the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Fully Coupled Regionally Refined Model of E3SM Version 2: Overview of the Atmosphere, Land, and River
Jean-Christophe Golaz
Luke P. Roekel
Mark A. Taylor
Wuyin Lin
Benjamin R. Hillman
Paul A. Ullrich
Andrew M. Bradley
Oksana Guba
Jonathan D. Wolfe
Tian Zhou
Kai Zhang
Xue Zheng
Yunyan Zhang
Meng Zhang
Mingxuan Wu
Hailong Wang
Cheng Tao
Balwinder Singh
Alan M. Rhoades
Hong-Yi Li
Yuying Zhang
Chengzhu Zhang
Charles S. Zender
Shaocheng Xie
Erika L. Roesler
Andrew F. Roberts
Azamat Mametjanov
Mathew E. Maltrud
Noel D. Keen
Robert L. Jacob
Christiane Jablonowski
Owen K. Hughes
Ryan M. Forsyth
Alan V. Vittorio
Peter M. Caldwell
Gautam Bisht
Renata B. McCoy
L. Ruby Leung
David C. Bader
Abstract. This paper provides an overview of the United States (US) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2 (E3SMv2) fully coupled Regionally Refined Model (RRM) and documents the overall atmosphere, land, and river results from the Coupled Model Intercomparison Project 6 (CMIP6) DECK (Diagnosis, Evaluation, and Characterization of Klima) and historical simulations – a first-of-kind set of climate production simulations using RRM. The North American (NA) RRM (NARRM) is developed as the high-resolution configuration of E3SMv2 with the primary goal of more explicitly addressing DOE's mission needs regarding impacts to the US energy sector facing Earth system changes. The NARRM features finer horizontal resolution grids centered over NA, consisting of 25→100 km atmosphere and land, 0.125° river routing model, and 14→60 km ocean and sea ice. By design, the computational cost of NARRM is ∼3x of the uniform low-resolution (LR) model at 100 km but only ∼10–20 % of a globally uniform high-resolution model at 25 km.
A novel hybrid timestep strategy for the atmosphere is key for NARRM to achieve improved climate simulation fidelity within the high-resolution patch without sacrificing the overall global performance. The global climate, including climatology, time series, sensitivity, and feedback, is confirmed to be largely identical between NARRM and LR as quantified with typical climate metrics. Over the refined NA area, NARRM is generally superior to LR, including for precipitation and clouds over the contiguous US (CONUS), summertime marine stratocumulus clouds off the coast of California, liquid and ice phase clouds near the North polar region, extratropical cyclones, and spatial variability in land hydrological processes. The improvements over land are related to the better resolved topography in NARRM, whereas those over ocean are attributable to the improved air-sea interactions with finer grids for both atmosphere and ocean/sea ice. Some features appear insensitive to the resolution change analyzed here, for instance the diurnal propagation of organized mesoscale convective systems over CONUS, and the warm-season land-atmosphere coupling at the Southern Great Plains. In summary, our study presents a realistically efficient approach to leverage the RRM framework for a standard Earth system model release and high-resolution climate production simulations.
Qi Tang et al.
Status: final response (author comments only)
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CEC1: 'Comment on gmd-2022-262', Juan Antonio Añel, 12 Dec 2022
Dear authors,Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlYou have archived your code and data on GitHub. However, GitHub is not a suitable repository. GitHub itself instructs authors to use other alternatives for long-term archival and publishing, such as Zenodo. Therefore, please, publish your code in one of the appropriate repositories, and reply to this comment with the relevant information (link and DOI) as soon as possible, as it should be available for the Discussions stage. Also, please, include the relevant primary input/output data. In this way, you must include in a potentially reviewed version of your manuscript the modified 'Code and Data Availability' section, the DOI of the code (and another DOI for the dataset if necessary).Juan A. AñelGeosci. Model Dev. Exec. EditorCitation: https://doi.org/
10.5194/gmd-2022-262-CEC1 -
AC1: 'Reply on CEC1', Qi Tang, 12 Dec 2022
Dear Juan Añel,
Thanks for the suggests. The code and data used in this manuscript have been published in Zenodo (https://zenodo.org/record/7343230#.Y5dfluzMKDU) with DOI: 10.5281/zenodo.7343230. We will make sure to include this information in the revision.
Thanks,
Qi
Citation: https://doi.org/10.5194/gmd-2022-262-AC1
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AC1: 'Reply on CEC1', Qi Tang, 12 Dec 2022
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RC1: 'Comment on gmd-2022-262', Anonymous Referee #1, 12 Dec 2022
The comment was uploaded in the form of a supplement: https://gmd.copernicus.org/preprints/gmd-2022-262/gmd-2022-262-RC1-supplement.pdf
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RC2: 'Comment on gmd-2022-262', Anonymous Referee #2, 01 Feb 2023
The comment was uploaded in the form of a supplement: https://gmd.copernicus.org/preprints/gmd-2022-262/gmd-2022-262-RC2-supplement.pdf
Qi Tang et al.
Qi Tang et al.
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