Elucidating the Life Cycle of Warm-Season Mesoscale Convective Systems in Eastern China from the Himawari-8 Geostationary Satellite

Remote Sensing

Zhe Feng¹  Yanluan Lin²  Dandan Chen³  Jianping Guo³  Dan Yao³ 

[1] Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, DC 99352, USA;Ministry of Education Key Laboratory for Earth System Modeling, and Department for Earth System Science, Tsinghua University, Beijing 100084, China;State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China;

关键词: mesoscale convective system (MCS);    eastern China;    Himawari-8;    three-dimensional radar mosaics;    precipitation;   

DOI  :  10.3390/rs12142307

来源: DOAJ

【 摘 要 】

The life cycle of mesoscale convective systems (MCSs) in eastern China is yet to be fully understood, mainly due to the lack of observations of high spatio-temporal resolution and objective methods. Here, we quantitatively analyze the properties of warm-season (from April to September of 2016) MCSs during their lifetimes using the Himawari-8 geostationary satellite, combined with ground-based radars and gauge measurements. Generally, the occurrence of satellite derived MCSs has a noon peak over the land and an early morning peak over the ocean, which is several hours earlier than the precipitation peak. The developing and dissipative stages are significantly longer as total durations of MCSs increase. Aided by three-dimensional radar mosaics, we find the fraction of convective cores over northern China is much lower when compared with those in central United States, indicating that the precipitation produced by broad stratiform clouds may be more important for northern China. When there exists a large amount of stratiform precipitation, it releases a large amount of latent heat and promotes the large-scale circulations, which favors the maintenance of MCSs. These findings provide quantitative results about the life cycle of warm-season MCSs in eastern China based on multiple data sources and large numbers of samples.

【 授权许可】

Unknown