Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2737-2023
© Author(s) 2023. 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-16-2737-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
23 May 2023
Model experiment description paper |
| 23 May 2023
| 23 May 2023
CLGAN: a generative adversarial network (GAN)-based video prediction model for precipitation nowcasting
Yan Ji
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Michael Langguth
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Amirpasha Mozaffari
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Xiefei Zhi
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
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Cited
16 citations as recorded by crossref.
- Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall J. Ritvanen et al. 10.5194/gmd-18-1851-2025
- Enhancing Multiple Precipitation Data Integration Across a Large-Scale Area: A Deep Learning ResU-Net Framework Without Interpolation G. Noh & K. Ahn 10.1109/TGRS.2025.3538829
- ER-MACG: An Extreme Precipitation Forecasting Model Integrating Self-Attention Based on FY4A Satellite Data M. Lu et al. 10.3390/rs16203911
- Rainfall nowcasting models: state of the art and possible future perspectives D. De Luca et al. 10.1080/02626667.2025.2490780
- Generation of Synthetic Advanced Microwave Scanning Radiometer-2 23.8 GHz Dual-Polarization Measurements From Global Precipitation Measurement Microwave Imager Observations H. Ryu et al. 10.1109/TGRS.2025.3555803
- MAFNet: Multimodal Asymmetric Fusion Network for Radar Echo Extrapolation Y. Pei et al. 10.3390/rs16193597
- MT-GAN: A Multitask GAN for Severe Convective Weather Nowcasting L. Fan et al. 10.1109/LGRS.2024.3522463
- A Practical Online Incremental Learning Framework for Precipitation Nowcasting C. Luo et al. 10.1109/TGRS.2023.3330303
- CNN-Based Time Series Decomposition Model for Video Prediction J. Lee & G. Kim 10.1109/ACCESS.2024.3458460
- The Evolution of Generative AI: Trends and Applications M. Trigka & E. Dritsas 10.1109/ACCESS.2025.3574660
- Toward a Variation-Aware and Interpretable Model for Radar Image Sequence Prediction X. Huang et al. 10.1109/TII.2024.3399401
- Evaluation of IMERG Precipitation Product Downscaling Using Nine Machine Learning Algorithms in the Qinghai Lake Basin K. Lei et al. 10.3390/w17121776
- Downscaling of the surface temperature forecasts based on deep learning approaches G. Chen et al. 10.1002/met.70042
- Precipitation Nowcasting Based on Deep Learning over Guizhou, China D. Kong et al. 10.3390/atmos14050807
- Deep Learning for Daily 2‐m Temperature Downscaling S. Ding et al. 10.1029/2023EA003227
- A 3D-CNN and multi-loss video prediction architecture Z. Qin & Q. Dai 10.1007/s10489-025-06328-1
12 citations as recorded by crossref.
- Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall J. Ritvanen et al. 10.5194/gmd-18-1851-2025
- Enhancing Multiple Precipitation Data Integration Across a Large-Scale Area: A Deep Learning ResU-Net Framework Without Interpolation G. Noh & K. Ahn 10.1109/TGRS.2025.3538829
- ER-MACG: An Extreme Precipitation Forecasting Model Integrating Self-Attention Based on FY4A Satellite Data M. Lu et al. 10.3390/rs16203911
- Rainfall nowcasting models: state of the art and possible future perspectives D. De Luca et al. 10.1080/02626667.2025.2490780
- Generation of Synthetic Advanced Microwave Scanning Radiometer-2 23.8 GHz Dual-Polarization Measurements From Global Precipitation Measurement Microwave Imager Observations H. Ryu et al. 10.1109/TGRS.2025.3555803
- MAFNet: Multimodal Asymmetric Fusion Network for Radar Echo Extrapolation Y. Pei et al. 10.3390/rs16193597
- MT-GAN: A Multitask GAN for Severe Convective Weather Nowcasting L. Fan et al. 10.1109/LGRS.2024.3522463
- A Practical Online Incremental Learning Framework for Precipitation Nowcasting C. Luo et al. 10.1109/TGRS.2023.3330303
- CNN-Based Time Series Decomposition Model for Video Prediction J. Lee & G. Kim 10.1109/ACCESS.2024.3458460
- The Evolution of Generative AI: Trends and Applications M. Trigka & E. Dritsas 10.1109/ACCESS.2025.3574660
- Toward a Variation-Aware and Interpretable Model for Radar Image Sequence Prediction X. Huang et al. 10.1109/TII.2024.3399401
- Evaluation of IMERG Precipitation Product Downscaling Using Nine Machine Learning Algorithms in the Qinghai Lake Basin K. Lei et al. 10.3390/w17121776
4 citations as recorded by crossref.
- Downscaling of the surface temperature forecasts based on deep learning approaches G. Chen et al. 10.1002/met.70042
- Precipitation Nowcasting Based on Deep Learning over Guizhou, China D. Kong et al. 10.3390/atmos14050807
- Deep Learning for Daily 2‐m Temperature Downscaling S. Ding et al. 10.1029/2023EA003227
- A 3D-CNN and multi-loss video prediction architecture Z. Qin & Q. Dai 10.1007/s10489-025-06328-1
Latest update: 03 Nov 2025
Short summary
Formulating short-term precipitation forecasting as a video prediction task, a novel deep learning architecture (convolutional long short-term memory generative adversarial network, CLGAN) is proposed. A benchmark dataset is built on minute-level precipitation measurements. Results show that with the GAN component the model generates predictions sharing statistical properties with observations, resulting in it outperforming the baseline in dichotomous and spatial scores for heavy precipitation.
Formulating short-term precipitation forecasting as a video prediction task, a novel deep...
