A typical severe convective precipitation process from the collaborative network mosaic from three XPADPRAD systems in Chengdu (drawn with Python 3.6).

A typical severe convective precipitation process from the collaborative network mosaic from three XPADPRAD systems in Chengdu (drawn with Python 3.6).

<p>A typical severe convective precipitation process from the collaborative network mosaic from three XPADPRAD systems in Chengdu (drawn with Python 3.6).</p>

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Bibliographic Details
Main Author:	Miaoyuan Xiao (15451337) (author)
Other Authors:	Lei Wang (6656) (author), Yuanchang Dong (17729575) (author), Chenghong Zhang (2069491) (author), Shunjiu Wang (17729578) (author), Kangquan Yang (6034784) (author), Kui Zhang (46471) (author)
Published:	2024
Subjects:	Biotechnology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified support operational utility provide probabilistic predictions omission alarm ratio observed precipitation data observation overlap area observation blind spots live observation data greater lead times data fusion technology critical success index cooperative networking data approximately 70 seconds approximately 7 minutes ></ sub >) >< sub >< increase warning times early warning approach quickly identify three many advantages compared fuzzy logic method div >< p based automatic station also significantly better traditional methods struggle improved thunderstorm identification early warning algorithm early warning traditional methods rapid identification lightning identification improved method traditional method traditional algorithm improved hail temporal resolution spatial continuity recent years radar systems one scan lightning occurrence lightning locations higher resolutions high spatial h </ dr </ comprehensively determine
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