Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 1
Articles | Volume 18, issue 1
https://doi.org/10.5194/gmd-18-161-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-161-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 1
Model experiment description paper
 | 
15 Jan 2025
Model experiment description paper |  | 15 Jan 2025

Climate model downscaling in central Asia: a dynamical and a neural network approach

Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann

Viewed

Total article views: 2,789 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,066 640 83 2,789 73 97 134
  • HTML: 2,066
  • PDF: 640
  • XML: 83
  • Total: 2,789
  • Supplement: 73
  • BibTeX: 97
  • EndNote: 134
Views and downloads (calculated since 05 Dec 2023)
Cumulative views and downloads (calculated since 05 Dec 2023)

Viewed (geographical distribution)

Total article views: 2,789 (including HTML, PDF, and XML) Thereof 2,752 with geography defined and 37 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 06 Dec 2025
Download
Short summary
We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.

Read more
Share