Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 16, issue 12
Articles | Volume 16, issue 12
https://doi.org/10.5194/essd-16-5753-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-5753-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 12
Data description paper
 | 
18 Dec 2024
Data description paper |  | 18 Dec 2024

Global tropical cyclone size and intensity reconstruction dataset for 1959–2022 based on IBTrACS and ERA5 data

Zhiqi Xu, Jianping Guo, Guwei Zhang, Yuchen Ye, Haikun Zhao, and Haishan Chen

Viewed

Total article views: 4,532 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,466 909 157 4,532 261 67 107
  • HTML: 3,466
  • PDF: 909
  • XML: 157
  • Total: 4,532
  • Supplement: 261
  • BibTeX: 67
  • EndNote: 107
Views and downloads (calculated since 06 Aug 2024)
Cumulative views and downloads (calculated since 06 Aug 2024)

Viewed (geographical distribution)

Total article views: 4,532 (including HTML, PDF, and XML) Thereof 4,428 with geography defined and 104 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 31 Dec 2025
Download
Short summary
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint