GPTCast: a weather language model for precipitation nowcasting

Franch, Gabriele; Tomasi, Elena; Wanjari, Rishabh; Poli, Virginia; Cardinali, Chiara; Alberoni, Pier Paolo; Cristoforetti, Marco

doi:https://doi.org/10.5194/gmd-18-5351-2025

Articles | Volume 18, issue 16

https://doi.org/10.5194/gmd-18-5351-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-18-5351-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 16

Model description paper

| Highlight paper

|

27 Aug 2025

Model description paper | Highlight paper |

| 27 Aug 2025

GPTCast: a weather language model for precipitation nowcasting

Gabriele Franch, Elena Tomasi, Rishabh Wanjari, Virginia Poli, Chiara Cardinali, Pier Paolo Alberoni, and Marco Cristoforetti

Data sets

Dataset for "GPTCast: a weather language model for precipitation nowcasting" Gabriele Franch et al. https://doi.org/10.5281/zenodo.13692016

Model code and software

Code for "GPTCast: a weather language model for precipitation nowcasting" Gabriele Franch et al. https://doi.org/10.5281/zenodo.13832526

Pretrained models for "GPTCast: a weather language model for precipitation nowcasting" Gabriele Franch et al. https://doi.org/10.5281/zenodo.13594332

PyTorch Lightning W. Falcon and The PyTorch Lightning team https://doi.org/10.5281/zenodo.3828935

Executive editor

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.