Abstract
Using the outputs of Global Circulation Models (GCM) has nowadays developed in meteorological and climatology studies and could compensate more computational vacuity. The resolution of global and local circulation models have recently increased, but none of these models could predict actual weather in station and micro scale. Thus, several methods are presented for using outputs of these models. These outputs are divided into statistical and dynamic groups and are known as Down Scaling Methods. In this paper, the researcher has tried to recognize and select the best climate scenario that fits the observation data of the selected area (stations of Khorasan Razavi Province) and using special statistical and dynamic methods to produce optimum data that fits the actual data. Then, by Down Scaling then, we could extract improved forecast data. Finally, by using Standard Precipitation Index (SPI), we can present drought status in future. Keywords: Drought prediction, Global Circulation Models (GCM), Down Scaling Methods, climate scenario, Standard Precipitation Index (SPI).
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