Data Assimilation Stability
Data Assimilation Stability is a theoretical construct in numerical analysis that characterizes the robustness of a data assimilation algorithm in maintaining consistent and bounded state estimates under perturbations in observational or model inputs, distinguishing it from general numerical stability by its specific focus on the interaction between observational data and dynamical model fidelity.
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1.4K
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92
Authors
64
Institutions
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2017–2026
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The University of Sydney
Sydney, Australia
2 h-index
4 publications
99 citations
University of California San Diego
San Diego, United States
2 h-index
6 publications
138 citations
Institute of Atmospheric Sciences and Climate
Bologna, Italy
2 h-index
2 publications
96 citations

Xi'an Jiaotong University
Xi'an, China
2 h-index
5 publications
181 citations
Courant Institute of Mathematical Sciences
New York, United States
2 h-index
3 publications
119 citations
University of Reading
Reading, United Kingdom
2 h-index
7 publications
252 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
7 publications
357 citations
Laboratoire des Écoulements Géophysiques et Industriels
Grenoble, France
2 h-index
7 publications
279 citations
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7 publications · 181 citations
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2 publications · 36 citations
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2 publications · 64 citations
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2 publications · 202 citations
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1 publications · 44 citations
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