Impact of statistical bias correction on the projected climate change signals of the regional climate model REMO over the Senegal River Basin

Abstract

We assess the impact of a statistical bias correction method based on histogram equalization functions on the projected climate change signals of regional climate model (RCM) simulations over the Senegal River Basin in West Africa. Focus is given to projected changes in precipitation, temperature, and potential water balance (P − PET) following the RCP4.5 and RCP8.5 emission scenario pathways by the end of the 21st century (2071–2100) compared to the 1971–2000 reference period. We found that applying the bias correction substantially improved the simulations of present day climate for both temporal and spatial variations of the analysed climate parameters when compared to gridded observations data sets and station data. For the future, the non-corrected RCM projections show a general decrease of precipitation by the end of 21st century for both scenarios over the majority of the basin, except the Guinean highlands where a slight increase is found. The reduction in mean precipitation is accompanied by a projected increase in the annual number of dry days, most pronounced in the northern basin. Furthermore, a general temperature increase is projected over the entire basin for both scenarios, but more pronounced under the RCP8.5 scenario. In addition, the deficit in the water balance (P − PET) above 12°N is projected to increase in the future. Applying the bias correction to the RCM projections leads to a general dampening of the projected change signals, strongest in the case of heavy precipitation events. However, for all analysed parameters the general directions of change as well as the predominant large-scale change patterns are conserved after applying the bias correction.