Changes between Version 1 and Version 2 of OMI_nondiagonal_observation_error_covariance_matrices


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Timestamp:
Sep 9, 2024, 8:41:10 AM (2 months ago)
Author:
lnerger
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  • OMI_nondiagonal_observation_error_covariance_matrices

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    11== Using non-diagonal R matrices with OMI ==
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    3 The default mode of PDAF-OMI is to use a diagonal observation error covariance matrix **R** and specifying the observation error variances, i.e. the diagonalof **R** only. This is in line with the common choice in data assimilation.
     3This feature was introduced with PDAF V2.3.
     4
     5The default mode of PDAF-OMI is to use a diagonal observation error covariance matrix **R** and specifying the observation error variances, i.e. the diagonalof **R** only. This is in line with the common choice in data assimilation to assume that observation errors are uncorrelated.
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     7However, there are also observation types with significant observation error correlations, which should be represented by a non-diagonal observation error covariance matrix. With PDAF V2.3 support for such nondiagonal **R** matrices was added to OMI.
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     9PDAF-OMIs support for nondiagonal **R**-matrices consists in given the user access to the routines that perform operations involve **R**. This differs with the filter type, e.g. in LESTKF and LETKF a produce of some matrix with the inverse of **R** ha sto be computed, while in the traditional, perturbed observations, EnKF the matrix **R** has to be added to some other matrix. For the particle filter and the NETF the computation of the likelihood involves **R**.
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