Réf. Déqué & al. 2011 - E

Référence bibliographique complète

DÉQUÉ, M., MARTIN, E., KITOVA, N. 2011. Response of the snow cover over France to climate. Research activities in Atmospheric and Oceanic Modelling, 41, 7.11-7.12. PDF

Abstract:

Mots-clés
 

Organismes / Contact

• Centre National de Recherches Météorologiques (CNRS/GAME), Météo-France. 42 avenue Coriolis F-31057 Toulouse Cédex 1, France, deque@meteo.fr


(1) - Paramètre(s) atmosphérique(s) modifié(s)
(2) - Elément(s) du milieu impacté(s)
(3) - Type(s) d'aléa impacté(s)
(3) - Sous-type(s) d'aléa
Daily surface variables and fluxes Snow cover    

Pays / Zone
Massif / Secteur
Site(s) d'étude
Exposition
Altitude
Période(s) d'observation
France Mountain regions     0-3000m  

(1) - Modifications des paramètres atmosphériques
Reconstitutions

 

Observations

 

Modélisations

 

Hypothèses

 


Informations complémentaires (données utilisées, méthode, scénarios, etc.)

 


(2) - Effets du changement climatique sur le milieu naturel
Reconstitutions

 

Observations

 

Modélisations

The mean number of days per year with snow on the ground in France was calculated, as a function of surface elevation, for the 1961-1990 period, the 2021-2050 period and the 2071-2100 period, with three forcing scenarios for the future periods (B1, A1B and A2). Up to 3000 m, the number of days with snow cover (> 1cm) decreases. The 3 mid-century scenarios have a similar response, whereas at the end of the century, the response is ranked by the GHG concentration. In the worse scenario (A2), the number of days with snow cover on the ground is reduced by 25% at 3000 m, 33% at 2400 m, 50% at 1800m and 75% at 1200m. This result confirms the sensitivity study in the Mont Blanc region by Martin et al. (1997).

Hypothèses

 


Sensibilité du milieu à des paramètres climatiques
Informations complémentaires (données utilisées, méthode, scénarios, etc.)

 

The climate change over the mountain regions is not an easy question because it is strongly modulated by the surface elevation and the horizontal gradient of this variable is not compatible with the horizontal resolution of the GCMs. The current resolution of the next CMIP5 exercise (100-200 km) does not allow to represent the mountains over France, except a coarse dome in the South-Eastern part corresponding to the Alps. The typical resolution of the next CORDEX exercise (50 km) enables to represent the main three mountains (Alps, Pyrenees and Massif Central) but the horizontal gradient of elevation is not steep enough and this has consequences on the representation of local precipitation and winds. In addition the maximum elevation is not high enough, which has consequences on the snow cover. Given the horizontal scale of ridges and valleys, a 1 km mesh would be necessary for an accurate representation of the mountains, but it is not yet compatible with centennial integrations with the present capacity of computers.

However the mid-latitude mountainous areas are vulnerable to global warming, because the reduction of the snow cover has a strong impact on water resources and tourism, even with a moderate increase in mean temperature. To investigate this question, we have developed, in the framework of the French national project SCAMPEI (http://www.cnrm.meteo.fr/scampei/) a four-step procedure to evaluate the snow cover over France:

Step one. The ARPEGE-climate-V4 AGCM model (Déqué, 2007) derived from the ARPEGE-IFS code has been run over 1950-2100 with monthly bias-corrected sea surface temperatures of the CMIP3 contribution by the AOGCM version of this model (A1B scenario). The AOGCM resolution is 300 km, whereas the AGCM has a variable horizontal resolution ranging from 50 km over Europe to 300 km in the southern Pacific.

Step two. The ALADIN-climate-V4 limited area RCM (Déqué and Somot, 2008) based on the above model, but with a 12 km resolution over a domain centered on France has been driven by the above AGCM. Figure 1 shows the surface elevation over France by the AOGCM, the AGCM, and the RCM.

Step three. The daily surface variables and fluxes have been corrected by the quantile-quantile method described in Déqué (2007). The reference data is the SAFRAN reanalysis (Quintana-Séguí et al., 2008). This reference offers hourly surface data and fluxes in 615 homogeneous areas within France (about 30 km horizontal resolution) at different altitudes (300 m vertical resolution).

Step four. The statistically corrected variables have been used as an input of the ISBA-ES soil-vegetation-snow model (Boone et al., 2001).

The output of this process is, inter alia, a daily data base of high resolution snow cover with different altitudes for each area. Because of the statistical pre-processing, the snow cover climatology is in fairly good agreement with the observations during the 1961-1990 period. The process has been repeated with SRES scenarios A2 and B1 in order to explore the uncertainty. It is planned to include two other French RCMs at similar resolution, and a direct statistical downscaling to SAFRAN data of some CMIP3 AOGCMs to deepen the uncertainty analysis.


(3) - Effets du changement climatique sur l'aléa
Reconstitutions

 

Observations

 

Modélisations

 

Hypothèses

 


Paramètre de l'aléa
Sensibilité des paramètres de l'aléa à des paramètres climatiques
Informations complémentaires (données utilisées, méthode, scénarios, etc.)

 

 

 


(4) - Remarques générales

 


(5) - Syntèses et préconisations

 

Références citées :

Boone, A. and P. Etchevers, 2001: An inter-comparison of three snow schemes of varying complexity coupled to the same land-surface model: Local scale evaluation at an Alpine site, J.Hydrometeorol., 2, 374-394.

Déqué, M., 2007: Frequency of precipitation and temperature extremes over France in an anthropogenic scenario: model results and statistical correction according to observed values. Global and Planetary Change, 57, 16-26.

Déqué, M. and S. Somot, 2008: Extreme precipitation and high resolution with Aladin. Quarterly Journal of the Hungarian Meteorological Service, 112, 179-190.

Quintana-Seguí, P., P. Le Moigne, Y. Durand, E. Martin, F. Habets, M. Baillon, C. Canellas, L. Franchisteguy and S. Morel, 2008: Analysis of Near-Surface Atmospheric Variables: Validation of the SAFRAN Analysis over France. J. Appl. Meteor. Climatol., 47, 92–107.

Martin E., B. Timbal and E. Brun, 1997: Downscaling of general circulation model outputs: simulation of the snow climatology of the French Alps and sensitivity to climate change. Climate Dynamics, 13, 45-56.