...
Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., et al. (2017). Solar forcing for CMIP6 (v3.2). Geoscientific Model Development, 10(6), 2247–2302. https://doi.org/10.5194/gmd‐10‐2247‐2017
Meinshausen, M. et al. (2017). Historical greenhouse gas concentrations for climate modelling (CMIP6). Geoscientific Model Development, 10(5), 2057–2116. https://doi.org/10.5194/gmd-10-2057-2017
Meinshausen, M. et al. (2020). The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500. Geoscientific Model Development, 13, 3571–3605. https://doi.org/10.5194/gmd-13-3571-2020
Michou, M., Nabat, P., Saint-Martin, D., Bock, J., Decharme, B., Mallet, M., Roehrig, R., Séférian, R., Sénési, S. and Voldoire, A. (2020). Present-day and historical aerosol and ozone characteristcs in CNRM CMIP6 simulatons. Journal of Advances in Modeling Earth Systems, 12, e2019MS001816, https://doi.org/10.1029/2019MS001816
Thomason, L. W., Ernest, N., Millán, L., Rieger, L., Bourassa, A., Vernier, J. P., et al. (2018). A global space‐based stratospheric aerosol climatology: 1979–2016. Earth System Science Data, 10(1), 469–492. https://doi.org/10.5194/essd‐10‐469‐2018
Voldoire, A., Saint-Martn, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M., et al (2019). Evaluation of CMIP6 DECK experiments with CNRM-CM6-1. Journal of Advances in Modeling Earth Systems, 11. https://doi.org/10.1029/2019MS001683
...
| Hindcast | Forecast | |
|---|---|---|
| Atmosphere initialization | ERA5 | ERA5T |
| Atmosphere IC perturbations | None | None |
Land Initialization | ERA5 | ERA5T |
| Land IC perturbations | None | None |
| Soil moisture initialization | ERA5 | ERA5T |
| Snow initialization | ERA5 | ERA5T |
| Unperturbed control forecast? | NA | NA |
Detailed documentation:
ERA5: data documentation
4.2 Ocean and cryosphere
...
| Model dynamics perturbations | Yes |
|---|---|
| Model physics perturbations | No |
If there is a control forecast, is it perturbed? | NA |
Detailed documentation:
Batté, L. and Déqué, M. (2016). Randomly correcting model errors in the ARPEGE-Climate v6. 1 component of CNRM-CM: applications for seasonal forecasts. Geoscientific Model Development, 9, 2055-2076. https://doi.org/10.5194/gmd-9-2055-2016
...