Data Science for Industry and Physics, Fondazione Bruno Kessler, via Sommarive 18, 38123 Trento (TN), Italy
Marco Cristoforetti
Data Science for Industry and Physics, Fondazione Bruno Kessler, via Sommarive 18, 38123 Trento (TN), Italy
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Total article views: 253 (including HTML, PDF, and XML)
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Views and downloads (calculated since 18 Sep 2024)
Cumulative views and downloads
(calculated since 18 Sep 2024)
Total article views: 253 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
252
0
1
253
0
0
HTML: 252
PDF: 0
XML: 1
Total: 253
BibTeX: 0
EndNote: 0
Views and downloads (calculated since 18 Sep 2024)
Cumulative views and downloads
(calculated since 18 Sep 2024)
Viewed (geographical distribution)
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 253 (including HTML, PDF, and XML)
Thereof 238 with geography defined
and 15 with unknown origin.
Total article views: 253 (including HTML, PDF, and XML)
Thereof 238 with geography defined
and 15 with unknown origin.
High-resolution weather data are crucial for many applications, typically generated via resource-intensive numerical models through dynamical downscaling. We developed an AI model using latent diffusion models (LDMs) to mimic this process, increasing weather data resolution over Italy from 25 to 2 km. LDM outperforms other methods, accurately capturing local patterns and extreme events. This approach offers a cost-effective alternative, with potential disruptive application in climate sciences.
High-resolution weather data are crucial for many applications, typically generated via...