Using a two-stage Rosenbrock solver to increase computational efficiency in the DOE's Exascale Earth System Model version 1 (E3SMv1)

Abstract. The integration of stiff atmospheric chemical systems is a major computational cost in Earth System Models and poses challenges for numerical stability and scalability as chemical complexity and temporal resolution increase. Current implementations commonly rely on fully implicit Newton–Raphson-based solvers, which are robust but computationally expensive. In this study, we implement a semi-implicit two-stage Rosenbrock method (ROS2) in the Energy Exascale Earth System Model version 1 (E3SMv1) and evaluate its performance as an alternative chemistry time-integration scheme. The ROS2 solver is applied to two interactive chemical mechanisms of differing stiffness and size: chemUCI (60 prognostic species) and trop_strat_mozart_mam4 (155 prognostic species). Numerical experiments include short simulations to quantify computational cost and year-long integrations to assess numerical stability, solution consistency, and long-term behavior. Solver performance is evaluated under identical model configurations and timesteps. At a 180-second timestep, ROS2 reduces chemistry integration cost by approximately 33 % relative to the default implicit solver. Differences in global mean surface ozone concentrations are small (≤1.03 ppb), and no systematic drift or degradation in numerical stability is observed over one-year simulations. These results indicate that low-order Rosenbrock methods provide a computationally efficient and numerically stable alternative for stiff atmospheric chemistry integration in E3SMv1. The implementation offers a flexible framework for future model configurations with increased chemical complexity and resolution.

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Publication Details

Journal
Geoscientific model development
Published
2026-10-29
DOI
https://doi.org/10.5194/gmd-19-10309-2026
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
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article

Using a two-stage Rosenbrock solver to increase computational efficiency in the DOE's Exascale Earth System Model version 1 (E3SMv1)

Rong‐You Chien, Joshua S. Fu
2 links
Geoscientific model development
Atmospheric chemistry and aerosols
article

Using a two-stage Rosenbrock solver to increase computational efficiency in the DOE's Exascale Earth System Model version 1 (E3SMv1)

Rong‐You Chien, Joshua S. Fu
article en

Abstract

Abstract. The integration of stiff atmospheric chemical systems is a major computational cost in Earth System Models and poses challenges for numerical stability and scalability as chemical complexity and temporal resolution increase. Current implementations commonly rely on fully implicit Newton–Raphson-based solvers, which are robust but computationally expensive. In this study, we implement a semi-implicit two-stage Rosenbrock method (ROS2) in the Energy Exascale Earth System Model version 1 (E3SMv1) and evaluate its performance as an alternative chemistry time-integration scheme. The ROS2 solver is applied to two interactive chemical mechanisms of differing stiffness and size: chemUCI (60 prognostic species) and trop_strat_mozart_mam4 (155 prognostic species). Numerical experiments include short simulations to quantify computational cost and year-long integrations to assess numerical stability, solution consistency, and long-term behavior. Solver performance is evaluated under identical model configurations and timesteps. At a 180-second timestep, ROS2 reduces chemistry integration cost by approximately 33 % relative to the default implicit solver. Differences in global mean surface ozone concentrations are small (≤1.03 ppb), and no systematic drift or degradation in numerical stability is observed over one-year simulations. These results indicate that low-order Rosenbrock methods provide a computationally efficient and numerically stable alternative for stiff atmospheric chemistry integration in E3SMv1. The implementation offers a flexible framework for future model configurations with increased chemical complexity and resolution.

Geoscientific model developmentVol. 19(20)
University of Tennessee at Knoxville (US)
National Science Foundation, U.S. Department of Energy, National Energy Research Scientific Computing Center, Office of Science, Advanced Scientific Computing Research, Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory
Openalex Percentile: Top 75%
Atmospheric chemistry and aerosols
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