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Book Sections Year : 2023

Stochastic Parameterization with Dynamic Mode Decomposition

Abstract

Abstract A physical stochastic parameterization is adopted in this work to account for the effects of the unresolved small-scale on the large-scale flow dynamics. This random model is based on a stochastic transport principle, which ensures a strong energy conservation. The dynamic mode decomposition (DMD) is performed on high-resolution data to learn a basis of the unresolved velocity field, on which the stochastic transport velocity is expressed. Time-harmonic property of DMD modes allows us to perform a clean separation between time-differentiable and time-decorrelated components. Such random scheme is assessed on a quasi-geostrophic (QG) model.
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Dates and versions

hal-03910774 , version 1 (23-01-2023)

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Long Li, Etienne Mémin, Gilles Tissot. Stochastic Parameterization with Dynamic Mode Decomposition. Stochastic Transport in Upper Ocean Dynamics, 10, Springer International Publishing, pp.179-193, 2023, Mathematics of Planet Earth, ⟨10.1007/978-3-031-18988-3_11⟩. ⟨hal-03910774⟩
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