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A passive microwave technique for estimating rainfall and vertical structure information from space. Part 1: Algorithm descriptionThis paper describes a multichannel physical approach for retrieving rainfall and vertical structure information from satellite-based passive microwave observations. The algorithm makes use of statistical inversion techniques based upon theoretically calculated relations between rainfall rates and brightness temperatures. Potential errors introduced into the theoretical calculations by the unknown vertical distribution of hydrometeors are overcome by explicity accounting for diverse hydrometeor profiles. This is accomplished by allowing for a number of different vertical distributions in the theoretical brightness temperature calculations and requiring consistency between the observed and calculated brightness temperatures. This paper will focus primarily on the theoretical aspects of the retrieval algorithm, which includes a procedure used to account for inhomogeneities of the rainfall within the satellite field of view as well as a detailed description of the algorithm as it is applied over both ocean and land surfaces. The residual error between observed and calculated brightness temperatures is found to be an important quantity in assessing the uniqueness of the solution. It is further found that the residual error is a meaningful quantity that can be used to derive expected accuracies from this retrieval technique. Examples comparing the retrieved results as well as the detailed analysis of the algorithm performance under various circumstances are the subject of a companion paper.
Document ID
19950034093
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Kummerow, Christian
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Giglio, Louis
(Science Systems & Applications, Inc. Lanham, MD, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1994
Publication Information
Publication: Journal of Applied Meteorology
Volume: 33
Issue: 1
ISSN: 0894-8763
Subject Category
Meteorology And Climatology
Accession Number
95A65692
Distribution Limits
Public
Copyright
Other

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