Institute of Urban Meteorology, China Metrological Administration, Beijing 100089, China
Yuchen Ye
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, 210044, China
Haikun Zhao
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, 210044, China
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, 210044, China
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Total article views: 5,302 (including HTML, PDF, and XML)
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Total
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EndNote
3,952
1,155
195
5,302
361
84
119
HTML: 3,952
PDF: 1,155
XML: 195
Total: 5,302
Supplement: 361
BibTeX: 84
EndNote: 119
Views and downloads (calculated since 06 Aug 2024)
Cumulative views and downloads
(calculated since 06 Aug 2024)
Total article views: 3,880 (including HTML, PDF, and XML)
HTML
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Total
Supplement
BibTeX
EndNote
3,212
598
70
3,880
202
64
100
HTML: 3,212
PDF: 598
XML: 70
Total: 3,880
Supplement: 202
BibTeX: 64
EndNote: 100
Views and downloads (calculated since 18 Dec 2024)
Cumulative views and downloads
(calculated since 18 Dec 2024)
Total article views: 1,422 (including HTML, PDF, and XML)
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Total
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EndNote
740
557
125
1,422
159
20
19
HTML: 740
PDF: 557
XML: 125
Total: 1,422
Supplement: 159
BibTeX: 20
EndNote: 19
Views and downloads (calculated since 06 Aug 2024)
Cumulative views and downloads
(calculated since 06 Aug 2024)
Viewed (geographical distribution)
Total article views: 5,302 (including HTML, PDF, and XML)
Thereof 5,202 with geography defined
and 100 with unknown origin.
Total article views: 3,880 (including HTML, PDF, and XML)
Thereof 3,810 with geography defined
and 70 with unknown origin.
Total article views: 1,422 (including HTML, PDF, and XML)
Thereof 1,392 with geography defined
and 30 with unknown origin.
Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. Here we generate a global long-term TC size and intensity reconstruction dataset, covering a time period from 1959 to 2022, with a 3 h temporal resolution, using machine learning models. These can be valuable for filling observational data gaps and advancing our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters.
Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. Here we...