SDSM ability in simulate predictors for climate detecting over Khorasan province

Abstract

We know, the global circulation models (GCMs) enable to simulate the global climate, with the field variables being represented on a grid points 300km apart. But, the most recent generation of general circulation models (GCMs) still has serious problems. GCMs Models are benefit for detecting Climate change and zone on a special parameter. Even if global climate models in the future are run at high resolution there will remain the need to ‘downscale’ the results from such models to individual sites or localities for impact studies. But it is necessary to know if this category of Data has enough ability to simulate predictor Variables in the selected Region. In this study we selected reliable synoptic stations throughout the Iran that had less 41 year Data for case study and Using HadCM3 for Global Circulation Model Data, NCEP/NCAR for Reanalysis and SDSM Model for downscaling GCMs. Period of 1961-2001 was selected for Evaluated periods. The Result was shown that there was good ability to simulate predictant such as minimum and maximum temperature and precipitation and there is no significant deference with 0.5 critical errors. With using Data constructed for the future in SPI (Standard Precipitation Index) we could detect climate change in this region for future and it will improve climate risk management.