North Khorasan Province HadCM3 droughts predicted by models and indicators of SPI and RDI

Abstract The simulated weather data for future planning in the field of natural and human resources is of paramount importance. Including the ability to forecast droughts, which in this case can be reduced with systematic planning of possible losses. In this study, data HADCM3 model under emission scenarios A1B, A2 and B1 to predict the meteorological data of North Khorasan province were simulated using LARS WG statistical dust. For this purpose, after calibration, validation and modeling data on selected stations, data base model in terms of compliance with simulated values (2012-1993-2032-2013) using three criteria Root Mean Square error (RMSE), mean absolute error (MAE) and mean bias error (MBE) were evaluated. Using indices SPI and RDI to get wet and drought periods during the simulated under the scenarios B1, A2, A1B was developed. . The results show that the frequency of droughts over the forecast period under all three scenarios compared to the baseline and annual month-long scale using SPI and RDI decreased to indicates % of the occurrences on the other hand grew wet. The highest frequency of normal class time devoted gained in both scale. More from the base period of the indices using SPI and RDI is predicted.Drought and climate phenomena will be appointed as part of the climate of a region. It has features that separates it from other natural disasters. Drought long-term shortage of rainfall in the period so that the moisture in the soil, causing reduced water flow And thereby disrupt human activities and natural life plants and animals. From a cognitive point of view of climate, when the rainfall received in a place in a certain period of time is less than average precipitation location, we are faced with drought (spunky, 1374).