FN Archimer Export Format
PT J
TI Data-Driven Interpolation of Sea Level Anomalies Using Analog Data Assimilation
BT 
AF Lguensat, Redouane
   Viet, Phi Huynh
   Sun, Miao
   Chen, Ge
   Fenglin, Tian
   Chapron, Bertrand
   Fablet, Ronan
AS 1:1;2:2;3:3;4:4;5:4;6:5;7:2;
FF 1:;2:;3:;4:;5:;6:PDG-ODE-LOPS-SIAM;7:;
C1 IGE, Université Grenoble Alpes, CNRS, IRD, Grenoble INP, 38000 Grenoble, France
   IMT Atlantique, Lab-STICC UMR CNRS 6285, UBL, 29200 Brest, France
   Key Laboratory of Digital Ocean, National Marine Data and Information Service, Tianjin 300171, China
   Department of Marine Information Technology, Ocean University of China, Qingdao 266100, China
   Laboratoire d’Océanographie Physique et Spatiale, IFREMER, 29200 Brest, France
C2 UNIV GRENOBLE ALPES, FRANCE
   IMT ATLANTIQUE, FRANCE
   NMDIS, CHINA
   UNIV OCEAN CHINA, CHINA
   IFREMER, FRANCE
SI BREST
SE PDG-ODE-LOPS-SIAM
UM LOPS
IN WOS Ifremer UMR
   DOAJ
   copubli-france
   copubli-univ-france
   copubli-int-hors-europe
   copubli-sud
IF 2.1
TC 15
UR https://archimer.ifremer.fr/doc/00489/60078/63402.pdf
LA English
DT Article
DE ;analog data assimilation;sea level anomaly;sea surface height;interpolation;data-driven methods
AB From the recent developments of data-driven methods as a means to better exploit large-scale observation, simulation and reanalysis datasets for solving inverse problems, this study addresses the improvement of the reconstruction of higher-resolution Sea Level Anomaly (SLA) fields using analog strategies. This reconstruction is stated as an analog data assimilation issue, where the analog models rely on patch-based and Empirical Orthogonal Functions (EOF)-based representations to circumvent the curse of dimensionality. We implement an Observation System Simulation Experiment (OSSE) in the South China Sea. The reported results show the relevance of the proposed framework with a significant gain in terms of Root Mean Square Error (RMSE) for scales below 100 km. We further discuss the usefulness of the proposed analog model as a means to exploit high-resolution model simulations for the processing and analysis of current and future satellite-derived altimetric data with regard to conventional interpolation schemes, especially optimal interpolation 
PY 2019
PD APR
SO Remote Sensing
SN 2072-4292
PU MDPI AG
VL 11
IS 7
UT 000465549300123
DI 10.3390/rs11070858
ID 60078
ER

EF