...
| Hindcast | Forecast | |||
|---|---|---|---|---|
| Ocean initialization | ORAS5 | Ensemble Kalman Filter (LSEIK, Nerger et al., 2006), adapted to MPIOM (Brune and Baehr, 2020) using EN4 data | Ensemble Kalman Filter (LSEIK, Nerger et al., 2006), adapted to MPIOM (Brune and Baehr, 2020) using ARGO data ORAS5 | |
| Ocean IC perturbations | The very first hindcast ensemble in 1990 starts with lagged initialisation of the 30 members by each one day. Subsequently, bred vectors add small disturbances to the global three-dimensional ocean temperature and salinity fields | bred vectors add small disturbances to the global three-dimensional ocean temperature and salinity fields | via the Kalman Filter | via the Kalman Filter |
| Unperturbed control forecast? | yesnoyes | no |
More ocean data assimilation details:
- Assimilation of 3D temperature and salinity (ORAS5 data) using Newtonian relaxation with ~10 days of relaxation timeusing EN4
- Assimilation of sea-ice concentration (ORAS5 data) using Newtonian relaxation with ~20 days of relaxation timeusing OSISAF
Detailed documentation: GCFS ocean data assimilation: Brune and Baehr & Piontek, 20142020
5. Model uncertainties perturbations:
| Model dynamics perturbations | no |
|---|---|
| Model physics perturbations | atmosphere: perturbation of diffusion in uppermost layer |
If there is a control forecast, is it perturbed? | unperturbed control forecastno |
Detailed documentation: Baehr et al. (2015)
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Interpolation details
Horizontal Interpolation
| Distance weighting | Bilinear | Nearest neighbour |
|---|---|---|
| soil temperature | orography | land sea mask |
| sea surface temperature | all other variables | sea ice temperature |
| (sub)surface runoff |
Vertical interpolation
8. Where to find more information
www.dwd.de/seasonalforecastsclimatepredictions