Changes between Version 12 and Version 13 of OMI_nondiagonal_observation_error_covariance_matrices


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Timestamp:
May 25, 2025, 7:33:21 PM (5 days ago)
Author:
lnerger
Comment:

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  • OMI_nondiagonal_observation_error_covariance_matrices

    v12 v13  
    3838This feature was introduced with PDAF V2.3.
    3939
     40|| The PDAF3 interface introduced by PDAF3 also provides support for non-diagonal R matrices. For details, see the [wiki:nondiagonal_observation_error_covariance_matrices_PDAF3 page on PDAF3 assimialtion interface for non-diagonal R matrices] ||
     41
    4042The 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.
    4143
    4244However, 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.
    4345
    44 PDAF-OMI's 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**.
    45 
    46 
     46To support nondiagonal **R**-matrices consists in giving the user access to the routines that perform operations involving **R**. The operations dedepend on the filter type, e.g. in LESTKF and LETKF a product of some matrix with the inverse of **R** has to be computed, while in the traditional, perturbed observations, EnKF the matrix **R** has to be added to some other matrix. For the particle filter, the NETF and the hybrid filter LKNETF, the computation of the likelihood involves **R**.
    4747
    4848== Routines to perform the analysis step ==