Radar characteristics of summer thunderstorms in the Kanto Plain of Japan with and without cloud-to-ground lightning
In: Meteorology and Atmospheric Physics, Jg. 133 (2020-05-11), S. 233-244
Online
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Zugriff:
The elucidation of characteristics of cumulonimbus clouds that cause lightning is important for predicting thunderstorm development. These characteristics, with and without lightning, were observed during a day (in 2010) of severe thunderstorms and lightning in Japan and statistically analyzed using radar observations with cell tracking. Observed cells were categorized into a cell including cloud-to-ground lightning (CG) and intra-cloud lightning (CGIC), a cell containing only intra-cloud lightning (IC), and a cell without lightning (NoL). These cells were compared to the average and temporal evolution of radar observations. Out of the 265 cells generated, 103 were CGIC cells, 30 were IC cells, and 132 were NoL cells. Significant differences were detected between the averaged values of lifetime, size, echo top, vertically integrated liquid (VIL), maximum radar reflectivity, and radar reflectivity of each cell category, when the − 10 °C isotherm height was considered. The temporal evolution of CGIC cell characteristics revealed changes in radar reflectivity at 0 °C and − 10 °C that were synchronized with lightning activity. The VIL value was elevated only for CGIC cells and had the tendency to decrease with time as lightning activity. CGIC cells produced the highest echo top and maintained their height during their lifetime. To predict CG within 20 min using 35 dBZ radar reflectivity at − 30 °C as the criterion, a critical success index (CSI) of 0.82 and false alarm rate (FAR) of 0.64 were found to have the best prediction scores.
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Radar characteristics of summer thunderstorms in the Kanto Plain of Japan with and without cloud-to-ground lightning
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Autor/in / Beteiligte Person: | Hayashi, Syugo ; Fujibe, Fumiaki ; Nakaike, Chizuru |
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Zeitschrift: | Meteorology and Atmospheric Physics, Jg. 133 (2020-05-11), S. 233-244 |
Veröffentlichung: | Springer Science and Business Media LLC, 2020 |
Medientyp: | unknown |
ISSN: | 1436-5065 (print) ; 0177-7971 (print) |
DOI: | 10.1007/s00703-020-00748-z |
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