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Title: Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling

Abstract

Climate simulations with more accurate process-level representation at finer resolutions (<100 km) are a pressing need in order to provide more detailed actionable information to policy makers regarding extreme events in a changing climate. Computational limitation is a major obstacle for building and running high-resolution (HR, here 0.25° average grid spacing at the Equator) models (HRMs). A more affordable path to HRMs is to use a global regionally refined model (RRM), which only simulates a portion of the globe at HR while the remaining is at low resolution (LR, 1°). In this study, we compare the Energy Exascale Earth System Model (E3SM) atmosphere model version 1 (EAMv1) RRM with the HR mesh over the contiguous United States (CONUS) to its corresponding globally uniform LR and HR configurations as well as to observations and reanalysis data. The RRM has a significantly reduced computational cost (roughly proportional to the HR mesh size) relative to the globally uniform HRM. Over the CONUS, we evaluate the simulation of important dynamical and physical quantities as well as various precipitation measures. Differences between the RRM and HRM over the HR region are predominantly small, demonstrating that the RRM reproduces the precipitation metrics of the HRM overmore » the CONUS. Further analysis based on RRM simulations with the LR vs. HR model parameters reveals that RRM performance is greatly influenced by the different parameter choices used in the LR and HR EAMv1. This is a result of the poor scale-aware behavior of physical parameterizations, especially for variables influencing sub-grid-scale physical processes. RRMs can serve as a useful framework to test physics schemes across a range of scales, leading to improved consistency in future E3SM versions. Applying nudging-to-observations techniques within the RRM framework also demonstrates significant advantages over a free-running configuration for use as a test bed and as such represents an efficient and more robust physics test bed capability. Our results provide additional confirmatory evidence that the RRM is an efficient and effective test bed for HRM development.« less

Authors:
ORCiD logo [1];  [1];  [1];  [2]; ORCiD logo [1];  [3]; ORCiD logo [3];  [4];  [1];  [4];  [1];  [2];  [5];  [4];  [4]; ORCiD logo [6];  [1];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  5. National Center for Atmospheric Research, Boulder, CO (United States)
  6. Univ. of California, Irvine, CA (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1544808
Alternate Identifier(s):
OSTI ID: 1526680; OSTI ID: 1542742; OSTI ID: 1631697
Report Number(s):
SAND-2019-7807J; BNL-211795-2019-JAAM; LLNL-JRNL-764721; PNNL-SA-141325
Journal ID: ISSN 1991-9603; 677219
Grant/Contract Number:  
AC04-94AL85000; SC0012704; AC52-07NA27344; A06-76RLO1830; AC02-05CH11231; AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Geoscientific Model Development (Online)
Additional Journal Information:
Journal Name: Geoscientific Model Development (Online); Journal Volume: 12; Journal Issue: 7; Journal ID: ISSN 1991-9603
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Tang, Qi, Klein, Stephen A., Xie, Shaocheng, Lin, Wuyin, Golaz, Jean -Christophe, Roesler, Erika L., Taylor, Mark A., Rasch, Philip J., Bader, David C., Berg, Larry K., Caldwell, Peter, Giangrande, Scott E., Neale, Richard B., Qian, Yun, Riihimaki, Laura D., Zender, Charles S., Zhang, Yuying, and Zheng, Xue. Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling. United States: N. p., 2019. Web. doi:10.5194/gmd-12-2679-2019.
Tang, Qi, Klein, Stephen A., Xie, Shaocheng, Lin, Wuyin, Golaz, Jean -Christophe, Roesler, Erika L., Taylor, Mark A., Rasch, Philip J., Bader, David C., Berg, Larry K., Caldwell, Peter, Giangrande, Scott E., Neale, Richard B., Qian, Yun, Riihimaki, Laura D., Zender, Charles S., Zhang, Yuying, & Zheng, Xue. Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling. United States. https://doi.org/10.5194/gmd-12-2679-2019
Tang, Qi, Klein, Stephen A., Xie, Shaocheng, Lin, Wuyin, Golaz, Jean -Christophe, Roesler, Erika L., Taylor, Mark A., Rasch, Philip J., Bader, David C., Berg, Larry K., Caldwell, Peter, Giangrande, Scott E., Neale, Richard B., Qian, Yun, Riihimaki, Laura D., Zender, Charles S., Zhang, Yuying, and Zheng, Xue. Mon . "Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling". United States. https://doi.org/10.5194/gmd-12-2679-2019. https://www.osti.gov/servlets/purl/1544808.
@article{osti_1544808,
title = {Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling},
author = {Tang, Qi and Klein, Stephen A. and Xie, Shaocheng and Lin, Wuyin and Golaz, Jean -Christophe and Roesler, Erika L. and Taylor, Mark A. and Rasch, Philip J. and Bader, David C. and Berg, Larry K. and Caldwell, Peter and Giangrande, Scott E. and Neale, Richard B. and Qian, Yun and Riihimaki, Laura D. and Zender, Charles S. and Zhang, Yuying and Zheng, Xue},
abstractNote = {Climate simulations with more accurate process-level representation at finer resolutions (<100 km) are a pressing need in order to provide more detailed actionable information to policy makers regarding extreme events in a changing climate. Computational limitation is a major obstacle for building and running high-resolution (HR, here 0.25° average grid spacing at the Equator) models (HRMs). A more affordable path to HRMs is to use a global regionally refined model (RRM), which only simulates a portion of the globe at HR while the remaining is at low resolution (LR, 1°). In this study, we compare the Energy Exascale Earth System Model (E3SM) atmosphere model version 1 (EAMv1) RRM with the HR mesh over the contiguous United States (CONUS) to its corresponding globally uniform LR and HR configurations as well as to observations and reanalysis data. The RRM has a significantly reduced computational cost (roughly proportional to the HR mesh size) relative to the globally uniform HRM. Over the CONUS, we evaluate the simulation of important dynamical and physical quantities as well as various precipitation measures. Differences between the RRM and HRM over the HR region are predominantly small, demonstrating that the RRM reproduces the precipitation metrics of the HRM over the CONUS. Further analysis based on RRM simulations with the LR vs. HR model parameters reveals that RRM performance is greatly influenced by the different parameter choices used in the LR and HR EAMv1. This is a result of the poor scale-aware behavior of physical parameterizations, especially for variables influencing sub-grid-scale physical processes. RRMs can serve as a useful framework to test physics schemes across a range of scales, leading to improved consistency in future E3SM versions. Applying nudging-to-observations techniques within the RRM framework also demonstrates significant advantages over a free-running configuration for use as a test bed and as such represents an efficient and more robust physics test bed capability. Our results provide additional confirmatory evidence that the RRM is an efficient and effective test bed for HRM development.},
doi = {10.5194/gmd-12-2679-2019},
journal = {Geoscientific Model Development (Online)},
number = 7,
volume = 12,
place = {United States},
year = {Mon Jul 08 00:00:00 EDT 2019},
month = {Mon Jul 08 00:00:00 EDT 2019}
}

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