@article{db2c75b2593f4ffb9d27137f12bbcac2,
title = "Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling",
abstract = "Convergence testing is a common practice in the development of dynamical cores of atmospheric models but is not as often exercised for the parameterization of subgrid physics. An earlier study revealed that the stratiform cloud parameterizations in several predecessors of the Energy Exascale Earth System Model (E3SM) showed strong time step sensitivity and slower-than-expected convergence when the model's time step was systematically refined. In this work, a simplified atmosphere model is configured that consists of the spectral-element dynamical core of the E3SM atmosphere model coupled with a large-scale condensation parameterization based on commonly used assumptions. This simplified model also resembles E3SM and its predecessors in the numerical implementation of process coupling and shows poor time step convergence in short ensemble tests. We present a formal error analysis to reveal the expected time step convergence rate and the conditions for obtaining such convergence. Numerical experiments are conducted to investigate the root causes of convergence problems. We show that revisions in the process coupling and closure assumption help to improve convergence in short simulations using the simplified model; the same revisions applied to a full atmosphere model lead to significant changes in the simulated long-term climate. This work demonstrates that causes of convergence issues in atmospheric simulations can be understood by combining analyses from physical and mathematical perspectives. Addressing convergence issues can help to obtain a discrete model that is more consistent with the intended representation of the physical phenomena.",
keywords = "atmospheric model, convergence, parameterization, time stepping",
author = "Hui Wan and Woodward, {Carol S.} and Shixuan Zhang and Vogl, {Christopher J.} and Panos Stinis and Gardner, {David J.} and Rasch, {Philip J.} and Xubin Zeng and Larson, {Vincent E.} and Balwinder Singh",
note = "Funding Information: The authors thank Dr. Nigel Wood and an anonymous reviewer for their careful review and insightful comments. This work was supported by the U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research (BER), and Office of Advanced Scientific Computing Research (ASCR) via the Scientific Discovery through Advanced Computing (SciDAC) program. Computing resources were provided by the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility operated under Contract No. DE‐AC02‐05CH11231. Additional computing resources were provided by Research Computing at Pacific Northwest National Laboratory (PNNL) and the Livermore Computing Center at Lawrence Livermore National Laboratory (LLNL). PNNL is operated for DOE by Battelle Memorial Institute under contract DE‐AC06‐76RLO 1830. Work at LLNL was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE‐AC52‐07NA27344. Lawrence Livermore National Security, LLC. Funding Information: Source codes used by simulations presented in this paper are based on the E3SM code (E3SM Project, 2018 ) sponsored by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. Our modifications are available from the E3SM code repository on GitHub ( https://github.com/E3SM‐Project/E3SM.git ). The simplified large‐scale condensation parameterization can be found on the branch (huiwanpnnl/atm/simple_condensation). The CAM4 physics suite with revised process coupling can be found on the branch (huiwanpnnl/atm/cam4_physics_revised_splitting). Model output used in this paper is available through the U.S. Department of Energy's Data Explorer at https://www.osti.gov/dataexplorer/biblio/dataset/1603675 (DOI:10.25584/data.2020‐03.1181/1603675). The CloudSat and CERES‐EBAF data used here were obtained from the U.S. National Center for Atmospheric Research (NCAR) as part of the Atmosphere Modeling Working Group (AMWG) Diagnostics Package ( https://www.cesm.ucar.edu/working_groups/Atmosphere/amwg‐diagnostics‐package/index.html ). The observational data in their repository can be found online ( https://svn‐ccsm‐release.cgd.ucar.edu/model_diagnostics/atm/cam/obs_data_20140804/ ). Publisher Copyright: {\textcopyright} 2020. The Authors.",
year = "2020",
month = oct,
day = "1",
doi = "10.1029/2019MS001982",
language = "English (US)",
volume = "12",
journal = "Journal of Advances in Modeling Earth Systems",
issn = "1942-2466",
publisher = "American Geophysical Union",
number = "10",
}