Systematical evaluation of VPR- identification and enhancement (VPR-IE) approach for different precipitation types

Yixin Wen; Yang Hong; Pierre Kirstetter; Qing Cao; J. J. Gourley; Jian Zhang; Xianwu Xue

doi:10.1117/12.2069334

8 November 2014 Systematical evaluation of VPR- identification and enhancement (VPR-IE) approach for different precipitation types

Yixin Wen, Yang Hong, Pierre Kirstetter, Qing Cao, J. J. Gourley, Jian Zhang, Xianwu Xue

Author Affiliations +

Proceedings Volume 9259, Remote Sensing of the Atmosphere, Clouds, and Precipitation V; 92590C (2014) https://doi.org/10.1117/12.2069334
Event: SPIE Asia-Pacific Remote Sensing, 2014, Beijing, China

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.

Citation Download Citation

Yixin Wen, Yang Hong, Pierre Kirstetter, Qing Cao, J. J. Gourley, Jian Zhang, and Xianwu Xue "Systematical evaluation of VPR- identification and enhancement (VPR-IE) approach for different precipitation types", Proc. SPIE 9259, Remote Sensing of the Atmosphere, Clouds, and Precipitation V, 92590C (8 November 2014); https://doi.org/10.1117/12.2069334

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