CERFACS CERFACS Scientific Activity Report Jan. 2010 – Dec. 2011

CLIMATE CHANGE AND IMPACT STUDIES
and a model-independent objective analysis (Corre et al. 2011). Several variables were used : the mean
temperature above the 14 o C isotherm, its depth and a fixed depth mean temperature (250 m mean
temperature). This choice of variables provides information about the local heat absorption, vertical
distribution and horizontal redistribution of heat, this latter being suggestive of changes in ocean circulation.
Use of the mean temperature above the 14 o C isotherm is a convenient, albeit simple, way to isolate
thermodynamical changes by filtering out dynamical changes related to thermocline vertical displacements.
We have found that the global upper ocean observations and reanalyses exhibit very similar warming trends
(0.045 o C per decade) over the period 1965-2005, superimposed with marked decadal variability in the
1970s and 1980s. The spatial patterns of the regression between indices (representative of anthropogenic
changes and known modes of internal decadal variability), and the three variables associated with the ocean
heat content are used as fingerprint to separate out the different contributions. Two robust findings result
from our analysis : (1) the signature of anthropogenic changes is qualitatively different from those of the
internal decadal variability associated to the Pacific Interdecadal Oscillation and the Atlantic Meridional
Oscillation, and (2) the anthropogenic changes in ocean heat content do not only consist of local heat
absorption, but are likely related with changes in the ocean circulation, with a clear shallowing of the
tropical thermocline in the Pacific and Indian oceans.
3.2 Statistical downscaling and impact studies
The downscaling activities have been aimed toward application of the previously developed statistical
downscaling methodology, using it for diversified climate change impact studies and research at regional to
local scales. Some studies have also taken place to better understand the characteristics and the stochastic
aspects of the methodology. In parallel, work has begun regarding the standardization of downscaled data,
along with the development of user guidance aimed at the impact communities, as well as the development
of new collaborative web portals to help dissemination.
A summary of the main activities during the period 2010-2011 is given below.
3.2.1 Impact of climate change on mountainous areas in France (C. Pagé,
L. Terray, M. Piazza, E. Sanchez, J. Boé)
Our main objective was to adapt the DSCLIM statistical downscaling methodology to study the impacts
of climate change on the mountainous areas in France, in the context of the ANR/SCAMPEI project led
by Météo-France CNRM. Several geographical domains for the large-scale circulation have been evaluated
by comparing the performance of downscaled precipitation to the original configuration used previously,
as well as the relevance of the generated weather types. The configuration has also been standardized
among the different seasons (number of weather types, mask to use only data exclusively over France,
random selection of analog day within closest days). After evaluation, it has been decided to keep the
original geographical domain. This result is also confirmed by the thesis results of M. Lafaysse (Lafaysse,
2011), which also stated the importance of taking into account the stochastic aspects of the methodology
when working on quite small geographical domains. A new dataset have been generated given this new
configuration, called SCRATCH2010, which improves DSCLIM results especially over southern Alps and
along the Mediterranean coast (except for Roussillon). DSCLIM downscaled scenarios have also been
compared to dynamically downscaled ARPEGE scenarios by Météo-France CNRM (using a bias correction
quantile-quantile methodology). Surface feedbacks have also been studied for the present climate, and also
in dynamically downscaled (non-corrected) scenarios, over the Alps and Pyrenees. Two hypothesis have
resulted from this study : a) In the south, feedbacks between snow cover and temperature occur mainly in
April (with a 2-month time lag), caused mostly by the generation of mist and fog which limits the solar
radiation. b) In the north and east, the correlation time lag is of 6 months, and the physical process is related
to the soil water content.
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