Articles | Volume 12, issue 4
Geosci. Model Dev., 12, 1387–1402, 2019
Geosci. Model Dev., 12, 1387–1402, 2019

Model description paper 09 Apr 2019

Model description paper | 09 Apr 2019

Optical flow models as an open benchmark for radar-based precipitation nowcasting (rainymotion v0.1)

Georgy Ayzel et al.

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Cited articles

Austin, G. L. and Bellon, A.: The use of digital weather radar records for short-term precipitation forecasting, Q. J. Roy. Meteor. Soc., 100, 658–664,, 1974. a, b
Ayzel, G.: hydrogo/rainymotion: rainymotion v0.1, Version v0.1, Zenodo,, 2019. a
Ayzel, G., Heistermann, M., and Winterrath, T.: rainymotion: python library for radar-based precipitation nowcasting based on optical flow techniques, available at: (last access: 28 March 2019), 2019. a, b, c, d
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55,, 2015. a
Bellerby, T. J.: High-resolution 2-D cloud-top advection from geostationary satellite imagery, IEEE T. Geosci. Remote, 44, 3639–3648,, 2006. a
Short summary
How much will it rain within the next hour? To answer this question, we developed rainymotion – an open source Python software library for precipitation nowcasting. In our benchmark experiments, including a state-of-the-art operational model, rainymotion demonstrated its ability to deliver timely and reliable nowcasts for a broad range of rainfall events. This way, rainymotion can serve as a baseline solution in the field of precipitation nowcasting.