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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: (Better use more specific question? Here or elsewhere?) 1 hour
2.1 Atmosphere and land surface
Model | ECHAM 6.3.04 (atmosphere) JSBACH (land) |
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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:
More model details? (e.g. land surface model?)
ECHAM6: Stevens et al., 2013
Soil scheme: Hagemann and Stacke, 2014
Runoff scheme: HD Hagemann and Dümenil-Gates, 2003
2.2
...
Ocean and cryosphere
Ocean model | NEMO v3.4MPIOM 1.6.3 |
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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: NEMO documentation : MPIOM: Jungclaus et al., 2013
3. Initialization and initial condition (IC) perturbations
3.1 Atmosphere and land
Hindcast | Forecast | |
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Atmosphere initialization | ERA-Interim | 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? |
Detailed documentation:
yes | yes |
The assimilation for the atmosphere employs Newtonian relaxation of the reference data with the following variable-dependent relaxation times:
- divergence (48 hrs)
- vorticity (6hrs)
- temperature (~4hrs)
- logarithm of surface pressure (~4 hrs)
...
Data assimilation method for control analysis:
Horizontal and vertical resolution of perturbations: T42L91 SVs+ T399L137 EDA perturbations
Perturbations in +/- pairs: Yes
no ensemble data assimilation
3.2 Ocean and cryosphere
Hindcast | Forecast | |
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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 |
More ocean data assimilation details?Source and treatment of SST? (Other data sources - altimetry?):
- Assimilation of 3D temperature and salinity (ORAS5 data) using Newtonian relaxation with ~10 days of relaxation time
- Assimilation of sea-ice concentration (ORAS5 data) using Newtonian relaxation with ~20 days of relaxation time
Detailed documentation: GCFS ocean data assimilation: Baehr & Piontek, 2014
4. Model uncertainties perturbations:
Model dynamics perturbations | no |
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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 |
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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.