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| Lguensat, Redouane; Viet, Phi Huynh; Sun, Miao; Chen, Ge; Fenglin, Tian; Chapron, Bertrand; Fablet, Ronan. |
| 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... |
| Tipo: Text |
Palavras-chave: Analog data assimilation; Sea level anomaly; Sea surface height; Interpolation; Data-driven methods. |
| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00489/60078/63402.pdf |
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| Fablet, Ronan; Viet, P.; Lguensat, R.; Chapron, Bertrand. |
| We address in this paper the reconstruction of irregurlarlysampled image time series with an emphasis on geophysical remote sensing data. We develop a data-driven approach, referred to as an analog assimilation and stated as an ensemble Kalman method. Contrary to model-driven assimilation models, we do not exploit a physically-derived dynamic prior but we build a data-driven dynamic prior from a representative dataset of the considered image dynamics. Our contribution is here to extend analog assimilation to images, which involve high-dimensional state space.We combine patch-based representations to a multiscale PCA-constrained decomposition. Numerical experiments for the interpolation of missing data in satellite-derived ocean remote sensing images... |
| Tipo: Text |
Palavras-chave: Data assimilation; Irregular sampling; Image time series; Data-driven methods; Kalman methods. |
| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00403/51440/52009.pdf |
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