Editorial Type:
Article
Article Type:
Research Article

An Automated Radar Technique for the Identification of Tropical Precipitation

Xiaoyong Xu Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Kenneth Howard NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma

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Jian Zhang Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Print Publication:
01 Oct 2008
DOI:
https://doi.org/10.1175/2007JHM954.1
Page(s):
885–902
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Abstract

A radar-based automated technique for the identification of tropical precipitation was developed to improve quantitative precipitation estimation during extreme rainfall events. The technique uses vertical profiles of reflectivity to identify the potential presence of warm rain (i.e., tropical rainfall) microphysics and delineates the tropical rainfall region to which the tropical Z–R relationship is applied. The performance of the algorithm is examined based on case studies of five storms that produced extreme precipitation in the United States. Results demonstrate relative improvements in radar-based quantitative precipitation estimation through the automated identification of tropical rainfall and the subsequent adaptation of the tropical Z–R relation to account for the potential warm rain processes.

Corresponding author address: Xiaoyong Xu, NSSL/WRDD, 120 David L. Boren Blvd., Norman, OK 73072. Email: E-mail xiaoyong.xu@noaa.gov

Abstract

A radar-based automated technique for the identification of tropical precipitation was developed to improve quantitative precipitation estimation during extreme rainfall events. The technique uses vertical profiles of reflectivity to identify the potential presence of warm rain (i.e., tropical rainfall) microphysics and delineates the tropical rainfall region to which the tropical Z–R relationship is applied. The performance of the algorithm is examined based on case studies of five storms that produced extreme precipitation in the United States. Results demonstrate relative improvements in radar-based quantitative precipitation estimation through the automated identification of tropical rainfall and the subsequent adaptation of the tropical Z–R relation to account for the potential warm rain processes.

Corresponding author address: Xiaoyong Xu, NSSL/WRDD, 120 David L. Boren Blvd., Norman, OK 73072. Email: E-mail xiaoyong.xu@noaa.gov

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