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Multiplicative Non‐Gaussian Model Error Estimation in Data Assimilation

Abstract Model uncertainty quantification is an essential component of effective data assimilation. Model errors associated with sub‐grid scale processes are often represented through stochastic parameterizations of the unresolved process. Many existing Stochastic Parameterization schemes are only a...

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Principais autores: S. Pathiraja, P. J. vanLeeuwen
Format: Artigo
Sprog:Inglês
Udgivet: American Geophysical Union (AGU) 2022-04-01
Serier:Journal of Advances in Modeling Earth Systems
Fag:
model uncertainty
non‐Gaussian
data‐driven
uncertainty quantification
Lorenz 96
sub‐grid scale
Online adgang:https://doi.org/10.1029/2021MS002564
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