Abstract
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.
Highlights
In semiarid areas, most of the available water resources for the production of hydroelectric energy, for drinking water, as well as for irrigated agriculture located downstream in the surrounding plains [1,2,3,4], comes from the mountainous regions [5]
The climate of the south Mediterranean mountain ranges faces a high spatiotemporal variability owing to steep precipitation and temperature gradients associated with a marked orography, to a strong seasonality of climate with most of the precipitation concentrated during the winter months [11,12] and, for the western regions, to the joint and complex influence of the synoptic flow originating from the Atlantic Ocean, from the Mediterranean sea and from the Sahara [13]
The projection of SAFRAN forcing is conducted in three steps corresponding to the three subsections below: (1) disaggregation of the 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
Summary
Most of the available water resources for the production of hydroelectric energy, for drinking water, as well as for irrigated agriculture located downstream in the surrounding plains [1,2,3,4], comes from the mountainous regions [5]. The climate of the south Mediterranean mountain ranges faces a high spatiotemporal variability owing to steep precipitation and temperature gradients associated with a marked orography, to a strong seasonality of climate with most of the precipitation concentrated during the winter months [11,12] and, for the western regions, to the joint and complex influence of the synoptic flow originating from the Atlantic Ocean, from the Mediterranean sea and from the Sahara [13] This high spatiotemporal variability, in addition to the inherent difficulty of access and the hard measuring conditions in mountainous regions, leads to strong observational issues: gauge network and radar observation are poor or nonexistent. This has led the scientific community to new developments, including new observation concepts based on remote sensing data and reanalysis systems merging atmospheric modelling with the available observations [14]
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