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INRAE

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Last update: May 2021

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AGADAPT - Adapting the water use by the agriculture sector

MEDCORDEX

The Med-Cordex climate projections have been computed with the limited-area atmosphere RCM ALADIN-Climate in its version 5 firstly described in Colin et al. (2010). ALADIN-Climate shares the same dynamical core as the cycle 32 of its weather forecast ALADIN (Aire Limitée Adaptation dynamique Développement InterNational) counterpart and the same physical package as the version 5 of the GCM ARPEGE-Climate (see http://www.cnrm.meteo.fr/gmgec/arpege-climat/ARPCLI-V5.1/index.html). It is worth noting that ALADIN-Climate takes into account five greenhouse gases (CO2, CH4, N2O and CFC) in addition to water vapour and ozone. The scheme also takes into account five classes of aerosols.

For the Med-Cordex simulations, ALADIN-Climate model has been run at a frontier resolution of 12-km over the whole Mediterranean area. Déqué and Somot (2008) and Herrmann et al. (2011) proved that 12-km resolution is required to represent accurately extreme precipitation over land in the Mediterranean climate of France and extreme and coastal wind over the Mediterranean Sea.

Inside the Med-Cordex data set, 4 simulations have been provided for the different areas :

  • The so-called evaluation run in which the RCM is driven at its lateral boundary conditions by the ERA-Interim reanalysis (80-km at its full resolution) (Dee et al., 2011). The period simulated is 1979–2012. The climate as simulated by ALADIN-Climate in the “evaluation mode” is the most realistic representation of the climate simulated, as we consider that ERA-Interim is the best knowledge of the 4-D dynamic of the atmosphere available over the last 30 yr.
  • The historical run in which the RCM is driven by the historical run of a CMIP5 (Coupled Model Intercomparison Project Phase 5)GCM (General Circulation Model). We used CNRM-CM5 (Voldoire et al., 2011) developed at CNRM to ensure a consistency of the physics between the driving GCM and the driven RCM. Note that consistency is however not perfect as the land-surface scheme and the radiative scheme are slightly different. However solar forcing, aerosol field and GHG concentrations are similar in the RCM and GCM. After a 2-yr spinup of ALADIN to ensure the stability of the land-surface scheme, the historical run covers the period 1950–2005. Among the 10-member runs with CNRM-CM5, we chose main member of CNRM-CM5 called HISTr8.
  • The RCP4.5 and the RCP8.5 scenarios in which ALADIN-Climate is driven by the RCP4.5 (resp. RCP8.5) scenario run made with CNRM-CM5 and corresponding to HISTr8 historical run. The period covered is 2006–2100. RCP4.5 and RCP8.5 corresponds to the naming of two of the new climate change scenarios (Radiative Concentration Pathway scenario) used in CMIP5 and in the IPCC-AR5. They replace the former SRES scenarios used for example in CMIP3 and IPCC-AR4. The RCP4.5 (resp. RCP8.5) means that the GHG and aerosols concentrations evolves in a way that leads to an additional radiative forcing equal to +4.5 W m−2 (resp. + 8.5 W m−2) at the end of the 21st century with respect to the pre-industrial climate. Consequently the RCP4.5 can be considered as an optimist scenario with respect to the GHG concentration whereas RCP8.5 is a more pessimistic option.

 

Data description

 Source

  • Météo-France

Manipulation

Availability

Spatial and temporal coverage

  • For the spatial coverage, a Lambert conformal projection for pan-Mediterranean area at horizontal resolutions of  12 km centred at centred at 43°N with 432 grid points in longitude and 288 grid points in latitude
  • For temporal coverage (used in the project) :
    • 1971-2005 for the historical run,
    • 2000-2011 for the evaluation run,
    • 2036-2065 for the climate projection.

 Evaluation

 Evaluation methodolology (reference, quantities that are compared)

  • Comparison of evaluation simulation with meteorological data.

Results of the evaluation

  • Results indicate that high resolution simulations at 12 km better reproduce the seasonal patterns, the seasonal distributions and the extreme events of precipitation. The parameters of the hydrological model, calibrated to reproduce runoff at the monthly time step over the 1984–2010 period, do not show a strong variability between dry and wet calibration periods in a differential split-sample test.

 Recommendations

 Strengths and weakness

  • High spatial resolution for climate simulations ;
  • Better ability to reproduce the Mediterranean climate
  • Such as every climate models, necessity of debiasing with climatological data.

 Limit of validity

  • The climate projections have to be used to compute statistics for long period of time, between 20 to 30 years

 References

  • Colin J., Déqué M., Radu R., Somot S. (2010) Sensitivity study of heavy precipitations in Limited Area Model climate simulation: influence of the size of the domain and the use of the spectral nudging technique. Tellus-A, 62(5), 591-604. DOI: 10.1111/j.1600-0870.2010.00467.x
  • Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G.,  Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, doi: 10.1002/qj.828, 2011
  • Déqué, M. and Somot, S.: Extreme precipitation and high resolution with Aladin, Idöjaras, Q. J. Hungar. Meteorol. Serv., 112, 179–190, 2008.
  • Herrmann M., Somot S., Calmanti S., Dubois C., Sevault F. (2011) “Representation of daily wind speed spatial and temporal variability and intense wind events over the Mediterranean Sea using dynamical downscaling : impact of the regional climate model configuration”, Nat. Hazards Earth Syst. Sci., 11, 1983-2001, doi:10.5194/nhess-11-1983-2011
  • Jacob D., Petersen J., Eggert B., Alias A., Christensen O.B., Bouwer L., Braun A., Colette A., Déqué M., Georgievski G., Georgopoulou E., Gobiet A., Menut L., Nikulin G., Haensler A., Hempelmann N., Jones C., Keuler K., Kovats S., Kröner N., Kotlarski S., Kriegsmann A., Martin E., van Meijgaard E., Moseley C., Pfeifer S., Preuschmann S., Radtke K., Rechid D., Rounsevell M., Samuelsson P., Somot S., Soussana J.-F., Teichmann C., Valentini R., Vautard R., Weber B. And Yiou P. (2013) EURO-CORDEX: New high-resolution climate change projections for European impact research. Regional Environmental Change (on-line in July 2013) doi: 10.1007/s10113-013-0499-2
  • Tramblay Y., Ruelland D., Somot S., Bouaicha R., Servat E. (2013) High-resolution Med-CORDEX regional climate model simulations for hydrological impact studies: a first evaluation of the ALADIN-Climate model in Morocco. Hydrol. Earth Syst. Sci., 17, 3721-3739,doi:10.5194/hess-17-3721-2013 (www.hydrol-earth-syst-sci.net/17/3721/2013/)
  • Voldoire, A., Sanchez-Gomez, E., Salas-y-Mélia, D., Decharme, B., Cassou, C., Sénési, S., Valcke, S., Beau, I., Alias, A., Chevallier, M., Déqué, M., Deshayes, J., Douville, H., Fernandez, E., Madec, G., Maisonnave, E., Moine, M.-P., Planton, S., Saint-Martin, D., Szopa, S., Tyteca, S., Alkama, R., Belamari, S., Braun, A., Coquart, L., and Chauvin, F.: The CNRM-CM5.1 global climate model: description and basic evaluation, Clim. Dynam., 40, 2091–2121, doi: 10.1007/s00382-011-1259-y, 2011

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