Impact of cloud model microphysics on passive microwave retrievals of cloud properties. Part I: Model comparison using EOF analyses

被引:20
|
作者
Biggerstaff, Michael I.
Seo, Eun-Kyoung
Hristova-Veleva, Svetla M.
Kim, Kwang-Yul
机构
[1] Univ Oklahoma, Sch Meteorol, Norman, OK 73019 USA
[2] Jet Propuls Lab, Pasadena, CA USA
[3] Florida State Univ, Tallahassee, FL 32306 USA
关键词
D O I
10.1175/JAM2372.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The impact of model microphysics on the relationships among hydrometeor profiles, latent heating, and derived satellite microwave brightness temperatures T-B have been examined using a nonhydrostatic, adaptive-grid cloud model to simulate a mesoscale convective system over water. Two microphysical schemes ( each employing three-ice bulk parameterizations) were tested for two different assumptions in the number of ice crystals assumed to be activated at 0 degrees C to produce simulations with differing amounts of supercooled cloud water. The model output was examined using empirical orthogonal function (EOF) analysis, which provided a quantitative framework in which to compare the simulations. Differences in the structure of the vertical anomaly patterns were related to physical processes and attributed to different approaches in cloud microphysical parameterizations in the two schemes. Correlations between the first EOF coefficients of cloud properties and T-B at frequencies associated with the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) showed additional differences between the two parameterization schemes that affected the relationship between hydrometeors and T-B. Classified in terms of T-B, the microphysical schemes produced significantly different mean vertical profiles of cloud water, cloud ice, snow, vertical velocity, and latent heating. The impact of supercooled cloud water on the 85-GHz T-B led to a 15% variation in mean convective rain mass at the surface. The variability in mean profiles produced by the four simulations indicates that the retrievals of cloud properties, especially latent heating, based on TMI frequencies are dependent on the particular microphysical parameterizations used to construct the retrieval database.
引用
收藏
页码:930 / 954
页数:25
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