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: 1,279 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
958 271 50 1,279 40 56 49
  • HTML: 958
  • PDF: 271
  • XML: 50
  • Total: 1,279
  • Supplement: 40
  • BibTeX: 56
  • EndNote: 49
Views and downloads (calculated since 05 Dec 2023)
Cumulative views and downloads (calculated since 05 Dec 2023)

Viewed (geographical distribution)

Total article views: 1,279 (including HTML, PDF, and XML) Thereof 1,240 with geography defined and 39 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Discussed (final revised paper)

Latest update: 21 Feb 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