Pôle Alpin Risques Naturels (PARN) Alpes–Climat–Risques Avec le soutien de la Région Rhône-Alpes (2007-2014)

Fiche bibliographique – Résumé


Réf. Piazza & al. 2014 - A

Référence bibliographique
PIAZZA, M., BOÉ, J., TERRAY, L. PAGÉ, C., SANCHEZ-GOMEZ, E., DÉQUÉ, M. 2014. Projected 21st century snowfall changes over the French Alps and related uncertainties. Climatic Change, Vol. 122 (4), 583–594. DOI

Abstract: Snowfall changes in mountain areas in response to anthropogenic forcing could have widespread hydrological, ecological and economic impacts. In this paper, the robustness of snowfall changes over the French Alps projected during the 21st century and the associated uncertainties are studied. In particular, the role of temperature changes on snowfall changes is investigated. Those issues are tackled through the analysis of the results of a very large ensemble of high-resolution regional climate projections, obtained either through dynamical or statistical downscaling. We find that, at the beginning and at the end of the cold season extending from November to March (included), temperature change is an important source of spread in snowfall changes. However, no link is found between temperature and snowfall changes in January and February. At the beginning and at the end of the cold season, the rate of change in snowfall per Kelvin does not depend much on the bias correction step, the period or the greenhouse gas scenario but mostly on the downscaling method and the climate models, the latter uncertainty source being dominant.


Organismes / Contact

• Sciences de l’Univers au CERFACS, CERFACS/CNRS, URA1875, Toulouse, France e-mail: piazza@cerfacs.fr
• Météo-France/CNRS, CNRM-GAME, UMR3589, Toulouse, France

This work has been partially supported by the French National Agency (ANR) in the framework of its Scientific Research Vulnérabilité Milieux et Climat (VMC) program (SCAMPEI, project). The ENSEMBLES data used in this work was funded by the EU FP6 Integrated Project ENSEMBLES.

(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
Temperature, Precipitation Snow cover    

Pays / Zone
Massif / Secteur
Site(s) d'étude
Période(s) d'observation
French Alps          

(5) - Syntèses et préconisations

Based on a very large ensemble of both statistically and dynamically downscaled high-resolution climate projections, we suggest that large changes in solid precipitation over the French Alps are to be expected in the future climate, with a winter decrease of roughly 25 % in the middle of the 21st century with a 20–80 % quantile range of −20 %–−35 % under the median A1B greenhouse gas scenario.

We find that the projected snowfall relative changes (per degree of warming) are relatively robust among the different downscaling techniques.

Interestingly, temperature changes only play a minor role in snowfall changes uncertainties during winter coldest months. However, in late fall and early spring, the spread in temperature changes is explaining an important part of snowfall change uncertainty. During those months, snowfall sensitivity to temperature changes is not affected by the bias correction step applied to dynamical downscaling results, the chosen projection period or the emission scenario. A limited sensitivity to the type of downscaling approach is found and the dominant source of spread is the climate model (global for statistical downscaling, regional for dynamical downscaling).

The close relationship between temperature change and snowfall change has important consequences. First, it could be argued that changes due to temperature can be better projected than changes due to other processes, like large scale atmospheric circulation (they have a higher signal to noise ratio). Qualitatively, the fact that snowfall changes are closely linked to temperature changes gives therefore higher confidence to the model estimation of those changes. Second, in the middle of the 21st century, temperature changes associated with different emission scenarios are relatively similar (e.g. Fig. 10.4 in Meehl et al. 2007a) while emission scenario at the end of century clearly becomes the dominant source of uncertainties (Hawkins and Sutton 2009). Given the nature of uncertainties associated with the emission scenario and the high dependency of snowfall changes during transition months to temperature, it would be difficult to significantly reduce this part of the uncertainties in late 21st century snowfall projections. However, as model uncertainty is also important all along the 21st century, reducing model bias has the potential to enable improvements in the accuracy of snowfall projections.

Several other research projects are currently interested in the regional impacts of climate change, based on different GCMs and RCMs and using other downscalingmethods and scenarios than those presented in this study. This is the case of the French project DRIAS (http://www.driasclimat. fr/) and the international project CORDEX (Coordinated Regional climate Downscaling Experiment) with the European branch EURO-CORDEX (http://euro-cordex.net/) performing a set of fine-scale climate projections over Europe in order to serve impact and adaptation studies to climate change in the context of the Fifth Assessment report of the IPCC.



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