A Set of Prognostic Variables for Long-Term Cloud-Resolving Model Simulations
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- ZENG Xiping
- Goddard Earth Sciences and Technology Center, University of Maryland Laboratory for Atmospheres, NASA Goddard Space Flight Center
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- TAO Wei-Kuo
- Laboratory for Atmospheres, NASA Goddard Space Flight Center
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- SIMPSON Joanne
- Laboratory for Atmospheres, NASA Goddard Space Flight Center
Bibliographic Information
- Other Title
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- A set of prognostic variables for long-term cloud-resolving mode simulations
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Description
A set of independent prognostic variables, based on a survey of the microphysical timescales in clouds, is proposed for long-term cloud-resolving model simulations. Two of the variables are the moist entropy and the total mixing ratio of airborne water with no contributions from precipitating particles. Non-prognostic variables such as air temperature can be diagnosed from the prognostic variables easily. In this proposed modeling framework, moist thermodynamics is separated (or modularized) from cloud dynamics and microphysics. Numerical results are compared with analytic solutions to show that the proposed prognostic variables work well when a large time step (e.g., 10 s) is used for numerical integration.
Journal
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- Journal of the Meteorological Society of Japan. Ser. II
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Journal of the Meteorological Society of Japan. Ser. II 86 (6), 839-856, 2008
Meteorological Society of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001206503695616
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- NII Article ID
- 110007021636
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- NII Book ID
- AA00702524
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- ISSN
- 21869057
- 00261165
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- NDL BIB ID
- 9752100
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- NDL-Digital
- CiNii Articles
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- Abstract License Flag
- Disallowed