• Energy Research

Abstract. SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.

Abstract. Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, like mean duration, mean affected area and total magnitude. This paper addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) are downscaled climate projections able to reproduce spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century? (3) How to use standardized drought indices to represent theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-yr multilevel and multiscale drought reanalysis over France. Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index and the Standardized Soil Wetness Index, respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well reproduced by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals, either retrospective or prospective, and by taking advantage of the statistical properties of the standardized drought indices. The perceived spatio-temporal characteristics of drought events derived from these theoretical adaptation scenarios show much reduced changes, but they call for more realistic scenarios at both the catchment and national scale in order to accurately assess the combined effect of local-scale adaptation and global-scale mitigation.

The main objective of this paper is to study the impacts of climate change on the hydrological cycle of the main French river basins, including the different uncertainties at stake. In particular, the relative importance of modeling uncertainty versus that of downscaling uncertainty is investigated. An ensemble of climate scenarios are statistically downscaled in order to force a hydrometeorological model over France. Then, the main changes in different variables of the hydrological cycle are studied. Despite large uncertainties linked to climate models, some robust signals already appear in the middle of the 21st century. In particular, a decrease in mean discharges in summer and fall, a decrease in soil moisture, and a decrease in snow cover, especially pronounced at the low and intermediate altitudes, are simulated. The low flows become more frequent but generally weak, and uncertain changes in the intensity of high flows are simulated. To evaluate downscaling uncertainties and assess the robustness of the results obtained with the statistical downscaling method, two other downscaling approaches are used. The first one is a dynamical downscaling methodology based on a variable resolution atmospheric model, with a quantile‐quantile bias correction of the model variables. The second approach is based on the so‐called anomaly method, that simply consists of perturbing present climate observations by the climatological change simulated by global climate models. After hydrological modeling, some discrepancies exist among the results from the different downscaling methods. However they remain limited and to a large extent smaller than climate model uncertainties, which raises important methodological considerations.

Abstract. The repetition of droughts in France has led to a growing demand for irrigation water and consequently to an increase in requests for the construction of small farm dams. Although such dams are small, their accumulation in a basin affects river flows, because the water collected in these small farm dams is used for irrigation and thus does not contribute to river flow. In order to gain more insight into their impact on the annual and monthly discharges, especially during dry years, a small farm dam model was built and connected to a hydrometeorological model. Several scenarios with different volume capacities, filling catchment sizes and filling periods were tested for such dams. The results were analysed in a small basin in western France, where the pressure for building such dams is high, and then extended to the entire country. It was found that, due to the hydrometeorological conditions (mainly low precipitation compared to other regions in France), the development of small farm dams in north-western France would result in greater decreases in river flows and less efficient filling of small farm dams than in other regions. Therefore, such dams might not be as efficient as expected in supplying water to farmers when needed. Moreover, the ability to fill small farm dams is projected to decrease in a context of climate change, despite the uncertainty on the evolution of precipitation, thus worsening the situation.

In semiarid areas, the climate is characterized by strong spatiotemporal variability while the meteorological ground network is often very sparse. In this context, the spatial distribution of meteorological variables is thus a real issue for watershed hydrology, agronomy and the study of surface–atmosphere retroaction in these regions. The aim of this study is twofold: (1) to evaluate and to adapt a reanalysis system “Système d’Analyse Fournissant des Renseignements Adaptés à la Nivologie” (SAFRAN) to map the meteorological variables on the Tensift catchment (Morocco) between 2004 and 2014; (2) to project temperature and precipitation for the 2041–2060 horizon at high-resolution based on the Euro-CORDEX database at 12 km resolution (using two Representative Concentration Pathway -RCPs- scenarios and four Regional Climate Models), on the SAFRAN reanalysis and on a network of meteorological stations. SAFRAN was assessed: (1) based on leave-one-out for a station located in the plain and another in the mountains; (2) by comparison to another re-analysis system named the Meteorological Distribution System for High-Resolution Terrestrial Modeling (MicroMet); (3) by comparison to in situ measurements of snowfall at one station and to the daily Snow Cover Area derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) product at the catchment scale. The evaluation of the SAFRAN reanalysis showed that an irregular grid up to 1 km resolution is better for reproducing meteorological variables than the regular version of SAFRAN at 8 km, especially in mountains. The projection of the SAFRAN forcing is conducted in three steps corresponding to the three subsections below: (1) disaggregation of the Euro-CORDEX climate scenarios using the Q–Q approach based on stations data; (2) computation of the spatialized delta-change between historical and future Euro-CORDEX runs after Q–Q correction; (3) futurization of SAFRAN using the spatialized delta change values. The mountainous area is expected to face a higher increase in air temperature than the plains, reaching +2.5 °C for RCP8.5 and +1.71 °C for RCP4.5 over 2041–2060. This warming will be accompanied by a marked decrease in precipitation (−16% for RCP8.5). These present and future spatialized data sets should be useful for impact studies, in particular those focusing on water resources.