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Data assimilation experiments using diffusive back-and-forth nudging for the NEMO ocean model
GA Ruggiero, Y Ourmieres, E Cosme… - Nonlinear Processes …, 2015 - npg.copernicus.org
The diffusive back-and-forth nudging (DBFN) is an easy-to-implement iterative data
assimilation method based on the well-known nudging method. It consists of a sequence of …
assimilation method based on the well-known nudging method. It consists of a sequence of …
Particle filtering in high-dimensional chaotic systems
We present an efficient particle filtering algorithm for multiscale systems, which is adapted
for simple atmospheric dynamics models that are inherently chaotic. Particle filters represent …
for simple atmospheric dynamics models that are inherently chaotic. Particle filters represent …
Unsupervised learning grou**-based resampling for particle filters
W Yang, L Song, CAT Tee, Y Zheng, Y Liu - IEEE Access, 2019 - ieeexplore.ieee.org
Conventional resampling for particle filters suffers from discarding much potentially useful
information due to using less information of spatial distribution of sampling particles set. An …
information due to using less information of spatial distribution of sampling particles set. An …
A comparative study of data assimilation methods for oceanic models
GAAR Ruggiero - 2014 - theses.hal.science
This thesis developed and implemented iterative data assimilation algorithms for a primitive
equation ocean model, and compared them with other well established DA methods such as …
equation ocean model, and compared them with other well established DA methods such as …