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Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling

Journal Article · · Journal of Advances in Modeling Earth Systems
DOI:https://doi.org/10.1029/2019ms001982· OSTI ID:1706688
 [1];  [2];  [1];  [2];  [1];  [2];  [1];  [3];  [4];  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  3. Univ. of Arizona, Tucson, AZ (United States)
  4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Univ. of Wisconsin, Milwaukee, WI (United States)
+ Show Author Affiliations
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 sub-grid 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.
Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR). Scientific Discovery through Advanced Computing (SciDAC); USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC02-05CH11231; AC05-76RL01830; AC52-07NA27344
OSTI ID:
1706688
Alternate ID(s):
OSTI ID: 1762840
Report Number(s):
LLNL-JRNL--818567; PNNL-SA--149970
Journal Information:
Journal of Advances in Modeling Earth Systems, Journal Name: Journal of Advances in Modeling Earth Systems Journal Issue: 10 Vol. 12; ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English

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  • Hemez, Francois; Brock, Jerry; Kamm, James
  • 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
    14th AIAA/ASME/AHS Adaptive Structures Conference
    7th     https://doi.org/10.2514/6.2006-1995
conference June 2012
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Related Subjects

54 ENVIRONMENTAL SCIENCES
ACGM
atmospheric model
clouds
convergence
numerical analysis
parameterization
time stepping