Performance of the Goddard multiscale modeling framework with Goddard ice microphysical schemes Article Swipe
J. Chern
,
Wei‐Kuo Tao
,
S. Lang
,
Toshihisa Matsui
,
J.‐L. F. Li
,
Karen I. Mohr
,
Gail Skofronick‐Jackson
,
C. D. Peters‐Lidard
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1002/2015ms000469
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1002/2015ms000469
The 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.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/2015ms000469
- OA Status
- gold
- Cited By
- 20
- References
- 137
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W2212893690Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/2015ms000469Digital Object Identifier
- Title
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Performance of the Goddard multiscale modeling framework with Goddard ice microphysical schemesWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2015Year of publication
- Publication date
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2015-12-15Full publication date if available
- Authors
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J. Chern, Wei‐Kuo Tao, S. Lang, Toshihisa Matsui, J.‐L. F. Li, Karen I. Mohr, Gail Skofronick‐Jackson, C. D. Peters‐LidardList of authors in order
- Landing page
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https://doi.org/10.1002/2015ms000469Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1002/2015ms000469Direct OA link when available
- Concepts
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Graupel, Environmental science, Snow, Cloud computing, Cloud forcing, Ice cloud, Meteorology, Climate model, Climatology, Atmospheric sciences, Cloud cover, Climate change, Computer science, Geology, Geography, Oceanography, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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20Total citation count in OpenAlex
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2024: 1, 2022: 4, 2021: 1, 2020: 3, 2019: 4Per-year citation counts (last 5 years)
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137Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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