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Long-term vegetation studies are needed to better predict the impact of future climate change on vegetation structure and distribution. According to the IPCC scenario, the Mediterranean region is expected to undergo significant climatic variability over the course of this century. Cedrus libani (A. Rich), in particular, is currently distributed in limited areas in the Eastern Mediterranean region, which are expected to be affected by such climate change. In order to predict the impact of future global warming, we have used fossil pollen data and model simulations. Palaeobotanical data show that C. libani has been affected by both climate change and human activities. Populations of C. libani survived in refugial zones when climatic conditions were less favourable and its range extended during periods of more suitable climate conditions. Simulations of its future geographical distribution for the year 2100 using a dynamic vegetation model show that only three areas from Mount Lebanon may allow its survival. These results extrapolated for cedar forests for the entire Eastern Mediterranean region show that forests in Syria are also threatened by future global warming. In southern Turkey, cedar forests seem to be less threatened. These results are expected to help in the long-term conservation of cedar forests in the Near East.

The local future climate conditions in Morocco under the SRES scenario A1B are studied by using two 30-year time-slice simulations performed by the variable resolution configuration of the global circulation model ARPEGE-Climate. The spatial resolution ranges between 50 and 60 km over the whole country. Firstly, the link between local precipitation and weather regimes in the North Atlantic basin is investigated in terms of mean precipitation and the frequencies of occurrence for wet and intense precipitation days. Then a statistical downscaling approach that uses large-scale fields to construct local scenarios of future climate change is validated in the case of Moroccan winter precipitation. The outputs of experiments carried out from an ensemble of regional climate models are used to assess the uncertainties associated to future climate change. These dynamical downscaling outputs have been also used to test the robustness of the results related to the statistical downscaling technique. Our results concerning the future climate conditions over Morocco show not solely a decrease in mean precipitation but also a change in the precipitation distribution and in extreme events.

Seasonal prediction is based on changes in the probability of weather statistics due to changes in slowly varying forcings such as sea-surface temperature anomalies, most notably those associated with El Niňo–Southern Oscillation (ENSO). However, seasonal weather can be perturbed by many factors, and is very much influenced by internal variability of the atmosphere, so comprehensive models are needed to identify what can be predicted. The predictability and probabilistic nature of seasonal forecasts is explained with suitable examples. Current capabilities for seasonal prediction that have grown out of work done in the research community at both national and international levels are described. Dynamical seasonal prediction systems are operational or quasi-operational at a number of forecasting centres around the world. Requirements for seasonal prediction include initial conditions, particularly for the upper ocean but also other parts of the climate system; high quality models of the ocean-atmosphere-land system; and data for verification and calibration. The wider context of seasonal prediction and seamless forecasting is explained. Recommendations for the future of seasonal prediction and climate services are given.

International audience; The SAMM (Sea Atmosphere Mediterranean Model) has been developed to study the climate evolution of the Mediterranean and European regions for the 21st Century. SAMM is a new concept of AORCM (Atmosphere-Ocean Regional Climate Model), where a global atmosphere model is locally coupled with a regional ocean circulation model. It consists of the global spectral AGCM ARPEGE-Climate model, whose variable resolution is maximum in the Mediterranean region (50 km), which has been coupled to the Mediterranean Sea limited area OGCM OPAMED (10 km). A 140-year numerical experiment starting in 1960 was run with the AORCM. Up to year 2000, forcing was prescribed from observed values, whereas forcing following a SRES-A2 scenario was applied beyond 2000. In order to ensure the model stability, a simple monthly heat flux correction on air-sea exchanges was applied. The present-climate validation proves that the AORCM is comparable to the state-of-the-art European Atmosphere Regional Climate Models (ARCM) at the same resolution. At first order, the climate change impact over Europe simulated by the AORCM is comparable with ARCM simulations. However the AORCM significantly amplifies the climate change signal over large parts of Europe with respect to the corresponding ARCM: the warming is higher in all seasons and in many areas of Europe (up to 25% of the signal), winters are wetter over northern Europe and summers drier over southern and eastern Europe (up to 50% of the signal). These differences are highly significant and the choice between coupled and non-coupled regional models could be an additional source of uncertainty when evaluating the climate change response over Europe. The factors responsible for these differences are discussed. Among them, the response of the Mediterranean SST, better simulated by the high resolution Mediterranean Sea model of the AORCM, seems to be preponderant. Further mechanism studies and model inter-comparisons are however required to legitimate the present results.

Meteo-France atmospheric model ARPEGE/Climate has been used to simulate present climate (1961–1990) and a possible future climate (2071–2100) through two ensembles of three 30-year numerical experiments. In the scenario experiment, the greenhouse gas and aerosol concentrations are prescribed by the so-called SRES-A2 hypotheses, whereas the sea surface temperature and sea ice extent come from an earlier ocean–atmosphere coupled simulation. The model covers the whole globe, with a variable resolution reaching 50 to 60 km over France. Model responses on daily minimum and maximum temperature and precipitation are analyzed over France. The distribution of daily values is compared with observed data from the French climatological network. The extreme cold temperatures and summer heavy precipitations are underestimated by the model. A correction technique is proposed in order to adjust the simulated values according to the observed ones. This process is applied to both reference and scenario simulation. Synthetic indices of extreme events are calculated with corrected simulations. The number of heavy rain (> 10 mm) days increases by one quarter in winter. The maximum length of summer dry episodes increases by one half in summer. The number of heat wave days is multiplied by 10. The response in precipitation is less when only the change in the mean is considered. Such a corrected simulation is useful to feed impact models which are sensitive to threshold values, but the correction does not reduce, and may enhance in some cases, the uncertainty about the climate projections. Using several models and scenarios is the appropriate technique to deal with uncertainty.

Resume A l'echelle planetaire, les modeles simulent de facon coherente une intensification du cycle hydrologique dans un climat futur, plus chaud que le climat actuel. Cependant, cette intensification du cycle pourrait s'accompagner de son ralentissement du a l'augmentation du temps de residence de la vapeur d'eau dans l'atmosphere. L'impact des changements climatiques sur les evenements extremes de precipitations est beaucoup plus difficile a evaluer, tant les resultats dependent des methodologies employees, des scenarios d'emissions et, principalement, des modeles. L'augmentation des precipitations extremes hivernales sur l'Europe du Nord est cependant un trait commun de ces evaluations. Le cycle hydrologique, au travers de la repartition geographique des humidites de surfaces continentales, semble jouer un role determinant sur la possibilite de detecter le rechauffement climatique en France. Pour citer cet article : S. Planton et al., C. R. Geoscience 337 (2005).

Resume Apres avoir rappele les caracteristiques principales de la vague de chaleur de l'ete 2003 qui a affecte l'Ouest de l'Europe, en particulier en comparaison avec de precedents etes exceptionnellement chauds, on examine quelles ont ete les performances des divers modeles de prevision saisonniere actuellement exploites de facon operationnelle ou pre-operationnelle. Aucun d'eux n'ayant ete en mesure de prevoir, a l'echeance de trois mois et de facon consistante, l'apparition de cette vague de chaleur, on analyse la situation meteo-climatique qui a prevalu au printemps 2003. On identifie ainsi une forte anomalie de temperature de surface oceanique dans l'Atlantique nord comme un des phenomenes precurseurs de la vague de chaleur. Le mecanisme complet permettant de rendre compte de l'apparition de la vague de chaleur ne peut toutefois se reduire a une « simple » influence « sous le vent » de cette anomalie, et met tres probablement en jeu des phenomenes complexes d'interaction entre l'ocean et l'atmosphere, encore trop mal pris en compte dans les modeles de prevision saisonniere. Pour citer cet article : J.-C. Andre et al., C. R. Geoscience 336 (2004).

The atmosphere and the ocean are subject to many dynamical instabilities, which limit the time during which their behaviour can be deterministically forecasted. At longer timescales, the atmosphere can be predicted at best using statistical methods, as a response to external forcing linked to sea- and land-surface anomalies. Climate being defined as the mean of atmospheric states, it appears that it can be predicted up to a few months in advance, which is the characteristic time of the so-called slow components of the climate system. Forecasting can sometimes be extended to longer time ranges, especially when the coupled ocean–atmosphere system exhibits internal variability modes, with characteristic times of a few years. Seasonal climate forecasting is most often based upon Monte-Carlo simulations, where the various realisations correspond to slightly different initial conditions. The present sate-of-the-art in Europe (ECMWF) and/or in the USA (IRI) allows to forecast such major phenomena, as El Nino, up to six months in advance. Finally, some parameters may exhibit predictability at still longer time-ranges (inter-annual to decadal), but only for certain regions. The example of electricity production is used to underline the potentially large economical benefit of seasonal climate forecasting. To cite this article: J.-C. Andre et al., C. R. Geoscience 334 (2002) 1115–1127.

Two climate simulations of 150 years, performed with a coupled ocean/sea-ice/atmosphere model including stratospheric ozone, respectively with and without heterogeneous chemistry, simulate the tropospheric warming associated with an increase of the greenhouse effect of carbon dioxide and other trace gases since 1950 and their impact on sea–ice extent, as well as the stratospheric cooling and its impact on ozone concentration. The scenario with heterogeneous chemistry reproduces the formation of the ozone hole over the South Pole from the 1970s and its deepening until the present time, and shows that the ozone hole should progressively fill during the coming decades. To cite this article: J.-F. Royer et al., C. R. Geoscience 334 (2002) 147–154.