The tropical Atlantic is home to multiple coupled climate variations covering a wide range of timescales and impacting societally relevant phenomena such as continental rainfall, Atlantic hurricane activity, oceanic biological productivity, and atmospheric circulation in the equatorial Pacific. The tropical Atlantic also connects the southern
International audienceIn order to fulfill the society demand for climate information at the spatial scale allowing impact studies, long-term high-resolution climate simulations are produced, over an area covering metropolitan France. One of the major goals of this article is to investigate whether such simulations appropriately simulate the spatial and temporal variability of the current climate, using two simulation chains. These start from the global IPSL-CM4 climate model, using two regional models (LMDz and MM5) at moderate resolution (15-20 km), followed with a statistical downscaling method in order to reach a target resolution of 8 km. The statistical downscaling technique includes a non-parametric method that corrects the distribution by using high-resolution analyses over France. First the uncorrected simulations are evaluated against a set of high-resolution analyses, with a focus on temperature and precipitation. Uncorrected downscaled temperatures suffer from a cold bias that is present in the global model as well. Precipitations biases have a season- and model-dependent behavior. Dynamical models overestimate rainfall but with different patterns and amplitude, but both have underestimations in the South-Eastern area (Cevennes mountains) in winter. A variance decomposition shows that uncorrected simulations fairly well capture observed variances from inter-annual to high-frequency intra-seasonal time scales. After correction, distributions match with analyses by construction, but it is shown that spatial coherence, persistence properties of warm, cold and dry episodes also match to a certain extent. Another aim of the article is to describe the changes for future climate obtained using these simulations under Scenario A1B. Results are presented on the changes between current and mid-term future (2021-2050) averages and variability over France. Interestingly, even though the same global climate model is used at the boundaries, regional climate change responses from the two models significantly differ. © 2012 Springer-Verlag Berlin Heidelberg
Résumé (GIEC, 2007). Les études menées sur l'évolu-tion de la ressource en eau en France métropolitaine se sont principalement intéressées aux paramètres météorolo-giques (précipitation notamment) ou hydrologiques, tels que les débits ou les hauteurs des nappes. Ainsi, l'étude des longues séries climatologiques de préci-pitation sur la seconde moitié du XX e siè-cle en France a-t-elle montré une tendance significative à l'augmentation des sécheresses estivales (Moisselin et Dubuisson, 2006 (Vidal et al., 2010a). Des indices ont été déve-loppés à partir des variables de la chaîne SIM pour caractériser les différents types de sécheresses liées à un déficit sur une composante spécifique du cycle de l'eau : précipitation, humidité des sols ou débit des cours d'eau. Une climatologie originale des événements de sécheresse en France a été établie sur la période de 1958de à 2008de (Vidal et al., 2010b. La pertinence de ces travaux a été reconnue par l'attribution du prix Norbert Gerbier-Mumm 2011 de l'Organisation météorologique mondiale (OMM).Cet article rappelle d'abord la méthodo-logie appliquée pour la caractérisation des sécheresses puis il présente les outils opérationnels, dérivés du projet et actuellement disponibles pour le suivi hydrologique en France, au travers de l'analyse de l'événement du printemps 2011. Enfin, les résultats des études à partir des projections climatiques régio-nalisées sur la France seront détaillés pour préciser l'évolution attendue des sécheresses au cours du XXI e siècle et les principales incertitudes associées. La méthodologie de caractérisation des sécheresses Définition des indices de sécheresseUne sécheresse se définit comme un déficit hydrique d'une composante (au moins) du cycle hydrologique (Wilhite et Glantz, 1985
On December 12, 1999, the Erika tanker broke in two sections at about 30 miles from the Brittany coast in the Bay of Biscay, France. The two parts of the wreck sank a few hours after the break. Some 15,000 tons of heavy fuel were released into the manne environment. It is the most serious discharge that has occurred in France since 1980 (Tanio, 6,000 tons). The nature of the incident, the kind and quantity of oil spilled, and the prevailing weather conditions posed considerable response problems. The spilled oil drifted for 2 weeks before reaching the coast. Three different models were implemented by CEntre de Documentation de Recherche et d'Experimentations sur les pollutions accidentelles des eaux (CEDRE) within a couple of hours of the Erika sinking. On December 14, it appeared that the forecast of the MOTHY model was closer to reality.The MOTHY model was developed by Meteo-France (the French national weather service) to simulate the movement of pollutants in three dimensions. MOTHY is an integrated system that includes hydrodynamic coastal ocean modeling and realtime atmospheric forcing from a global model. Pollutants can be oil or floating objects. CEDRE contributes to the improvement and validation of the model using both experiments and interventions during actual pollution events. New developments, exercises, and training are jointly conducted. In the event of marine pollution, Meteo-France sends meteorological forecasts and pollutant drift forecasts to CEDRE. This response system has been operational since February 1994.The MOTHY model was used routinely for several weeks after the ship broke up. The model predicted that the coastline was at risk and that the beaching of the main slick would occur after 2 weeks. Diffuse pollution reached the coastline 1 or 2 days before the main slicks, about 200 km west of the main beaching. Hindcast runs and backward integration of the model explained this unexpected arrival of oil. Some pollution was still arriving onshore several weeks after the initial release. This longer-term pollution came from the wrecks, but also of older pollution by the coastal detachment and deposit tides. Using the model in conjunction with remote sensing information allowed operators to develop and then execute a response strategy rather than react only to observed information.
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