A Multiscale Modeling System: Developments, Applications, and Critical Issues

Wei-Kuo Tao
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Jiun-Dar Chern
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Robert Atlas
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David Randall
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Marat Khairoutdinov
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Jui-Lin Li
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Duane E. Waliser
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Arthur Hou
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Xin Lin
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Christa Peters-Lidard
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William Lau
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Jonathan Jiang
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Joanne Simpson
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A multiscale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach for climate modeling. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The CRM allows for explicit simulation of cloud processes and their interactions with radiation and surface processes, and the GCM allows for global coverage.

A new MMF has been developed that is based on the NASA Goddard Space Flight Center (GSFC) finite-volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using traditional cloud parameterizations. Both MMFs also produce a large and positive precipitation bias in the Indian Ocean and western Pacific during the Northern Hemisphere summer. However, there are also notable differences between the two MMFs. For example, the CSU MMF simulates less rainfall over land than its parent GCM. This is why the CSU MMF simulated less overall global rainfall than its parent GCM. The Goddard MMF simulates more global rainfall than its parent GCM because of the high contribution from the oceanic component. A number of critical issues (i.e., the CRM's physical processes and its configuration) involving the Goddard MMF are discussed in this paper.

Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland

Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, and Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland

NOAA/Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida

Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, and Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

Hydrological Sciences Branch, NASA Goddard Space Flight Center, Greenbelt, Maryland

CORRESPONDING AUTHOR: Dr. Wei-Kuo Tao, Code 613.1, NASA Goddard Space Flight Center, Greenbelt, MD 20771, E-mail: Wei-Kuo.Tao-l@nasa.gov

A multiscale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach for climate modeling. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The CRM allows for explicit simulation of cloud processes and their interactions with radiation and surface processes, and the GCM allows for global coverage.

A new MMF has been developed that is based on the NASA Goddard Space Flight Center (GSFC) finite-volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using traditional cloud parameterizations. Both MMFs also produce a large and positive precipitation bias in the Indian Ocean and western Pacific during the Northern Hemisphere summer. However, there are also notable differences between the two MMFs. For example, the CSU MMF simulates less rainfall over land than its parent GCM. This is why the CSU MMF simulated less overall global rainfall than its parent GCM. The Goddard MMF simulates more global rainfall than its parent GCM because of the high contribution from the oceanic component. A number of critical issues (i.e., the CRM's physical processes and its configuration) involving the Goddard MMF are discussed in this paper.

Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland

Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, and Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland

NOAA/Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida

Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, and Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

Hydrological Sciences Branch, NASA Goddard Space Flight Center, Greenbelt, Maryland

CORRESPONDING AUTHOR: Dr. Wei-Kuo Tao, Code 613.1, NASA Goddard Space Flight Center, Greenbelt, MD 20771, E-mail: Wei-Kuo.Tao-l@nasa.gov
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