| This study assesses future changes in low precipitation patterns over land around the globe underthe SRES A1B scenario. We use global precipitation data sets derived by the super-high-resolutionAtmospheric General Circulation Model of the Japan Meteorological Agency and MeteorologicalResearch Institute (MRI-AGCM3.1S) and Atmospheric Ocean coupled General CirculationModels (AOGCMs) compiled in the phase 3 of the Coupled Model Intercomparison Project(CMIP3). The low precipitation patterns refer to the temporal and spatial distribution of annualminimum of accumulated precipitation over a given time interval using occurrence probability andobservation windows in unfixed seasons. As for the low precipitation patterns, this study assesseslow precipitation quantiles in six probability levels approximated by the Weibull distribution usingannual minima of monthly accumulated precipitation over 1-, 3-, 6- and 12-month time intervals.Also, low precipitation occurrence season were assessed from the centroid of the frequencydistribution of the ending months with annual minima of the low precipitation over the four timeintervals. The capability of the model of reproducing current low precipitation patterns wasexamined in reference to the global precipitation observation data set of VASClimO, from whichMRI-AGCM3.1S showed the best performance among all models. The MRI-AGCM3.1Sprojections, as well as the multi-model ensemble mean calculated over 16 GCMs, indicate that 0.1probability low precipitation quantiles in 3- and 6-month intervals would decrease by 10 to 50 %in Mexico, southern Brazil, southern Argentina, Mediterranean area and southern Africa with highmodel consistency. The projected shifts in low precipitation occurrence seasons were of concern,however, they show a considerable degree of uncertainty with low model consistency. |
