Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 17, issue 3
Articles | Volume 17, issue 3
https://doi.org/10.5194/essd-17-1153-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-1153-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 3
Data description paper
 | 
19 Mar 2025
Data description paper |  | 19 Mar 2025

Global projections of heat stress at high temporal resolution using machine learning

Pantelis Georgiades, Theo Economou, Yiannis Proestos, Jose Araya, Jos Lelieveld, and Marco Neira

Viewed

Total article views: 3,002 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,429 426 147 3,002 70 102
  • HTML: 2,429
  • PDF: 426
  • XML: 147
  • Total: 3,002
  • BibTeX: 70
  • EndNote: 102
Views and downloads (calculated since 22 Aug 2024)
Cumulative views and downloads (calculated since 22 Aug 2024)

Viewed (geographical distribution)

Total article views: 3,002 (including HTML, PDF, and XML) Thereof 2,923 with geography defined and 79 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 Nov 2025
Download
Short summary
Climate change is posing increasing challenges in the dairy cattle farming sector, as heat stress adversely affects the animals' health and milk production. To accurately assess these impacts, we developed a machine learning model to downscale daily climate data to hourly Temperature Humidity Index (THI) values. We utilized historical weather data to train our model and applied them to future climate projections, under two climate scenarios.
Read more
Share
Altmetrics
Final-revised paper
Preprint