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Proceedings Paper

Systematical evaluation of VPR- identification and enhancement (VPR-IE) approach for different precipitation types
Author(s): Yixin Wen; Yang Hong; Pierre Kirstetter; Qing Cao; J. J. Gourley; Jian Zhang; Xianwu Xue
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Paper Abstract

Over complex terrains, ground radars usually rely on scans at higher elevation angles to observe precipitating systems. The surface quantitative precipitation estimation (QPE) might have considerable errors if veridical structure of precipitation is not considered because radar reflectivity varies with height due to evaporation at low levels as well as processes of melting, aggregation, and drop break-up. The vertical profile of reflectivity (VPR) links the surface precipitation to the radar observation at higher levels, which is very useful for accurately estimating the surface rainfall. Researchers at the University of Oklahoma have demonstrated the integration of the Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar products (4-km precipitation quantity, types, and 250-meter vertical profile of reflectivity (VPR)) into the NEXRAD ground-based radar rainfall estimation system. In the latest progress in the VPRIdentification and Enhancement (VPR-IE) approach, we have optimally combined the climatological VPR information to the National Mosaic QPE (NMQ) system from 1 January 2011 to 31 December 2011 over the Mountainous West Region of the U.S. Performance of latest VPR-IE is systematically evaluated by rain gauges measurements for different precipitation types. The results indicate improvements in precipitation detection and estimation following the incorporation of space-based radar information into ground radar networks.

Paper Details

Date Published: 8 November 2014
PDF: 9 pages
Proc. SPIE 9259, Remote Sensing of the Atmosphere, Clouds, and Precipitation V, 92590C (8 November 2014); doi: 10.1117/12.2069334
Show Author Affiliations
Yixin Wen, The Univ. of Oklahoma (United States)
Yang Hong, The Univ. of Oklahoma (United States)
Pierre Kirstetter, The Univ. of Oklahoma (United States)
Qing Cao, The Univ. of Oklahoma (United States)
J. J. Gourley, National Severe Storms Lab. (United States)
Jian Zhang, National Severe Storms Lab. (United States)
Xianwu Xue, National Severe Storms Lab. (United States)


Published in SPIE Proceedings Vol. 9259:
Remote Sensing of the Atmosphere, Clouds, and Precipitation V
Eastwood Im; Song Yang; Peng Zhang, Editor(s)

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