• Tunisia;
  • precipitation;
  • climate change;
  • regional climate models


Northern Tunisia is the rainiest part of the country where most of the water management structures (dams, reservoirs, etc) are located. Its strategic situation with respect to surface water resources encourages the investigation of the climate change impacts projected by climate models. The goal of this study is first to compare the observed precipitation with climate model outputs, and then to evaluate the future changes projected by different climate models. The study area is subdivided into four regions: the upstream and downstream transboundary Medjerda basin, the northern coastal basins and the eastern coastal basins. A database provided by the Tunisian hydrological service includes 388 stations with complete monthly precipitation data over the period 1961–2000. An ensemble of Regional Climate Models (RCM) simulations provided by the European Union-funded project ENSEMBLES are used. Six RCM model runs (CNR-A, DMI-A, DMI-B, ICT-E, SMH-B and SMH-E) are analysed, for the control period 1961–2000 and two projection periods, 2011–2050 and 2051–2090. The models efficiency in reproducing seasonal precipitation amounts and variability is evaluated. A 1-km monthly precipitation reference grid is computed through the interpolation of rainfall observations during the period 1961–2000 with kriging techniques. Monthly precipitation series averaged over the four basins are built for comparison during the control period. The RCM outputs are evaluated with respect to the annual precipitation cycle and rainfall frequency distribution using robust statistics. For the control period, features of the seasonal regimes are well reproduced by all models. It is found that models underestimate seasonal precipitation on average by 20%. The discrepancy between model outputs and observations depends on the season. For the future, in summer and autumn the different models do not project major changes in the seasonal distributions. However, for winter and spring, all the models project a significant decrease of precipitations. Copyright © 2013 Royal Meteorological Society