Deep Learning Nowcasting
Deep Learning Nowcasting is a machine learning–based nowcasting framework that leverages deep neural networks to model spatiotemporal dynamics in radar data for the purpose of generating highly accurate short-term precipitation forecasts.
122
Publications
6.4K
Citations
474
Authors
183
Institutions
Publications per year
2017–2026
120
Parents
122
Skilful precipitation nowcasting using deep generative models of radar
Suman Ravuri, Karel Lenc, Matthew Willson et al. · Nature · 2021 · 916 citations · Full text
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
Xingjian Shi, Zhihan Gao, Leonard Lausen et al. · arXiv (Cornell University) · 2017 · 617 citations · Full text
A Deep Learning‐Based Methodology for Precipitation Nowcasting With Radar
Lei Chen, Yuan Cao, Leiming Ma et al. · Earth and Space Science · 2020 · 158 citations · Full text
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183

Harbin Institute of Technology
Harbin, China
9 h-index
35 publications
2.1K citations
Colorado State University
Fort Collins, United States
8 h-index
12 publications
617 citations

China Meteorological Administration
Beijing, China
6 h-index
16 publications
355 citations

Ocean University of China
Qingdao, China
5 h-index
17 publications
1.1K citations

Nanjing University of Information Science and Technology
Nanjing, China
5 h-index
17 publications
402 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
10 publications
249 citations

Babeș-Bolyai University
Cluj-Napoca, Romania
4 h-index
12 publications
198 citations
Meteorological Bureau of Shenzhen Municipality
Shenzhen, China
4 h-index
12 publications
425 citations
1–8 of 183
11 publications · 564 citations
11
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13 publications · 376 citations
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Repository · 8 publications · 763 citations
8
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8 publications · 315 citations
8
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6 publications · 251 citations
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