Quadrangle statistical downscaling method application to Mascara-Matemore in Algeria

Climate change consequences have become the concern of all countries. For this reason, scientists have been interested in the future climate prediction. In this study, coupled general circulation models (CGCMs) data precipitation are statistically downscaled by taking scenario data from the Community Climate System Model version 4 (CCSM4) and those from 42 rainfall stations, located at North-western Algeria, over the period 1971-2011. The period 1971-2005 is used for the model calibration and 2006-2011 for the model validation. Quadrangle statistical downscaling method (QSDM) was used with four scenarios (representative concentration pathway, RCPs: RCP2.6, RCP4.5, RCP6.0 and RCP8.5). The use of the spatial dependence function (SDF) allowed the CGCM data transfer to the Mascara-Matemore station. Therefore, monthly-downscaled rainfall amounts are generated from 2020 to 2100. Annual rainfall analysis, using moving average method, indicated a decreasing trend until 2100. The scenario RCP4.5 has been selected because of its minimal root mean square error (RMSE). The observed period (1971-2011) was compared to those projected (2020-2060 and 2060-2100). Monthly rainfall comparison exhibits a frequency decrease in low and high precipitation classes in addition to increase in the frequency of consecutive dry months (CDM).