP Version 2.1
journal, January 2009

  • Huffman, George J.; Adler, Robert F.; Bolvin, David T.
  • Geophysical Research Letters, Vol. 36, Issue 17
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Sensitivity of Simulated Climate to Horizontal and Vertical Resolution in the ECHAM5 Atmosphere Model
journal, August 2006

  • Roeckner, E.; Brokopf, R.; Esch, M.
  • Journal of Climate, Vol. 19, Issue 16
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Arctic climate sensitivity to local black carbon: BLACK CARBON INFLUENCE ON ARCTIC CLIMATE
journal, February 2013

  • Flanner, Mark G.
  • Journal of Geophysical Research: Atmospheres, Vol. 118, Issue 4
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A standard test case suite for two-dimensional linear transport on the sphere: results from a collection of state-of-the-art schemes
journal, January 2014

  • Lauritzen, P. H.; Ullrich, P. A.; Jablonowski, C.
  • Geoscientific Model Development, Vol. 7, Issue 1
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A More Powerful Reality Test for Climate Models
journal, May 2016


Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750–2015)
journal, January 2017

  • van Marle, Margreet J. E.; Kloster, Silvia; Magi, Brian I.
  • Geoscientific Model Development, Vol. 10, Issue 9
  • DOI: 10.5194/gmd-10-3329-2017

Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)
journal, January 2018

  • Butchart, Neal; Anstey, James A.; Hamilton, Kevin
  • Geoscientific Model Development, Vol. 11, Issue 3
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Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling
journal, January 2019

  • Tang, Qi; Klein, Stephen A.; Xie, Shaocheng
  • Geoscientific Model Development, Vol. 12, Issue 7
  • DOI: 10.5194/gmd-12-2679-2019

Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations
journal, February 2001


Global-mean radiative feedbacks and forcing in atmosphere-only and coupled atmosphere-ocean climate change experiments
journal, June 2014

  • Ringer, Mark A.; Andrews, Timothy; Webb, Mark J.
  • Geophysical Research Letters, Vol. 41, Issue 11
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Observational constraints on mixed-phase clouds imply higher climate sensitivity
journal, April 2016


A physically based framework for modeling the organic fractionation of sea spray aerosol from bubble film Langmuir equilibria
journal, January 2014

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  • Atmospheric Chemistry and Physics, Vol. 14, Issue 24
  • DOI: 10.5194/acp-14-13601-2014

Stratospheric Control of the Madden–Julian Oscillation
journal, March 2017


Simulations of Arctic mixed-phase clouds in forecasts with CAM3 and AM2 for M-PACE
journal, January 2008

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  • Journal of Geophysical Research, Vol. 113, Issue D4
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A compatible and conservative spectral element method on unstructured grids
journal, August 2010


Mesoscale Dynamics
journal, January 2008

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Dependence of DMS global sea-air flux distribution on transfer velocity and concentration field type: DMS GLOBAL SEA-AIR FLUX DISTRIBUTION
journal, April 2009

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  • Journal of Geophysical Research: Biogeosciences, Vol. 114, Issue G2
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A “Vertically Lagrangian” Finite-Volume Dynamical Core for Global Models
journal, October 2004


The Community Earth System Model: A Framework for Collaborative Research
journal, September 2013

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  • Bulletin of the American Meteorological Society, Vol. 94, Issue 9
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The Role of Convective Gustiness in Reducing Seasonal Precipitation Biases in the Tropical West Pacific
journal, April 2018

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  • Journal of Advances in Modeling Earth Systems, Vol. 10, Issue 4
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Evaluating Parameterizations in General Circulation Models: Climate Simulation Meets Weather Prediction
journal, December 2004

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  • Bulletin of the American Meteorological Society, Vol. 85, Issue 12
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NCAR_Topo (v1.0): NCAR global model topography generation software for unstructured grids
journal, January 2015

  • Lauritzen, P. H.; Bacmeister, J. T.; Callaghan, P. F.
  • Geoscientific Model Development, Vol. 8, Issue 12
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Impact of horizontal resolution on climate model forecasts of tropical precipitation and diabatic heating for the TWP-ICE period
journal, January 2010

  • Boyle, James; Klein, Stephen A.
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Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models
journal, January 2008

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  • Journal of Geophysical Research, Vol. 113, Issue D13
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On the Correspondence between Mean Forecast Errors and Climate Errors in CMIP5 Models
journal, February 2014


Recommendations for diagnosing effective radiative forcing from climate models for CMIP6: RECOMMENDED EFFECTIVE RADIATIVE FORCING
journal, October 2016

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  • Journal of Geophysical Research: Atmospheres, Vol. 121, Issue 20
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A general circulation model simulation of the springtime Antarctic ozone decrease and its impact on mid-latitudes
journal, January 1990

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The Mathematical Theory of Frontogenesis
journal, January 1982


A parameterization of aerosol activation: 2. Multiple aerosol types
journal, March 2000

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  • Journal of Geophysical Research: Atmospheres, Vol. 105, Issue D5
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Using regime analysis to identify the contribution of clouds to surface temperature errors in weather and climate models: Cloud-Regime Analysis and Surface Temperature Errors
journal, September 2015

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  • Quarterly Journal of the Royal Meteorological Society, Vol. 141, Issue 693
  • DOI: 10.1002/qj.2603

Technical Note: Estimating aerosol effects on cloud radiative forcing
journal, January 2013


Parametric Sensitivity and Uncertainty Quantification in the Version 1 of E3SM Atmosphere Model Based on Short Perturbed Parameter Ensemble Simulations
journal, December 2018

  • Qian, Yun; Wan, Hui; Yang, Ben
  • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 23
  • DOI: 10.1029/2018JD028927

Processes controlling Southern Ocean shortwave climate feedbacks in CESM: CESM SOUTHERN OCEAN CLIMATE feedbacks
journal, January 2014

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Improved Diurnal Cycle of Precipitation in E3SM With a Revised Convective Triggering Function
journal, July 2019

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  • Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 7
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