| | 1 | = Features of PDAF = |
| | 2 | |
| | 3 | PDAF provides the following filter algorithms for data assimilation. All filters are fully implemented, optimized and parallelized. |
| | 4 | |
| | 5 | Local filters: |
| | 6 | * LSEIK (Nerger et al. (2006)) |
| | 7 | * LETKF (Hunt et al. (2007)) |
| | 8 | |
| | 9 | Global filters: |
| | 10 | * SEIK (Pham et al. (1998a, 2001), the implemented variant is more detailed described by Nerger et al. (2005)) |
| | 11 | * ETKF (The implementation follows Hunt et al. (2007) but without localization) |
| | 12 | * SEEK (The original formulation by Pham et al. (1998) |
| | 13 | * EnKF (The classical formulation with perturbed observations by Evensen (1994) |
| | 14 | |