Using GIS based algorithms for GCMs' performance evaluation

General circulation models (GCMs) are used for estimating future climate scenarios, run on a very coarse scale, so the outputs from GCMs need to be downscaled to obtain a finer spatial resolution. This paper provides a methodology for GCM-Ensembles performance evaluation using a GIS platform by applying statistical spatial downscaling methods. Statistical downscaling methods were used in the projection process after validation and performance evaluation using several techniques such as Taylor diagram for each GCM-ensembles within independent sub-periods. Climate change projections for the Shannon River catchment in Ireland were developed for temperature and precipitation from multi-GCM ensembles for three future time intervals forcing by different Representative Concentration Pathways (RCP). The changes in temperature and precipitation were spatially projected at a very fine spatial scale.