Articles | Volume 12, issue 10
https://doi.org/10.5194/gmd-12-4185-2019
https://doi.org/10.5194/gmd-12-4185-2019
Model description paper
 | 
07 Oct 2019
Model description paper |  | 07 Oct 2019

Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0)

Seppo Pulkkinen, Daniele Nerini, Andrés A. Pérez Hortal, Carlos Velasco-Forero, Alan Seed, Urs Germann, and Loris Foresti

Model code and software

https://github.com/pySTEPS/pysteps/releases/tag/v1.0.0 S. Pulkkinen, D. Nerini, A. Perez Hortal, C. Velasco-Forero and L. Foresti https://doi.org/10.5281/zenodo.2631911

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Short summary
Reliable precipitation forecasts are vital for the society, as water-related hazards can cause economic losses and loss of lives. Pysteps is an open-source Python library for radar-based precipitation forecasting. It aims to be a well-documented platform for development of new methods as well as an easy-to-use tool for practitioners. The potential of the library is demonstrated by case studies and scientific experiments using radar data from Finland, Switzerland, the United States and Australia.