Skills of Thunderstorm Prediction by Convective Indices over a Metropolitan Area: Comparison of Microwave and Radiosonde Data

Autor: Mikhail Yu. Kulikov, Mikhail V. Belikovich, Natalya K. Skalyga, Maria V. Shatalina, Svetlana O. Dementyeva, Vitaly G. Ryskin, Alexander A. Shvetsov, Alexander A. Krasil’nikov, Evgeny A. Serov, Alexander M. Feigin
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Remote Sensing, Vol 12, Iss 4, p 604 (2020)
Druh dokumentu: article
ISSN: 2072-4292
DOI: 10.3390/rs12040604
Popis: In this work, we compare the values of 15 convective indices obtained from radiosonde and microwave temperature and water vapor profiles simultaneously measured over Nizhny Novgorod (56.2°N, 44°E) during 5 convective seasons of 2014−2018. A good or moderate correlation (with coefficients of ~0.7−0.85) is found for most indices. We assess the thunderstorm prediction skills with a lead time of 12 h for each radiosonde and microwave index. It is revealed that the effectiveness of thunderstorm prediction by microwave indices is much better than by radiosonde ones. Moreover, a good correlation between radiosonde and microwave values of a certain index does not necessarily correspond to similar prediction skills. Eight indices (Showalter Index, Maximum Unstable Convective Available Potential Energy (CAPE), Total Totals index, TQ index, Jefferson Index, S index, K index, and Thompson index) are regarded to be the best predictors from both the true skill statistics (TSS) maximum and Heidke skill score (HSS) maximum points of view. In the case of radiosonde data, the best indices are the Jefferson Index, K index, S index, and Thompson index. Only TSS and HSS maxima for these indices are close to the microwave ones, whereas the prediction skills of other radiosonde indices are essentially worse than in the case of microwave data. The analysis suggests that the main possible reason of this discrepancy is an unexpectedly low quality of radiosonde data.
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