You are viewing an old version of this page. View the current version.
Compare with Current
View Page History
Version 1
Next »
1. Ensemble version |
|
---|
Ensemble identifier code |
|
---|
Short Description |
|
---|
Research or operational |
|
---|
Data time of first forecast run |
|
---|
2. Configuration of the EPS |
|
---|
Is the model coupled to an ocean model? |
|
---|
If yes, please describe ocean model briefly including frequency of coupling and any ensemble perturbation applied. |
|
---|
Is the model coupled to a sea Ice model? |
|
---|
If yes, please describe sea-ice model briefly including any ensemble perturbation applied. |
|
---|
Is the model coupled to a wave model? |
|
---|
If yes, please describe wave model briefly including any ensemble perturbation applied |
|
---|
Ocean model |
|
---|
Horizontal resolution of the atmospheric model |
|
---|
Number of model levels |
|
---|
Top of model |
|
---|
Type of model levels |
|
---|
Forecast length |
|
---|
Run Frequency |
|
---|
Is there an unperturbed control forecast included? |
|
---|
Number of perturbed ensemble members |
|
---|
Integration time step |
|
---|
3. Initial conditions and perturbations |
|
---|
Data assimilation method for control analysis |
|
---|
Resolution of model used to generate Control Analysis |
|
---|
Ensemble initial perturbation strategy |
|
---|
Horizontal and vertical resolution of perturbations |
|
---|
Perturbations in +/- pairs |
|
---|
Initialization of land surface |
|
---|
3.1 What is the land surface model (LSM) and version used in the forecast model, and what are the current/relevant references for the model? |
|
---|
Are there any significant changes/deviations in the operational version of the LSM from the documentation of the LSM? |
|
---|
3.2 How is soil moisture initialized in the forecasts? (climatology / realistic / other) |
|
---|
If “realistic”, does the soil moisture come from an analysis using the same LSM as is coupled to the GCM for forecasts, or another source? Please describe the process of soil moisture initialization. |
|
---|
Is there horizontal and/or vertical interpolation of initialization data onto the forecast model grid? If so, please give original data resolution(s). |
|
---|
Does the LSM differentiate between liquid and ice content of the soil? If so, how are each initialized? |
|
---|
If all model soil layers are not initialized in the same way or from the same source, please describe. |
|
---|
3.3 How is snow initialized in the forecasts? (climatology / realistic / other) |
|
---|
If “realistic”, does the snow come from an analysis using the same LSM as is coupled to the GCM for forecasts, or another source? Please describe the process of soil moisture initialization. |
|
---|
Is there horizontal and/or vertical interpolation of data onto the forecast model grid? If so, please give original data resolution(s) |
|
---|
Are snow mass, snow depth or both initialized? What about snow age, albedo, or other snow properties? |
|
---|
3.4. How is soil temperature initialized in the forecasts? (climatology / realistic / other) |
|
---|
If “realistic”, does the soil moisture come from an analysis using the same LSM as is coupled to the GCM for forecasts, or another source? Please describe the process of soil moisture initialization. |
|
---|
Is the soil temperature initialized consistently with soil moisture (frozen soil water where soil temperature ≤0°C) and snow cover (top layer soil temperature ≤0°C under snow)? |
|
---|
Is there horizontal and/or vertical interpolation of data onto the forecast model grid? If so, please give original data resolution(s) |
|
---|
If all model soil layers are not initialized in the same way or from the same source, please describe. |
|
---|
3.5. How are time-varying vegetation properties represented in the LSM? |
|
---|
3.6. What is the source of soil properties (texture, porosity, conductivity, etc.) used by the LSM? |
|
---|
3.7 If the initialization of the LSM for re-forecasts deviates from the procedure for forecasts, please describe the differences. |
|
---|
4. Model Uncertainties perturbations |
|
---|
Is model physics perturbed? |
|
---|
Do all ensemble members use exactly the same model version? |
|
---|
Is model dynamics perturbed? |
|
---|
Are the above model perturbations applied to the control forecast? |
|
---|
Additional Comments |
|
---|
5. Surface Boundary perturbations |
|
---|
Perturbations to sea surface temperature? |
|
---|
Perturbation to soil moisture? |
|
---|
Perturbation to surface stress or roughness? |
|
---|
Any other surface perturbation? |
|
---|
Are the above surface perturbations applied to the Control forecast? |
|
---|
Additional comments |
|
---|
6. Other details of the models |
|
---|
Description of model grid |
|
---|
List of model levels in appropriate coordinates |
|
---|
What kind of large scale dynamics is used? |
|
---|
What kind of boundary layer parameterization is used? |
|
---|
What kind of convective parameterization is used? |
|
---|
What kind of large-scale precipitation scheme is used? |
|
---|
What cloud scheme is used? |
|
---|
What kind of land-surface scheme is used? |
|
---|
How is radiation parametrized? |
|
---|
Long Wave Radiation |
|
---|
Short Wave radiation |
|
---|
Sea-ice thickness |
|
---|
Other relevant details? |
|
---|
7. Re-forecast Configuration |
|
---|
Number of years covered |
|
---|
Produced on the fly or fix re-forecasts? |
|
---|
Frequency |
|
---|
Ensemble size |
|
---|
Initial conditions |
|
---|
Is the model physics and resolution the same as for the real-time forecasts |
|
---|
If not, what are the differences |
|
---|
Is the ensemble generation the same as for real-time forecasts? |
|
---|
If not, what are the differences |
|
---|
8. References
- Batté, L. and Déqué, M. (2016), ‘Randomly correcting model erros in the ARPEGE-Climate v6.1 component of CNRM-CM : applications for seasonal forecasts.’ Geoscientific Model Development 9(6)
- Boisserie, M., Decharme, B., Descamps, L. and Arbogast, P. (2016), ‘Land surface initialization strategy for a global reforecast dataset’, Quarterly Journal of the Royal Meteorological Society 142(695), 880–888.
- Cuxart, J., Bougeault, P. and Redelsperger, J.-L. (2000), ‘A turbulence scheme allowing for mesoscale and large-eddy simulations’, Quarterly Journal of the Royal Meteorological Society 126(562), 1–30.
- Constantin Ardilouze, Damien Specq, Lauriane Batté, and Christophe Cassou: Flow dependence of wintertime subseasonal prediction skill over Europe, Weather Clim. Dynam., 2, 1033–1049, 2021, https://doi.org/10.5194/wcd-2-1033-2021
- Decharme, B., Delire, C., Minvielle, M., Colin, J., Vergnes, J.-P., Alias, A., Saint-Martin, D., Séférian,R., Sénési, S. and Voldoire, A. (2019), ‘Recent changes in the ISBA-CTRIP land surface system foruse in the CNRM-CM6 climate model and in global off-line hydrological applications’, Journal of Advances in Modeling Earth Systems .
- Faroux, S., Kaptué Tchuenté, A., Roujean, J.-L., Masson, V., Martin, E. and Moigne, P. L. (2013), ‘ECOCLIMAP-II/Europe : A twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models’, Geoscientific Model Development 6(2), 563–582.
- Fouquart, Y. and Bonnel, B. (1980), ‘Computations of solar heating of the earth’s atmosphere- A new parameterization’, Beitraege zur Physik der Atmosphaere 53, 35–62.
- Guérémy, J. (2011), ‘A continuous buoyancy based convection scheme : one-and three-dimensional validation’, Tellus A : Dynamic Meteorology and Oceanography 63(4), 687–706.
- Lopez, P. (2002), ‘Implementation and validation of a new prognostic large-scale cloud and precipitation scheme for climate and data-assimilation purposes’, Quarterly Journal of the Royal Meteorological Society 128(579), 229–257.
- Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J. and Clough, S. A. (1997), ‘Radiative transfer for inhomogeneous atmospheres : RRTM, a validated correlated-k model for the longwave’, Journal of Geophysical Research : Atmospheres 102(D14), 16663–16682.
- Piriou, J.-M., Redelsperger, J.-L., Geleyn, J.-F., Lafore, J.-P. and Guichard, F. (2007), ‘An approach for convective parameterization with memory : Separating microphysics and transport in grid-scale equations’, Journal of the Atmospheric Sciences 64(11), 4127–4139.
- Voldoire, A., Saint-Martin, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M., Colin, J., Guérémy, J.-F., Michou, M., Moine, M.-P., Nabat, P., Roehrig, R., Salas y Mélia, D., Séférian, R., Valcke, S., Beau,I., Belamari, S., Berthet, S., Cassou, C., Cattiaux, J., Deshayes, J., H. Douville, H., Franchisteguy,L., Ethé, C., Geoffroy, O., Lévy, C., Madec, G., Meurdesoif, Y., Msadek, R., Ribes, A., Sanchez, E.,Terray, L. and Waldman, R. (2019), ‘Evaluation of CMIP6 DECK experiments with CNRM-CM6-1’,Journal of Advances in Modeling Earth Systems.
- URL: http ://www.umr-cnrm.fr/cmip6/references