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

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

doi:https://doi.org/10.5194/gmd-12-4185-2019

Articles | Volume 12, issue 10

https://doi.org/10.5194/gmd-12-4185-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-12-4185-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 10

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

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Final revised paper (published on 07 Oct 2019)
Preprint (discussion started on 13 May 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Clear and Comprehensive Description of an Open-Source Nowcast System', Wang Chun Woo, 11 Jun 2019
RC2: 'review', Anonymous Referee #2, 21 Jun 2019
AC1: 'Response to reviewers', Seppo Pulkkinen, 06 Aug 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Seppo Pulkkinen on behalf of the Authors (08 Aug 2019) Author's response Manuscript

ED: Publish as is (25 Aug 2019) by Richard Neale

AR by Seppo Pulkkinen on behalf of the Authors (01 Sep 2019) Manuscript

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.