Coupled Climate Simulations With E3SM‐MMF

Hannah, Walter M.; Mahajan, Salil; Harrop, Bryce E.; Liu, Nana; Peng, Liran; Pritchard, Michael S.; Hillman, Benjamin R.; Bader, David C.; Taylor, Mark A.

doi:10.1029/2025MS004935

Coupled Climate Simulations With E3SM‐MMF

Journal Article · Thu Sep 18 00:00:00 EDT 2025 · Journal of Advances in Modeling Earth Systems

DOI:https://doi.org/10.1029/2025MS004935· OSTI ID:2589915

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Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Univ. of Oklahoma, Norman, OK (United States)
Univ. of California, Irvine, CA (United States)
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Simulations of the recent historical period from 1950 to 2014 are conducted with E3SM‐MMF, which uses an embedded 2D cloud resolving model that runs efficiently on GPUs in place of traditional parameterizations for cloud and turbulence. Analysis of the climate and variability reveal several aspects where E3SM‐MMF produces smaller biases compared to E3SMv2, including better agreement with the observed evolution of global mean surface temperature, although the representation of ENSO is too weak and fast. Three idealized abrupt CO₂ experiments were also conducted to assess climate sensitivity and feedbacks. These yield three estimates of effective climate sensitivity (4.38, 5.21, and 6.06 K), with a corresponding spread in the shortwave cloud feedbacks. These estimates are on the higher end of sensitivity estimates from CMIP ensembles, and the spread indicates substantial state‐dependent feedbacks. These results demonstrate how multiscale modeling framework (MMF) models can be used for climate relevant experiments and projections by leveraging modern GPU enabled computational platforms. The unique qualities of E3SM‐MMF shown in previous literature are largely still present, but various instances of reduced biases suggest that MMF models have utility in improving future projections.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), Biological and Environmental Research (BER); National Energy Research Scientific Computing Center (NERSC)

Grant/Contract Number:: AC52-07NA27344; NA0003525; AC05-00OR22725; AC02-05CH11231; AC05-76RL01830

OSTI ID:: 2589915

Report Number(s):: LLNL--JRNL-2011187

Journal Information:: Journal of Advances in Modeling Earth Systems, Journal Name: Journal of Advances in Modeling Earth Systems Journal Issue: 9 Vol. 17; ISSN 1942-2466

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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