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 …

Particle filtering in high-dimensional chaotic systems

N Lingala, N Sri Namachchivaya… - … Journal of Nonlinear …, 2012 - pubs.aip.org
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 …

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 …

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 …

[ALINTI][C] UNIVERSITY OF ILLINOIS CHAMPAIGN