Advances in Severe Convection Research and Operation in China
Journal of Meteorological Research, ISSN: 2198-0934, Vol: 34, Issue: 2, Page: 189-217
2020
- 29Citations
- 20Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
This article reviews the advances in severe convection research and operation in China during the past several decades. The favorable synoptic situations for severe convective weather (SCW), the major organization modes of severe convective storms (SCSs), the favorable environmental conditions and characteristics of weather radar echoes and satellite images of SCW and SCSs, and the forecasting and nowcasting techniques of SCW, are emphasized. As a whole, Chinese scientists have achieved a profound understanding of the synoptic patterns, organization, and evolution characteristics of SCW from radar and satellite observations, and the mechanisms of different types of convective weather in China. Specifically, in-depth understanding of the multiple types of convection triggers, along with the environmental conditions, structures and organization modes, and maintenance mechanisms of supercell storms and squall lines, has been obtained. The organization modes and climatological distributions of mesoscale convective systems and different types of SCW, and the multiscale characteristics and formation mechanisms of large hail, tornadoes, downbursts, and damaging convective wind gusts based on radar, satellite, and lightning observations, as well as the related features from damage surveys, are elucidated. In terms of operational applications, different types of identification and mesoanalysis techniques, and various forecasting and nowcasting techniques using methods such as the “ingredients-based” and deep learning algorithms, have been developed. As a result, the performance of operational SCW forecasts in China has been significantly improved.
Bibliographic Details
Springer Science and Business Media LLC
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