The overlap properties of similar to850 snapshots of convective cloud fields generated by a cloud-resolving model are studied and compared with previously published results based on cloud radar observations. Total cloud cover is overestimated by the random overlap assumption but underestimated by the maximum overlap assumption and two standard implementations of the combined maximum/random overlap assumption. When the overlap of two layers is examined as a function of vertical separation distance, the value of the parameter alpha measuring the relative weight of maximum (alpha=1) and random (alpha=0) overlap decreases in such a way that only layers less than 1 km apart can be considered maximally overlapped, while layers more than 5 km apart are essentially randomly overlapped. The decrease of alpha with separation distance Deltaz is best expressed by a power law, which may not, however, be suitable for parameterization purposes. The more physically appropriate exponential function has slightly smaller goodness of fit overall but still gives very good fits for Deltaz between 0 and 5 km, which is the range of separation distances that would be of most importance in any overlap parameterization for radiative transfer purposes.
机构:
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science &TechnologyCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science &Technology
Xianwen JING
Hua ZHANG
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Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science &Technology
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological SciencesCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science &Technology
Hua ZHANG
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Masaki SATOH
Shuyun ZHAO
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Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science &Technology
Laboratory for Climate Studies National Climate Center, China Meteorological AdministrationCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science &Technology
机构:
Univ Washington, Joint Inst Study Atmosphere & Ocean, Seattle, WA 98105 USAUniv Washington, Joint Inst Study Atmosphere & Ocean, Seattle, WA 98105 USA
Marchand, Roger
Ackerman, Thomas
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Univ Washington, Joint Inst Study Atmosphere & Ocean, Seattle, WA 98105 USAUniv Washington, Joint Inst Study Atmosphere & Ocean, Seattle, WA 98105 USA