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: 4,624 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
3,125
1,384
115
4,624
196
145
200
HTML: 3,125
PDF: 1,384
XML: 115
Total: 4,624
Supplement: 196
BibTeX: 145
EndNote: 200
Views and downloads (calculated since 09 Jan 2023)
Cumulative views and downloads
(calculated since 09 Jan 2023)
Total article views: 3,590 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
2,576
914
100
3,590
196
131
185
HTML: 2,576
PDF: 914
XML: 100
Total: 3,590
Supplement: 196
BibTeX: 131
EndNote: 185
Views and downloads (calculated since 30 Jun 2023)
Cumulative views and downloads
(calculated since 30 Jun 2023)
Total article views: 1,034 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
549
470
15
1,034
14
15
HTML: 549
PDF: 470
XML: 15
Total: 1,034
BibTeX: 14
EndNote: 15
Views and downloads (calculated since 09 Jan 2023)
Cumulative views and downloads
(calculated since 09 Jan 2023)
Viewed (geographical distribution)
Total article views: 4,624 (including HTML, PDF, and XML)
Thereof 4,588 with geography defined
and 36 with unknown origin.
Total article views: 3,590 (including HTML, PDF, and XML)
Thereof 3,573 with geography defined
and 17 with unknown origin.
Total article views: 1,034 (including HTML, PDF, and XML)
Thereof 1,015 with geography defined
and 19 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...
