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Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical SchemesThe multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.
Document ID
20160009338
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Chern, Jiun-Dar
(Maryland Univ. College Park, MD, United States)
Tao, Wei-Kuo
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Lang, Stephen E.
(Science Systems and Applications, Inc. Lanham, MD, United States)
Matsui, Toshihisa
(Maryland Univ. College Park, MD, United States)
Li, J.-L.
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Mohr, Karen I.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Skofronick-Jackson, Gail M.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Peters-Lidard, Christa D.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
July 25, 2016
Publication Date
January 28, 2016
Publication Information
Publication: Journal of Advances in Modeling Earth Systems
Publisher: AGU Publications
Volume: 8
Issue: 1
e-ISSN: 1942-2466
Subject Category
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN33951
Funding Number(s)
CONTRACT_GRANT: NNX12AD03A
Distribution Limits
Public
Copyright
Other
Keywords
snow
microphysics scheme
cloud-resolving models

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