Physics-based Forecasting Models
Physics-Based Forecasting Models is a forecasting methodology that belongs to the class of predictive models and is distinguished by its reliance on fundamental physical laws and governing equations of the system to simulate and predict production behavior.
88
Publications
5K
Citations
523
Authors
212
Institutions
Publications per year
2017–2026
71
Variants
Physics-based Forecasting Model
Parents
88
Seasonal Arctic sea ice forecasting with probabilistic deep learning
Tom R. Andersson, J. Scott Hosking, María Pérez‐Ortiz et al. · Nature Communications · 2021 · 279 citations · Full text
Deep learning for twelve hour precipitation forecasts
Lasse Espeholt, Shreya Agrawal, Casper Kaae Sønderby et al. · Nature Communications · 2022 · 238 citations · Full text
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212
Stanford University
Stanford, United States
5 h-index
10 publications
1.5K citations

European Centre for Medium-Range Weather Forecasts
Reading, United Kingdom
5 h-index
10 publications
1.2K citations
University of Washington
Seattle, United States
4 h-index
4 publications
349 citations
ETH Zurich
Zurich, Switzerland
4 h-index
4 publications
317 citations
Loughborough University
Loughborough, United Kingdom
4 h-index
4 publications
429 citations

National Taiwan University
Taipei, Taiwan
3 h-index
10 publications
343 citations
KU Leuven
Leuven, Belgium
3 h-index
11 publications
671 citations
National Centre for Atmospheric Science
Leeds, United Kingdom
3 h-index
5 publications
364 citations
1–8 of 212
Repository · 5 publications · 146 citations
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3 publications · 128 citations
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3 publications · 113 citations
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3 publications · 119 citations
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3 publications · 54 citations
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