Articles | Volume 12, issue 4
https://doi.org/10.5194/gmd-12-1387-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-1387-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
09 Apr 2019
Model description paper |
| 09 Apr 2019
| 09 Apr 2019
Optical flow models as an open benchmark for radar-based precipitation nowcasting (rainymotion v0.1)
Institute for Environmental Sciences and Geography, University of Potsdam, Potsdam, Germany
Maik Heistermann
Institute for Environmental Sciences and Geography, University of Potsdam, Potsdam, Germany
Tanja Winterrath
Department of Hydrometeorology, Deutscher Wetterdienst, Offenbach, Germany
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- Developing Deep Learning Models for Storm Nowcasting J. Cuomo & V. Chandrasekar 10.1109/TGRS.2021.3110180
- CLGAN: a generative adversarial network (GAN)-based video prediction model for precipitation nowcasting Y. Ji et al. 10.5194/gmd-16-2737-2023
- Enhancing Rainfall Nowcasting Using Generative Deep Learning Model with Multi-Temporal Optical Flow J. Ha & H. Lee 10.3390/rs15215169
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- TPDTC-Net: A Decoupled Spatial–Temporal Network for Precipitation Nowcasting C. Deng et al. 10.1109/TGRS.2025.3611969
- Scale‐dependent blending of ensemble rainfall nowcasts and numerical weather prediction in the open‐source pysteps library R. Imhoff et al. 10.1002/qj.4461
- Reconstruction of Missing Data in Weather Radar Image Sequences Using Deep Neuron Networks L. Gao et al. 10.3390/app11041491
- Residual Spatiotemporal Convolutional Neural Network Based on Multisource Fusion Data for Approaching Precipitation Forecasting T. Zhang et al. 10.3390/atmos15060628
- A Radar Reflectivity Image Prediction Method: The Spatial MIM + Pix2Pix J. Guo et al. 10.3390/rs15235554
- Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events G. Franch et al. 10.3390/atmos11030267
- Spatiotemporal Optimization for Short-Term Solar Forecasting Based on Satellite Imagery M. Oh et al. 10.3390/en14082216
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- A Systematic Modular Approach for the Coupling of Deep-Learning-Based Models to Forecast Urban Flooding Maps in Early Warning Systems J. Koltermann da Silva et al. 10.3390/hydrology11120215
- RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting G. Ayzel et al. 10.5194/gmd-13-2631-2020
- STFF-UNet: a spatio-temporal feature fusion UNet model for short-term precipitation forecasting X. Du et al. 10.1007/s12145-025-01882-1
- A spatiotemporal mixed-enhanced generative adversarial network for radar-based precipitation nowcasting L. He et al. 10.1016/j.cageo.2025.105919
- TISE-LSTM: A LSTM model for precipitation nowcasting with temporal interactions and spatial extract blocks C. Zheng et al. 10.1016/j.neucom.2024.127700
- MSLKNet: A Multi-Scale Large Kernel Convolutional Network for Radar Extrapolation W. Tian et al. 10.3390/atmos15010052
- Weather Radar Echo Extrapolation with Dynamic Weight Loss Y. Zhang et al. 10.3390/rs15123138
- TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting G. Franch et al. 10.1038/s41597-020-0574-8
- Cloud Nowcasting with Structure-Preserving Convolutional Gated Recurrent Units S. Kellerhals et al. 10.3390/atmos13101632
- A two-stage trained hybrid Unet-ConvLSTM2D for enhanced precipitation nowcasting F. Naz et al. 10.1016/j.envsoft.2025.106532
- MPFNet: Multiproduct Fusion Network for Radar Echo Extrapolation Y. Pei et al. 10.1109/TGRS.2024.3496081
- Hybrid physics-AI outperforms numerical weather prediction for extreme precipitation nowcasting P. Das et al. 10.1038/s41612-024-00834-8
- PFformer: A Time-Series Forecasting Model for Short-Term Precipitation Forecasting L. Xu et al. 10.1109/ACCESS.2024.3458055
- RadarDiT: An advanced radar echo extrapolation model for three gorges reservoir area via diffusion transformer J. Wan et al. 10.1016/j.ejrh.2025.102703
- STUNNER: Radar Echo Extrapolation Model Based on Spatiotemporal Fusion Neural Network W. Fang et al. 10.1109/TGRS.2023.3268187
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Discussed (final revised paper)
Discussed (preprint)
Latest update: 07 Oct 2025
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.
How much will it rain within the next hour? To answer this question, we developed rainymotion...
