Skilful precipitation nowcasting using deep generative models of radar
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DOI: 10.1038/s41586-021-03854-z
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Cited by:
- Fenghua Ling & Jing-Jia Luo & Yue Li & Tao Tang & Lei Bai & Wanli Ouyang & Toshio Yamagata, 2022. "Multi-task machine learning improves multi-seasonal prediction of the Indian Ocean Dipole," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
- Xueliang Zhao & Qilong Sun & Xiaoguang Lin, 2023. "Physical Attention-Gated Spatial-Temporal Predictive Network for Weather Forecasting," Mathematics, MDPI, vol. 11(6), pages 1-10, March.
- Olivares, Kin G. & Meetei, O. Nganba & Ma, Ruijun & Reddy, Rohan & Cao, Mengfei & Dicker, Lee, 2024. "Probabilistic hierarchical forecasting with deep Poisson mixtures," International Journal of Forecasting, Elsevier, vol. 40(2), pages 470-489.
- Pan Xia & Lu Zhang & Min Min & Jun Li & Yun Wang & Yu Yu & Shengjie Jia, 2024. "Accurate nowcasting of cloud cover at solar photovoltaic plants using geostationary satellite images," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
- Aurélie Bouchard & Magalie Buguet & Adrien Chan-Hon-Tong & Jean Dezert & Philippe Lalande, 2023. "Comparison of different forecasting tools for short-range lightning strike risk assessment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1011-1047, January.
- Fuping Liu & Ying Liu & Chen Yang & Ruixun Lai, 2022. "A New Precipitation Prediction Method Based on CEEMDAN-IWOA-BP Coupling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4785-4797, September.
- Xiao-Yang Liu & Jingyang Rui & Jiechao Gao & Liuqing Yang & Hongyang Yang & Zhaoran Wang & Christina Dan Wang & Jian Guo, 2021. "FinRL-Meta: A Universe of Near-Real Market Environments for Data-Driven Deep Reinforcement Learning in Quantitative Finance," Papers 2112.06753, arXiv.org, revised Mar 2022.
- Chu, Yinghao & Wang, Yiling & Yang, Dazhi & Chen, Shanlin & Li, Mengying, 2024. "A review of distributed solar forecasting with remote sensing and deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
- Marino Marrocu & Luca Massidda, 2022. "Coupling a Neural Network with a Spatial Downscaling Procedure to Improve Probabilistic Nowcast for Urban Rain Radars," Forecasting, MDPI, vol. 4(4), pages 1-21, October.
- Bai, Mingliang & Yao, Peng & Dong, Haiyu & Fang, Zuliang & Jin, Weixin & Xusheng Yang, & Liu, Jinfu & Yu, Daren, 2024. "Spatial-temporal characteristics analysis of solar irradiance forecast errors in Europe and North America," Energy, Elsevier, vol. 297(C).
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