Variational Data Assimilation
Variational Data Assimilation is a data assimilation method that belongs to the class of optimization-based techniques, distinguished by its formulation of the state estimation problem as a variational problem where an objective functional, measuring the discrepancy between observations and model predictions weighted by their uncertainties, is minimized to obtain the optimal initial conditions for a numerical model.
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Authors
725
Institutions
Publications per year
2017–2026
218
Parents
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The AROME-France Convective-Scale Operational Model
Yann Seity, Pierre Brousseau, Sylvie Malardel et al. · Monthly Weather Review · 2010 · 1.1K citations · Full text
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European Centre for Medium-Range Weather Forecasts, United Kingdom
26 publications · 5.4K citations
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NSF National Center for Atmospheric Research, United States
21 publications · 2K citations
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NSF National Center for Atmospheric Research
Boulder, United States
51 h-index
230 publications
32.6K citations

European Centre for Medium-Range Weather Forecasts
Reading, United Kingdom
45 h-index
210 publications
28.2K citations

Centre National de la Recherche Scientifique
Paris, France
35 h-index
180 publications
9.4K citations
Met Office
Exeter, United Kingdom
33 h-index
153 publications
20.6K citations
Météo-France
Toulouse, France
32 h-index
114 publications
14.6K citations
University of Oklahoma
Norman, United States
26 h-index
90 publications
5.5K citations
Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique
Toulouse, France
25 h-index
67 publications
4K citations
Florida State University
Tallahassee, United States
25 h-index
59 publications
2.8K citations
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220 publications · 17K citations
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169 publications · 16.4K citations
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77 publications · 5.8K citations
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JGR · 60 publications · 4.5K citations
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28 publications · 2K citations
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