Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China
Yaqiang Wang
Chinese Academy of Meteorological Sciences, Beijing 100081, China
Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China
Yuanyuan Zheng
Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China
Xiaoran Zhuang
Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China
Jiangsu Meteorological Observatory, Nanjing 210041, China
Hongyan Wang
Chinese Academy of Meteorological Sciences, Beijing 100081, China
Mei Gao
Chinese Academy of Meteorological Sciences, Beijing 100081, China
Viewed
Total article views: 1,637 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
1,140
435
62
1,637
57
63
62
HTML: 1,140
PDF: 435
XML: 62
Total: 1,637
Supplement: 57
BibTeX: 63
EndNote: 62
Views and downloads (calculated since 09 Jan 2023)
Cumulative views and downloads
(calculated since 09 Jan 2023)
Total article views: 946 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
655
241
50
946
57
58
56
HTML: 655
PDF: 241
XML: 50
Total: 946
Supplement: 57
BibTeX: 58
EndNote: 56
Views and downloads (calculated since 30 Jun 2023)
Cumulative views and downloads
(calculated since 30 Jun 2023)
Total article views: 691 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
485
194
12
691
5
6
HTML: 485
PDF: 194
XML: 12
Total: 691
BibTeX: 5
EndNote: 6
Views and downloads (calculated since 09 Jan 2023)
Cumulative views and downloads
(calculated since 09 Jan 2023)
Viewed (geographical distribution)
Total article views: 1,637 (including HTML, PDF, and XML)
Thereof 1,575 with geography defined
and 62 with unknown origin.
Total article views: 946 (including HTML, PDF, and XML)
Thereof 910 with geography defined
and 36 with unknown origin.
Total article views: 691 (including HTML, PDF, and XML)
Thereof 665 with geography defined
and 26 with unknown origin.
Due to the small-scale and nonstationary nature of convective wind gusts (CGs), reliable CG nowcasting has remained unattainable. Here, we developed a deep learning model — namely CGsNet — for 0—2 h of quantitative CG nowcasting, first achieving minute—kilometer-level forecasts. Based on the CGsNet model, the average surface wind speed (ASWS) and peak wind gust speed (PWGS) predictions are obtained. Experiments indicate that CGsNet exhibits higher accuracy than the traditional method.
Due to the small-scale and nonstationary nature of convective wind gusts (CGs), reliable CG...