FN Archimer Export Format
PT CHAP
TI Constrained Random Diffeomorphisms for Data Assimilation
BT 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
AF Resseguier, Valentin
   Zhen, Yicun
   CHAPRON, Bertrand
AS 1:1,2;2:3;3:4;
FF 1:;2:;3:PDG-ODE-LOPS-SIAM;
C1 INRAE,OPAALE,Rennes,France
   LAB,SCALIANDS,Rennes,France
   Department of Oceanography, Hohai University, Nanjing,China
   Laboratoire d’Océanographie Physique et Spatiale(LOPS),Ifremer,Plouzané,France
C2 INRAE, FRANCE
   SCALIAN, FRANCE
   UNIV HOHAI, CHINA
   IFREMER, FRANCE
SI BREST
SE PDG-ODE-LOPS-SIAM
UM LOPS
UR https://archimer.ifremer.fr/doc/00856/96752/105299.pdf
LA English
DT Book section
AB 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. 
PY 2024
DI 10.1007/978-3-031-40094-0_13
ID 96752
ER

EF