Articles | Volume 13, issue 6
© Author(s) 2020. This work is distributed underthe Creative Commons Attribution 4.0 License.
RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting
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26 citations as recorded by crossref.
- RAIN-F+: The Data-Driven Precipitation Prediction Model for Integrated Weather Observations Y. Choi et al. 10.3390/rs13183627
- Towards a More Realistic and Detailed Deep-Learning-Based Radar Echo Extrapolation Method Y. Hu et al. 10.3390/rs14010024
- HPC cluster-based user-defined data integration platform for deep learning in geoscience applications G. Li & Y. Choi 10.1016/j.cageo.2021.104868
- Real-Time Tephra Detection and Dispersal Forecasting by a Ground-Based Weather Radar M. Syarifuddin et al. 10.3390/rs13245174
- GAN–argcPredNet v1.0: a generative adversarial model for radar echo extrapolation based on convolutional recurrent units K. Zheng et al. 10.5194/gmd-15-1467-2022
- ConvLSTM Network-Based Rainfall Nowcasting Method with Combined Reflectance and Radar-Retrieved Wind Field as Inputs W. Liu et al. 10.3390/atmos13030411
- Performance Comparison between Deep Learning and Optical Flow-Based Techniques for Nowcast Precipitation from Radar Images M. Marrocu & L. Massidda 10.3390/forecast2020011
- RainPredRNN: A New Approach for Precipitation Nowcasting with Weather Radar Echo Images Based on Deep Learning D. Tuyen et al. 10.3390/axioms11030107
- SOPNet Method for the Fine-Grained Measurement and Prediction of Precipitation Intensity Using Outdoor Surveillance Cameras C. Lin et al. 10.1109/ACCESS.2020.3032430
- A Precipitation Nowcasting Mechanism for Real-World Data Based on Machine Learning Y. Xiang et al. 10.1155/2020/8408931
- Near real-time hurricane rainfall forecasting using convolutional neural network models with Integrated Multi-satellitE Retrievals for GPM (IMERG) product T. Kim et al. 10.1016/j.atmosres.2022.106037
- Use of Deep Learning for Weather Radar Nowcasting J. Cuomo & V. Chandrasekar 10.1175/JTECH-D-21-0012.1
- Effective training strategies for deep-learning-based precipitation nowcasting and estimation J. Ko et al. 10.1016/j.cageo.2022.105072
- Enhancing the Encoding-Forecasting Model for Precipitation Nowcasting by Putting High Emphasis on the Latest Data of the Time Step C. Jeong et al. 10.3390/atmos12020261
- Developing Deep Learning Models for Storm Nowcasting J. Cuomo & V. Chandrasekar 10.1109/TGRS.2021.3110180
- EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models – Part 1: Development of deep learning model J. Quinting & C. Grams 10.5194/gmd-15-715-2022
- SF-CNN: Signal Filtering Convolutional Neural Network for Precipitation Intensity Estimation C. Lin et al. 10.3390/s22020551
- Quantifying the Location Error of Precipitation Nowcasts A. Costa Tomaz de Souza et al. 10.1155/2020/8841913
- Deep Learning-Based Radar Composite Reflectivity Factor Estimations from Fengyun-4A Geostationary Satellite Observations F. Sun et al. 10.3390/rs13112229
- Nowcasting thunderstorm hazards using machine learning: the impact of data sources on performance J. Leinonen et al. 10.5194/nhess-22-577-2022
- Skilful precipitation nowcasting using deep generative models of radar S. Ravuri et al. 10.1038/s41586-021-03854-z
- Probabilistic Attenuation Nowcasting for the 5G Telecommunication Networks J. Pudashine et al. 10.1109/LAWP.2021.3068393
- DeePS at: A deep learning model for prediction of satellite images for nowcasting purposes V. Ionescu et al. 10.1016/j.procs.2021.08.064
- Very Short-term Prediction of Weather Radar-Based Rainfall Distribution and Intensity Over the Korean Peninsula Using Convolutional Long Short-Term Memory Network Y. Kim & S. Hong 10.1007/s13143-022-00269-2
- Reconstruction of Missing Data in Weather Radar Image Sequences Using Deep Neuron Networks L. Gao et al. 10.3390/app11041491
- RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting G. Ayzel et al. 10.5194/gmd-13-2631-2020
Latest update: 01 Jun 2023