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An Improved Oceanic Rainfall Retrieval Algorithm and Results from Seawinds

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3 Author(s)
Khalil Ahmad ; Central Florida Remote Sensing Laboratory, University of Central Florida, Orlando, FL 32816-2450 ; W. Linwood Jones ; Takis Kasparis

This paper describes the development of an oceanic rainfall retrieval algorithm that combines both the simultaneous active (radar backscatter) and passive (microwave brightness temperatures) observations from the SeaWinds scatterometer on the QuikSCAT satellite. The retrieval algorithm is statistically based, and has been developed using collocated measurements from SeaWinds, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rates, and the National Center for Environmental Prediction (NCEP) wind fields. The rain is retrieved on a wind vector cell (WVC) measurement grid that has a spatial resolution of 25 km. Due to its broad swath coverage, SeaWinds affords additional independent sampling of the oceanic rainfall, which may contribute to NASA's future Global Precipitation Mission. Results emphasize the powerful rain detection capabilities of the SeaWinds retrieval algorithm.

Published in:

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium  (Volume:4 )

Date of Conference:

7-11 July 2008