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1. Forecast system version
System name: CMCC-SPS3.5
First operational forecast run: 1st October, 2020
2. Configuration of the forecast model
Is it a coupled model ? YES
Coupling frequency:
Atmosphere-Ocean: 90 minutes (every third full time-timestep step of atmospheric model)
Atmosphere-Land: 30 minutes (also full time-timestep step of atmospheric model)
Atmosphere-Sea Ice: 30 minutes (also full time-timestep step of atmospheric model)
Detailed documentation:
CMCC technical documentation Gualdi et al (2020) CMCC Technical Note RP0288 DOI: https://doi.org/10.25424/CMCC/SPS3.5
2.1 Atmosphere and land surface
Model | CESM 1.2 - CAM 5.3 (Atmosphere) CESM 1.2 - CLM 4.5 ( |
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Land surface) | |
Horizontal resolution and grid | 1/2° lat-lon approx |
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Atmosphere vertical resolution | 46 levels in the vertical |
Top of atmosphere | 0.2 hPa (60 km approx.) |
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Soil levels (layers) | 15 Layer 1 (soil): 0-0.0175m |
Time step | Main (Physics) Time-step: 30 minutes. “Tracer” Advection Time step: 225 seconds Fluid-Dynamics Time step: 56.25 seconds |
Detailed documentation:
CAM Model documentation http://www.cesm.ucar.edu/models/cesm1.2/cam/
CLM Model documentation http://www.cesm.ucar.edu/models/cesm1.2/clm/
CMCC technical documentation Gualdi et al , (2020, CMCC Tech. Rep. RP0XXX, YYpp. Available at address: ) CMCC Technical Note RP0288 DOI: https://wwwdoi.cmccorg/10.it25424/it/publications/rp0XXX-cmcc-sps3.5-the-cmcc-seasonal-prediction-system-3.5CMCC/SPS3.5
2.2 Ocean and cryosphere
Ocean model | NEMO v3.4 |
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Horizontal resolution | 1/4° |
Vertical resolution | 50 levels in the vertical levels |
Time step | 18 minutes |
Sea ice model | CICE 4.0 |
Sea ice model resolution | 1/4° |
Sea ice model levels | 1 thickness only |
Wave model | NO |
Wave model resolution | N/A |
Detailed documentation: goto NEMO documentation
Nemo Model documentation https://www.nemo-ocean.eu/doc/
CMCC technical documentation Gualdi et al (2020) CMCC Technical Note RP0288 DOI: https://doi.org/10.25424/CMCC/SPS3.5
3. Initialization and initial condition (IC) perturbations
3.1 Atmosphere and land
Hindcast | Forecast | |
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Atmosphere initialization | ERA5 | ECMWF IFS operational analysis |
Atmosphere IC perturbations | 10 | 10 |
Land Initialization | Forced |
monthly run |
initialized from 10-year spin-up
Forced (obs. atmosphere) monthly run
initialized from 10-year spin-upfrom a continuous transient simulation with initial-date January 1993, started after a 10 year spinup (with climatological forcings) | Forced monthly run from a continuous transient simulation with initial-date January 1993, started after a 10 year spinup (with climatological forcings) | |
Land IC perturbations | 3 | 3 |
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Soil moisture initialization | From land initialization | From land initialization |
Snow initialization | From land initialization | From land initialization |
Unperturbed control forecast? | NO | NO |
Horizontal resolution of perturbation | N/A | N/A |
Perturbations in +/- pairs | NO | NO |
Data assimilation method for control analysis | ERA5 | ECMWF operational |
Detailed documentation:
For more details on atmospheric DA details , see ECMWF operational analysis documentation at: https://www.ecmwf.int/en/elibrary/16666-part-ii-data-assimilation
Data assimilation method for control analysis: ECMWF operational
Horizontal resolution of perturbation: N/A
For more details on ERA5: https://doi.org/10.1002/qj.3803.
CMCC technical documentation Gualdi et al (2020) CMCC Technical Note RP0288 DOI: https://doi.org/10.25424/CMCC/SPS3.5 Perturbations in +/- pairs: NO
3.2 Ocean and cryosphere
Hindcast | Forecast | |
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Ocean initialization | C-GLORS Global Ocean 3D-VAR | C-GLORS Global Ocean 3D-VAR |
Ocean IC perturbations | 4 | 8 |
Unperturbed control forecast? | NONO | YES |
Detailed documentation:
More details on ocean data assimilation details available at http://c-glors.cmcc.it/index/index.html
CMCC technical documentation Gualdi et al (2020) CMCC Technical Note RP0288 DOI: https://doi.org/10.25424/CMCC/SPS3.5
4. Model uncertainties perturbations:
Model dynamics perturbations | NO |
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Model physics perturbations | YES (Ocean Model only, only during perturbed data assimilation cycles) |
If there is a control forecast, is it perturbed? | There ius is no Control Forecastcontrol forecast |
Detailed documentation: For more info on ocean DA perturbations, see Brankart (2013) DOI: https://doi.org/10.1016/j.ocemod.2013.02.004
CMCC technical documentation Gualdi et al (2020) CMCC Technical Note RP0288 DOI: https://doi.org/10.25424/CMCC/SPS3.5 Detailed documentation: N/A
5. Forecast system and hindcasts
Forecast frequency | Monthly |
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Forecast ensemble size | 50 |
Hindcast years | 1993-2016 |
Hindcast ensemble size | 40 |
On-the-fly or static hindcast set? | STATICstatic |
6. Other relevant information
The 10 atmospheric perturbed ICsinitial conditions, the 3 land perturbed ICs initial conditions and the 8 (4 9 ocean initial conditions (8 perturbed plus the unperturbed, only 4 perturbed in hindcast mode) are combined to yield 240 270 (120 in hindcast mode) possible perturbed ICs among which the 50 ICs forecast system initial conditions from which 50 initial conditions (40 in hindcast mode) to produce the forecast ensemble are chosen at random, to produce the Forecast Ensemble.
Detailed documentation:
CMCC technical documentation Gualdi et al (2020) CMCC Technical Note RP0288 DOI: https://doi.org/10.25424/CMCC/SPS3.5
7. Where to find more information
Sanna, A., A. Borrelli, P. Athanasiadis, S. Materia, A. Storto, S. Tibaldi, S. Gualdi, 2017: CMCC-SPS3: CMCC-SPS3: The CMCC Seasonal Prediction System 3. Centro Euro-Mediterraneo sui Cambiamenti Climatici. CMCC Tech. Rep. Note RP0285, 61pp. Available at address: https://www.cmcc.it/it/publications/rp0285-cmcc-sps3-the-cmcc-seasonal-prediction-system-3
Gualdi, S., A. Sanna, A. Borrelli, A. Cantelli, M. del Mar Chaves Montero, S. Tibaldi, 2017: CMCC-SPS3: CMCC-SPS32020: The new CMCC Operational Seasonal Prediction System 3SPS3.5. Centro Euro-Mediterraneo sui Cambiamenti Climatici. CMCC Tech. Rep. RP0XXX, YYpp. Available at address:Note RP0288, 26pp. DOI: https://wwwdoi.cmccorg/10.it25424/it/publications/rp0XXX-cmcc-sps3.5-the-cmcc-seasonal-prediction-system-3CMCC/SPS3.5