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Title: Impact of Physics Parameterization Ordering in a Global Atmosphere Model

Abstract

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced bymore » the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1422431
Alternate Identifier(s):
OSTI ID: 1425706; OSTI ID: 1432960
Report Number(s):
LLNL-JRNL-730895
Journal ID: ISSN 1942-2466
Grant/Contract Number:
AC52-07NA27344
Resource Type:
Journal Article: Published Article
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 10; Journal Issue: 2; Journal ID: ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 97 MATHEMATICS AND COMPUTING

Citation Formats

Donahue, Aaron S., and Caldwell, Peter M. Impact of Physics Parameterization Ordering in a Global Atmosphere Model. United States: N. p., 2018. Web. doi:10.1002/2017MS001067.
Donahue, Aaron S., & Caldwell, Peter M. Impact of Physics Parameterization Ordering in a Global Atmosphere Model. United States. doi:10.1002/2017MS001067.
Donahue, Aaron S., and Caldwell, Peter M. Fri . "Impact of Physics Parameterization Ordering in a Global Atmosphere Model". United States. doi:10.1002/2017MS001067.
@article{osti_1422431,
title = {Impact of Physics Parameterization Ordering in a Global Atmosphere Model},
author = {Donahue, Aaron S. and Caldwell, Peter M.},
abstractNote = {Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.},
doi = {10.1002/2017MS001067},
journal = {Journal of Advances in Modeling Earth Systems},
number = 2,
volume = 10,
place = {United States},
year = {Fri Feb 02 00:00:00 EST 2018},
month = {Fri Feb 02 00:00:00 EST 2018}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1002/2017MS001067

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