Machine Learning Nowcasting
Machine Learning Nowcasting is a computational framework within radar nowcasting that employs machine learning algorithms to model and predict short-term spatiotemporal evolution of atmospheric phenomena directly from observational data, distinguishing itself from traditional numerical or extrapolation-based methods through data-driven learning of complex non-linear dynamics.
42
Publications
1.7K
Citations
157
Authors
82
Institutions
Publications per year
2017–2026
38
Parents
42
1–5 of 42
157
Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland
3 publications · 120 citations
3
h-index
2
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2
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2
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2
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1–5 of 157
82
Federal Office of Meteorology and Climatology MeteoSwiss
Zurich, Switzerland
3 h-index
10 publications
424 citations
ETH Zurich
Zurich, Switzerland
2 h-index
3 publications
186 citations
CESI (Italy)
Milan, Italy
2 h-index
2 publications
52 citations

Reserve Bank of New Zealand
Wellington, New Zealand
2 h-index
6 publications
408 citations
University of Alabama in Huntsville
Huntsville, United States
2 h-index
2 publications
56 citations
University of Iowa
Iowa City, United States
2 h-index
6 publications
114 citations
University of Bergen
Bergen, Norway
2 h-index
3 publications
116 citations

International Monetary Fund
Washington D.C., United States
2 h-index
3 publications
196 citations
1–8 of 82
3 publications · 97 citations
3
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2 publications · 36 citations
2
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2 publications · 75 citations
2
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2 publications · 423 citations
2
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Repository · 2 publications · 28 citations
2
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1–5