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Proceedings Paper

Evaluation of observed and pre-simulated passive microwave signatures over tropical oceans
Author(s): Eun-Kyoung Seo; Michael I. Biggerstaff
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Paper Abstract

Bayesian algorithms are a common method of retrieving cloud properties from a set of observed passive microwave brightness temperature (TB) measurements. In practice, such methods often use predefined databases from cloud resolving models to perform the retrieval. Successful performance in these types of Bayesian retrievals is greatly affected by the similarity of TBs between observed and predefined databases. Here Empirical Orthogonal Function (EOF) analysis methods were used to illustrate the importance of predefined simulation databases on the ability to retrieve known regional variability in cloud structures across different parts of the tropical oceans and to provide insight on the relative impact of environmental conditions to limitations in cloud model microphysical parameterizations in retrieving different types of cloud structures. The spatial distributions of EOF coefficients in EOF space showed that there were both underrepresentation and overrepresentation between manifolds of the predefined and observed databases.

Paper Details

Date Published: 26 October 2011
PDF: 5 pages
Proc. SPIE 8177, Remote Sensing of Clouds and the Atmosphere XVI, 817712 (26 October 2011); doi: 10.1117/12.897927
Show Author Affiliations
Eun-Kyoung Seo, Kongju National Univ. (Korea, Republic of)
Michael I. Biggerstaff, The Univ. of Oklahoma (United States)

Published in SPIE Proceedings Vol. 8177:
Remote Sensing of Clouds and the Atmosphere XVI
Evgueni I. Kassianov; Adolfo Comeron; Richard H. Picard; Klaus Schäfer, Editor(s)

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