| Table of Contents | ||
|---|---|---|
|
1. Forecast system version
System name: GCFS 2.0
First operational forecast run: April 2018
2. Configuration of the forecast model
Is it a coupled model? Yes
Coupling frequency: 1 hour (Better use more specific question? Here or elsewhere?)
2.1 Atmosphere and land surface
| Model | ECHAM 6.3.04 (atmosphere) JSBACH (land) |
|---|---|
| Horizontal resolution and grid | T127 (~100 km) on regular Gaussian grid |
| Atmosphere vertical resolution | L95 |
| Top of atmosphere | 0.01 hPa |
| Soil levels | 5 Level 1: 0 - 0.065 m Level 2: 0.065 - 0.319 m Level 3: 0.319 - 1.232 m Level 4: 1.232 - 4.134 m Level 5: 4.134 - 9.834 m |
| Time step | 200 s |
Detailed documentation:
ECHAM6: Stevens et al., 2013
Soil scheme: Hagemann and Stacke, 2014
Runoff scheme: HD : Hagemann and Dümenil-Gates, 2003
More model details? (e.g. land surface model?)
...
2.2 Ocean and cryosphere
| Ocean model | MPIOM 1.6.3 |
|---|---|
| Horizontal resolution | TP04 (0.4°) on a tripolar grid |
| Vertical resolution | L40 |
| Time step | 1 h |
| Sea ice model | Thermodynamic and sea-ice dynamics |
| Sea ice model resolution | same as ocean model |
| Sea ice model levels | zero-layer model |
| Wave model | NA |
| Wave model resolution | NA |
Detailed documentation: MPIOM: Jungclaus et al., 2013
3. Initialization and initial condition (IC) perturbations
3.1 Atmosphere and land
| Hindcast | Forecast | |
|---|---|---|
| Atmosphere initialization | ERA-InterimIFS-Analyses | ECMWF operations |
| Atmosphere IC perturbations | none | none |
Land Initialization | indirect via atmosphere initialization | indirect via atmosphere initialization |
| Land IC perturbations | none | none |
| Soil moisture initialization | indirect via atmosphere initialization | indirect via atmosphere initialization |
| Snow initialization | indirect via atmosphere initialization | indirect via atmosphere initialization |
| Unperturbed control forecast? | yes | yes |
Detailed documentation:
More DA details?
The assimilation for the atmosphere employs Newtonian relaxation of the reference data with the following variable dependend -dependent relaxation times:
- Divergence divergence (48 hrs)
- Vorticity vorticity (6hrs)
- Temperature temperature (24hrs~4hrs)
- logarithm of surface pressure (24 ~4 hrs)
Data assimilation method for control analysis: no ensemble data assimilation
Horizontal and vertical resolution of perturbations:
Perturbations in +/- pairs:
3.2 Ocean and cryosphere
| Hindcast | Forecast | |
|---|---|---|
| Ocean initialization | ORAS5 | 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 | ||
| Unperturbed control forecast? | yes | yes |
|---|
Detailed documentation:
GCFS More ocean data assimilation details: Baehr & Piontek, 2014
More ocean data assimilation details?
- Assimilation of 3D temperature and salinity (ORAS5 data) using Newtonian relaxation with ~10 days of relaxation time
- Assimilation of sea-ice concentration ( coming from ORAS5 data) using Newtonian relaxation with ~20 days of relaxation time
Source and treatment of SST? (Other data sources - altimetry?)Detailed documentation:GCFS ocean data assimilation: Baehr & Piontek, 2014
4. 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 forecast |
Detailed documentation: Baehr et al. (2015)
5. Forecast system and hindcasts
| Forecast frequency | monthly |
|---|---|
| Forecast ensemble size | 50 |
| Hindcast years | 1993 - 2017 |
| Hindcast ensemble size | 30 |
| On-the-fly or static hindcast set? | static |
6. Other relevant information
The forcing database for radiative parameters like ozone, aerosol and greenhouse gases is provided by CMIP6 for the historical period up to 2014. Afterwards, values are kept constant as CMIP6 future scenarios were not yet available.