17 | | Special cases like data assimilation with a fixed covariance matrix or a static covariance matrix are also supported in PDAF. In case of a fixed covariance matrix one obtains an ensemble optimal interpolation (ensemble OI) algorithm in which the covariance matrix from the initialization is used for all filter analysis steps. With a static covariance matrix, the ensemble members representing the covariance matrix are updated during the analysis step. However, in the forecast phase only the ensemble mean state is integrated by the model. These special cases are currently only provided with the ESTKF, SEEK, SEIK and LSEIK filters. They can be selected by specifying `subtype=2` for the static covariance matrix and `subtype=3` for the fixed covariance matrix. As the ensemble members are not integrated in these cases, the improved ensemble transformation of the ESTKF would not change the results. |
| 17 | Special cases like data assimilation with a fixed covariance matrix or a static covariance matrix are also supported in PDAF. In case of a fixed covariance matrix one obtains an ensemble optimal interpolation (ensemble OI) algorithm in which the covariance matrix from the initialization is used for all filter analysis steps. With a static covariance matrix, the ensemble members representing the covariance matrix are updated during the analysis step. However, in the forecast phase only the ensemble mean state is integrated by the model. These special cases are provided for all filters, except EnKF, LEnKF, and the weight-based filters NETF, LNETF, and PF. They can be selected by specifying `subtype=2` for the static covariance matrix and `subtype=3` for the fixed covariance matrix. |