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A suboptimal data assimilation algorithm based on the ensemble Kalman filter
Author(s) -
Klimova Ekaterina
Publication year - 2012
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.1941
Subject(s) - data assimilation , ensemble kalman filter , kalman filter , fast kalman filter , algorithm , covariance , computer science , covariance matrix , covariance intersection , assimilation (phonology) , invariant extended kalman filter , extended kalman filter , ensemble learning , mathematics , artificial intelligence , statistics , meteorology , geography , linguistics , philosophy
A suboptimal algorithm for data assimilation based on the ensemble Kalman filter (EnKF) is proposed. An advantage of the algorithm is that it does not require an additional calculation of the ensemble of perturbations that correspond to the analysis‐error covariance matrix because it is calculated automatically with this algorithm. The operation count of the algorithm is close to that of the local ensemble transform Kalman filter (LETKF), but its formulae are different from those of the LETKF. Copyright © 2012 Royal Meteorological Society