Articles | Volume 14, issue 12
https://doi.org/10.5194/essd-14-5637-2022
https://doi.org/10.5194/essd-14-5637-2022
Data description paper
 | 
21 Dec 2022
Data description paper |  | 21 Dec 2022

A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)

Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Gang Chen, Jia Hu, and Li Wang

Viewed

Total article views: 9,192 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
7,277 1,773 142 9,192 502 95 118
  • HTML: 7,277
  • PDF: 1,773
  • XML: 142
  • Total: 9,192
  • Supplement: 502
  • BibTeX: 95
  • EndNote: 118
Views and downloads (calculated since 21 Jul 2022)
Cumulative views and downloads (calculated since 21 Jul 2022)

Viewed (geographical distribution)

Total article views: 9,192 (including HTML, PDF, and XML) Thereof 8,774 with geography defined and 418 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Apr 2025
Download
Short summary
We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
Share
Altmetrics
Final-revised paper
Preprint