Analysis of the Winter Cloud-to-Ground Lightning Activity and Its Synoptic Background in China during 2010–20

Cloud-to-ground (CG) lightning data and the ECMWF ERA-Interim reanalysis dataset are analyzed to gain insight into the spatiotemporal distribution and synoptic background of winter-season CG flashes between December 2010 and February 2020 in China. We identify three Winter Lightning Frequent Areas (...

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Veröffentlicht in:Advances in atmospheric sciences 2022-06, Vol.39 (6), p.985-998
Hauptverfasser: Ma, Manman, Huang, Xiaogang, Fei, Jianfang, Zhang, Chi, Li, Chao, Cheng, Xiaoping
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Sprache:eng
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Zusammenfassung:Cloud-to-ground (CG) lightning data and the ECMWF ERA-Interim reanalysis dataset are analyzed to gain insight into the spatiotemporal distribution and synoptic background of winter-season CG flashes between December 2010 and February 2020 in China. We identify three Winter Lightning Frequent Areas (WLAs): the southwest side of the Yunnan-Guizhou Plateau (WLA1), the east side of the Yunnan-Guizhou Plateau (WLA2), and the Poyang Lake Plain (WLA3). The CG lightning flashes most frequently occur at local midnight and have a monthly peak in February. The CG lightning in WLA1 is mostly generated in non-frontal weather; however, the lightning in WLA2 and WLA3 mostly occurs in frontal systems. The frontal circulation situation is divided into four typical types: transversal trough after high pressure, low vortex, confrontational convergence, and asymptotic convergence. In all typical weather patterns, the lightning occurs downstream of a 500 hPa trough and is accompanied by a southwesterly low-level jet. The convective parameters of winter thunderstorms differ greatly from those of summer thunderstorms. The maximum convective available potential energy (MCAPE) and K-index (KI) are more useful metrics than convective available potential energy (CAPE) and Showalter index (SI) during winter. This study further deepens the understanding of the distribution characteristics of winter CG lightning in China, which motivates further research to improve the ability of winter thunderstorm prediction.
ISSN:0256-1530
1861-9533
DOI:10.1007/s00376-021-1260-2