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Title: Hail-Detection Algorithm for the GPM Core Observatory Satellite Sensors
Authors: Mroz, Kamil
Battaglia, Alessandro
Lang, Timothy J.
Cecil, Daniel J.
Tanelli, Simone
Tridon, Frederic
First Published: 27-Jun-2017
Publisher: American Meteorological Society
Citation: Journal of Applied Meteorology and Climatology, 2017, 56 (7), pp. 1939-1957
Abstract: By exploiting an abundant number of extreme storms observed simultaneously by the Global Precipitation Measurement (GPM) mission Core Observatory satellite’s suite of sensors and by the ground-based S-band Next Generation Weather Radar (NEXRAD) network over the continental United States, proxies for the identification of hail are developed from the GPM Core Observatory satellite observables. The full capabilities of the GPM Core Observatory are tested by analyzing more than 20 observables and adopting the hydrometeor classification on the basis of ground-based polarimetric measurements being truth. The proxies have been tested using the critical success index (CSI) as a verification measure. The hail-detection algorithm that is based on the mean Ku-band reflectivity in the mixed-phase layer performs the best of all considered proxies (CSI of 45%). Outside the dual-frequency precipitation radar swath, the polarization-corrected temperature at 18.7 GHz shows the greatest potential for hail detection among all GPM Microwave Imager channels (CSI of 26% at a threshold value of 261 K). When dual-variable proxies are considered, the combination involving the mixed-phase reflectivity values at both Ku and Ka bands outperforms all of the other proxies, with a CSI of 49%. The best-performing radar–radiometer algorithm is based on the mixed-phase reflectivity at Ku band and on the brightness temperature (TB) at 10.7 GHz (CSI of 46%). When only radiometric data are available, the algorithm that is based on the TBs at 36.6 and 166 GHz is the most efficient, with a CSI of 27.5%.
DOI Link: 10.1175/JAMC-D-16-0368.1
ISSN: 1558-8424
eISSN: 1558-8432
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Description: Supplemental information related to this paper is available at the Journals Online website:
Appears in Collections:Published Articles, Dept. of Physics and Astronomy

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