TY - JOUR
T1 - E3SM-Arctic
T2 - Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions
AU - Huo, Yiling
AU - Wang, Hailong
AU - Veneziani, Milena
AU - Comeau, Darin
AU - Osinski, Robert
AU - Hillman, Benjamin R.
AU - Roesler, Erika
AU - Maslowski, Wieslaw
AU - Rasch, Philip J.
AU - Weijer, Wilbert
AU - Baxter, Ian
AU - Fu, Qiang
AU - Garuba, Oluwayemi A.
AU - Ma, Weiming
AU - Seefeldt, Mark W.
AU - Sweeney, Aodhan
AU - Wu, Mingxuan
AU - Zhang, Jing
AU - Zhang, Xiangdong
AU - Zhang, Yu
AU - Asay-Davis, Xylar
AU - Craig, Anthony P.
AU - Lee, Younjoo J.
AU - Lin, Wuyin
AU - Roberts, Andrew F.
AU - Wolfe, Jonathan D.
AU - Zhang, Shixuan
N1 - Publisher Copyright:
© 2025 Brookhaven Science Associates, LLC, Battelle Memorial Institute and The Author(s). Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union.
PY - 2025/6
Y1 - 2025/6
N2 - Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.
AB - Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.
KW - Arctic modeling
KW - Energy Exascale Earth System Model (E3SM)
KW - air-sea ice-ocean interactions
KW - radiative feedbacks
KW - regionally refined mesh
UR - https://www.scopus.com/pages/publications/105009295889
U2 - 10.1029/2024MS004726
DO - 10.1029/2024MS004726
M3 - Article
SN - 1942-2466
VL - 17
JO - Journal of Advances in Modeling Earth Systems
JF - Journal of Advances in Modeling Earth Systems
IS - 6
M1 - e2024MS004726
ER -