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    Mitigating Observation Perturbation Sampling Errors in the Stochastic EnKF

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    Type
    Article
    Authors
    Hoteit, Ibrahim cc
    Pham, D.-T.
    El Gharamti, Mohamad cc
    Luo, X.
    KAUST Department
    Earth Fluid Modeling and Prediction Group
    Earth Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2015-04-06
    Online Publication Date
    2015-04-06
    Print Publication Date
    2015-07
    Permanent link to this record
    http://hdl.handle.net/10754/565937
    
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    Abstract
    The stochastic ensemble Kalman filter (EnKF) updates its ensemble members with observations perturbed with noise sampled from the distribution of the observational errors. This was shown to introduce noise into the system and may become pronounced when the ensemble size is smaller than the rank of the observational error covariance, which is often the case in real oceanic and atmospheric data assimilation applications. This work introduces an efficient serial scheme to mitigate the impact of observations’ perturbations sampling in the analysis step of the EnKF, which should provide more accurate ensemble estimates of the analysis error covariance matrices. The new scheme is simple to implement within the serial EnKF algorithm, requiring only the approximation of the EnKF sample forecast error covariance matrix by a matrix with one rank less. The new EnKF scheme is implemented and tested with the Lorenz-96 model. Results from numerical experiments are conducted to compare its performance with the EnKF and two standard deterministic EnKFs. This study shows that the new scheme enhances the behavior of the EnKF and may lead to better performance than the deterministic EnKFs even when implemented with relatively small ensembles.
    Citation
    Mitigating Observation Perturbation Sampling Errors in the Stochastic EnKF 2015, 143 (7):2918 Monthly Weather Review
    Publisher
    American Meteorological Society
    Journal
    Monthly Weather Review
    DOI
    10.1175/MWR-D-14-00088.1
    Additional Links
    http://journals.ametsoc.org/doi/abs/10.1175/MWR-D-14-00088.1
    ae974a485f413a2113503eed53cd6c53
    10.1175/MWR-D-14-00088.1
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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