Constrained Random Diffeomorphisms for Data Assimilation

Type Book section
Date 2024
Language English
Author(s) Resseguier Valentin1, 2, Zhen Yicun3, Chapron BertrandORCID4
Affiliation(s) 1 : INRAE,OPAALE,Rennes,France
2 : LAB,SCALIANDS,Rennes,France
3 : Department of Oceanography, Hohai University, Nanjing,China
4 : Laboratoire d’Océanographie Physique et Spatiale(LOPS),Ifremer,Plouzané,France
Book Chapron, B., Crisan, D., Holm, D., Mémin, E., Radomska, A. (eds) Stochastic Transport in Upper Ocean Dynamics II. STUOD 2022. Part of the Mathematics of Planet Earth book series (MPE,volume 11).. Springer, Cham. Print ISBN 978-3-031-40093-3 Online ISBN 978-3-031-40094-0, 10.1007/978-3-031-40094-0_13, pp.281-292
DOI 10.1007/978-3-031-40094-0_13
Abstract

For ensemble-based data assimilation purposes, there is a definite need for relevant ensemble sampling tools. Indeed, the quality and spreading of these ensembles have deep implications in the quality of the data assimilation, and—until recently—those so-called covariance inflation tools have mostly relied on unsuitable linear Gaussian frameworks. A promising alternative is the generation of ensembles through a stochastic remapping of the physical space.
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Resseguier Valentin, Zhen Yicun, Chapron Bertrand (2024). Constrained Random Diffeomorphisms for Data Assimilation. In Chapron, B., Crisan, D., Holm, D., Mémin, E., Radomska, A. (eds) Stochastic Transport in Upper Ocean Dynamics II. STUOD 2022. Part of the Mathematics of Planet Earth book series (MPE,volume 11).. Springer, Cham. Print ISBN 978-3-031-40093-3 Online ISBN 978-3-031-40094-0, 10.1007/978-3-031-40094-0_13, pp.281-292 (Springer Nature Switzerland). https://archimer.ifremer.fr/doc/00856/96752/