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: 2,577 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,472
80
25
2,577
29
28
HTML: 2,472
PDF: 80
XML: 25
Total: 2,577
BibTeX: 29
EndNote: 28
Views and downloads (calculated since 10 Oct 2024)
Cumulative views and downloads
(calculated since 10 Oct 2024)
Total article views: 2,179 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,080
80
19
2,179
29
28
HTML: 2,080
PDF: 80
XML: 19
Total: 2,179
BibTeX: 29
EndNote: 28
Views and downloads (calculated since 27 Aug 2025)
Cumulative views and downloads
(calculated since 27 Aug 2025)
Total article views: 398 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
392
0
6
398
0
0
HTML: 392
PDF: 0
XML: 6
Total: 398
BibTeX: 0
EndNote: 0
Views and downloads (calculated since 10 Oct 2024)
Cumulative views and downloads
(calculated since 10 Oct 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: 2,577 (including HTML, PDF, and XML)
Thereof 2,502 with geography defined
and 75 with unknown origin.
Total article views: 2,179 (including HTML, PDF, and XML)
Thereof 2,115 with geography defined
and 64 with unknown origin.
Total article views: 398 (including HTML, PDF, and XML)
Thereof 387 with geography defined
and 11 with unknown origin.
The application of machine learning techniques to weather forecasting is an exceptionally promising area for this technology. This paper presents an LLM nowcasting tool which outperforms existing technology for short term precipitation forecasting. This is an exciting demonstrator of the possibilities of this novel approach.
The application of machine learning techniques to weather forecasting is an exceptionally...
Our research introduces GPTCast, a novel method for very short term precipitation forecasting using radar data. By applying advanced machine learning techniques inspired by large language models, we developed a system that generates accurate and realistic weather predictions. We trained the model using 6 years of radar data from northern Italy, demonstrating its superior performance over leading ensemble extrapolation methods.
Our research introduces GPTCast, a novel method for very short term precipitation forecasting...