Characteristics of spatial distribution and temporal variation of convective cloud merger in Yangtze and Huaihe River Basin in summer season

Wen Hu; Yong Huang; Labao Wang

doi:10.1117/12.746120

9 October 2007 Characteristics of spatial distribution and temporal variation of convective cloud merger in Yangtze and Huaihe River Basin in summer season

Wen Hu, Yong Huang, Labao Wang

Author Affiliations +

Proceedings Volume 6679, Remote Sensing and Modeling of Ecosystems for Sustainability IV; 66791O (2007) https://doi.org/10.1117/12.746120
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

Abstract

GMS and FY-1C satellite data in Summer Season (June to August) during the period of 2001~2006 were used to analyze the spatial and temporal distribution characteristic of convective cloud merger in Yangtze and Huaihe River Basin. The results show that convective cloud merger in Yangtze and Huaihe River Basin occurs frequently in summer season, and has a typical spatial and temporal distribution characteristic, coinciding very well with the thunderstorm days distribution in Yangtze and Huaihe River Basin. a) Cloud mergers in the Yangtze and Huaihe River Basin show a distinct spatial grouping associated to mesoscale topography. Three high frequency centers are Dabieshan mountain area with frequency of 28%, Huangshan mountain area with frequency of 23% and Hongzehu area with frequency of 16%. b) Cloud mergers often occur during late June and early August, with a prominent peak during late July. The diurnal variation of cloud mergers shows a peak at 1400 LST, some two hours after convective cloud initiation. c) Merging has a significant effect on cloud system developing. More than 80% merged clouds have apparent increase with enlarging of intensity and area, and lengthening of lifetime.

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Wen Hu, Yong Huang, and Labao Wang "Characteristics of spatial distribution and temporal variation of convective cloud merger in Yangtze and Huaihe River Basin in summer season", Proc. SPIE 6679, Remote Sensing and Modeling of Ecosystems for Sustainability IV, 66791O (9 October 2007); https://doi.org/10.1117/12.746120

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