Le climat futur des régions méditerranéennes françaises : quelles tendances ? -

La forte sensibilité climatique de la région méditerranéenne, notamment celle des espaces forestiers, nécessite une meilleure prise en compte des projections climatiques pour le siècle à venir. Pour ce faire, l'information climatique mise à disposition doit être à haute résolution spatiale. D'une part pour prendre en compte de manière plus réaliste que les simulations globales, les contraintes et processus physiques d'échelle fine. Et, d'autre part, pour permettre à certaines communautés d'alimenter des modèles d'impacts par des variables atmosphériques scalairement cohérentes. Les méthodes de régionalisation statistiques et dynamiques sont les deux grandes approches méthodologiques permettant de produire une information climatique régionalisée, allant de 50 à 8 km de résolution horizontale en fonction de la méthode et de la région prise en compte. Les résultats de ces méthodes obtenues par la communauté climatique française mettent en évidence pour la fin de siècle une augmentation (diminution) des températures (précipitations) en été. En hiver une incertitude persiste sur l'amplitude du réchauffement, alors qu'aucune tendance sur les précipitations ne se dégage

A multi-model climate response over tropical Africa at +2 °C

The impact of a +2 °C global warming on temperature and precipitation over tropical Africa is examined, based on an ensemble of 12 regional climate model scenario simulations. These 12 scenarios are re-phased so that they all correspond to the same global warming of 2 °C with respect to pre-industrial conditions. The continental temperature increase is above the global average. If heat waves are defined with the same temperature threshold in the reference climate and in the scenario, their frequency increases by a factor of 10. When the temperature threshold is adapted to future conditions, there is still a slight increase in frequency. The average precipitation does not show a significant response, due to model-to-model spread. However two compensating phenomena occur, which are robust among the models: (a) the number of rain days decreases whereas the precipitation intensity increases, and (b) the rain season occurs later during the year with less precipitation in early summer and more precipitation in late summer. Simulated daily temperature and precipitation data are combined in two impact models, one for the hydrology of the Nile and Niger basins, one for the food security of the different countries. They show that the main feature of the climate change is not a continuous trend signal, but an alternation of dry and wet decadal to multidecadal episodes

The sub-seasonal to seasonal prediction (S2S) project database

A database containing sub-seasonal to seasonal forecasts from 11 operational centres is available to the research community and will help advance our understanding of the sub-seasonal to seasonal time range. Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the sub-seasonal to seasonal time range, a sub-seasonal prediction (S2S) research project has been established by the World Weather Research Program/World Climate Research Program. A main deliverable of this project is the establishment of an extensive database, containing sub-seasonal (up to 60 days) forecasts, 3-weeks behind real-time, and reforecasts from 11 operational centers, modelled in part on the THORPEX Interactive Grand Global Ensemble (TIGGE) database for medium range forecasts (up to 15 days). The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the sub-seasonal to seasonal time range that has been considered for a long time as a “desert of predictability”. In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of sub-seasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models underestimate significantly the amplitude of the Madden Julian Oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database represents also an important tool for case studies of extreme events. For instance, a multi-model combination of S2S models displays higher probability of a landfall over Vanuatu islands 2 to 3 weeks before tropical cyclone Pam devastated the islands in March 2015

Development of a European Multi-Model Ensemble System for Seasonal to Inter-Annual Prediction (DEMETER)

A multi-model ensemble-based system for seasonal-to-interannual prediction has been developed in a joint European project known as DEMETER (Development of a European Multimodel Ensemble Prediction System for Seasonal to Interannual Prediction). The DEMETER system comprises seven global atmosphere–ocean coupled models, each running from an ensemble of initial conditions. Comprehensive hindcast evaluation demonstrates the enhanced reliability and skill of the multimodel ensemble over a more conventional single-model ensemble approach. In addition, innovative examples of the application of seasonal ensemble forecasts in malaria and crop yield prediction are discussed. The strategy followed in DEMETER deals with important problems such as communication across disciplines, downscaling of climate simulations, and use of probabilistic forecast information in the applications sector, illustrating the economic value of seasonal-to-interannual prediction for society as a whole

Le climat futur des régions méditerranéennes françaises : quelles tendances ? -

International audienceLa forte sensibilité climatique de la région méditerranéenne, notamment celle des espaces forestiers, nécessite une meilleure prise en compte des projections climatiques pour le siècle à venir. Pour ce faire, l'information climatique mise à disposition doit être à haute résolution spatiale. D'une part pour prendre en compte de manière plus réaliste que les simulations globales, les contraintes et processus physiques d'échelle fine. Et, d'autre part, pour permettre à certaines communautés d'alimenter des modèles d'impacts par des variables atmosphériques scalairement cohérentes. Les méthodes de régionalisation statistiques et dynamiques sont les deux grandes approches méthodologiques permettant de produire une information climatique régionalisée, allant de 50 à 8 km de résolution horizontale en fonction de la méthode et de la région prise en compte. Les résultats de ces méthodes obtenues par la communauté climatique française mettent en évidence pour la fin de siècle une augmentation (diminution) des températures (précipitations) en été. En hiver une incertitude persiste sur l'amplitude du réchauffement, alors qu'aucune tendance sur les précipitations ne se dégage

Evaluation of Probabilistic Quality and Value of the ENSEMBLES Multimodel Seasonal Forecasts: Comparison with DEMETER

The performance of the new multimodel seasonal prediction system developed in the framework of the European Commission FP7 project called ENSEMBLE-based predictions of climate changes and their impacts (ENSEMBLES) is compared with the results from the previous project [i.e., Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER)]. The comparison is carried out over the five seasonal prediction systems (SPSs) that participated in both projects. Since DEMETER, the contributing SPSs have improved in all aspects with the main advancements including the increase in resolution, the better representation of subgrid physical processes, land, sea ice, and greenhouse gas boundary forcing, and the more widespread use of assimilation for ocean initialization. The ENSEMBLES results show an overall enhancement for the prediction of anomalous surface temperature conditions. However, the improvement is quite small and with considerable space-time variations. In the tropics, ENSEMBLES systematically improves the sharpness and the discrimination attributes of the forecasts. Enhancements of the ENSEMBLES resolution attribute are also reported in the tropics for the forecasts started 1 February, 1 May, and 1 November. Our results indicate that, in ENSEMBLES, an increased portion of prediction signal from the single-models effectively contributes to amplify the multimodel forecasts skill. On the other hand, a worsening is shown for the multimodel calibration over the tropics compared to DEMETER. Significant changes are also shown in northern midlatitudes, where the ENSEMBLES multimodel discrimination, resolution, and reliability improve for February, May, and November starting dates. However, the ENSEMBLES multimodel decreases the capability to amplify the performance with respect to the contributing single models for the forecasts started in February, May, and August. This is at least partly due to the reduced overconfidence of the ENSEMBLES single models with respect to the DEMETER counterparts. Provided that they are suitably calibrated beforehand, it is shown that the ENSEMBLES multimodel forecasts represent a step forward for the potential economical value they can supply. A warning for all potential users concerns the need for calibration due to the degraded tropical reliability compared to DEMETER. In addition, the superiority of recalibrating the ENSEMBLES predictions through the discrimination information is shown. Concerning the forecasts started inAugust, ENSEMBLES exhibitsmixed results over both tropics and northernmidlatitudes. In this case, the increased potential predictability compared to DEMETER appears to be balanced by the reduction in the independence of the SPSs contributing to ENSEMBLES. Consequently, for the August start dates no clear advantage of using one multimodel system instead of the other can be evidenced. © 2011 American Meteorological Society

Evaluation of Probabilistic Quality and Value of the ENSEMBLES Multimodel Seasonal Forecasts: Comparison with DEMETER

The performance of the new multimodel seasonal prediction system developed in the framework of the European Commission FP7 project called ENSEMBLE-based predictions of climate changes and their impacts (ENSEMBLES) is compared with the results from the previous project [i.e., Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER)]. The comparison is carried out over the five seasonal prediction systems (SPSs) that participated in both projects. Since DEMETER, the contributing SPSs have improved in all aspects with the main advancements including the increase in resolution, the better representation of subgrid physical processes, land, sea ice, and greenhouse gas boundary forcing, and the more widespread use of assimilation for ocean initialization. The ENSEMBLES results show an overall enhancement for the prediction of anomalous surface temperature conditions. However, the improvement is quite small and with considerable space time variations. In the tropics, ENSEMBLES systematically improves the sharpness and the discrimination attributes of the forecasts. Enhancements of the ENSEMBLES resolution attribute are also reported in the tropics for the forecasts started 1 February, 1 May, and 1 November. Our results indicate that, in ENSEMBLES, an increased portion of prediction signal from the single-models effectively contributes to amplify the multimodel forecasts skill. On the other hand, a worsening is shown for the multimodel calibration over the tropics compared to DEMETER. Significant changes are also shown in northern midlatitudes, where the ENSEMBLES multimodel discrimination, resolution, and reliability improve for February, May, and November starting dates. However, the ENSEMBLES multimodel decreases the capability to amplify the performance with respect to the contributing single models for the forecasts started in February, May, and August. This is at least partly due to the reduced overconfidence of the ENSEMBLES single models with respect to the DEMETER counterparts. Provided that they are suitably calibrated beforehand, it is shown that the ENSEMBLES multimodel forecasts represent a step forward for the potential economical value they can supply. A warning for all potential users concerns the need for calibration due to the degraded tropical reliability compared to DEMETER. In addition, the superiority of recalibrating the ENSEMBLES predictions through the discrimination information is shown. Concerning the forecasts started in August, ENSEMBLES exhibits mixed results over both tropics and northern midlatitudes. In this case, the increased potential predictability compared to DEMETER appears to be balanced by the reduction in the independence of the SPSs contributing to ENSEMBLES. Consequently, for the August start dates no clear advantage of using one multimodel system instead of the other can be evidenced