LONG-TERM PREDICTION OF THE CLIMATE VARIABLES IN NORTHERN SHORE OF IRAN ON UNCERTAINTY OF GLOBAL CLIMATE MODELS

In the near future climatic change can lead to different negative results on various systems including water, agriculture, environment, healthcare, industry and economy. The study purpose is to evaluate the future climate conditions in the northern shore of Iran. We used collection of long- term daily data of precipitation, minimum and maximum temperature and sunshine for 10 synoptic stations and monthly rainfall and temperature of coupled ocean- atmosphere models data In this study. First, the uncertainty and operation of the global climate models are evaluated for baseline period (1971-2000) and then stochastic weather generator model is validated and analyzed using statistical tests like K-S, T and F. The future data for 2011-2030 and 2046-2065 are generated for each station base on the Mpeh and Ncccsm models under three scenarios of SRA1B, SRA2 and SRB1. The prediction results showed that trend of temperature will be ascending and the minimum temperature will increase more than maximum temperature. In the first study course, maximum of increasing of temperature will be in September, October and November (autumn season) and in the second study course will be in July, august and September (summer season). Also, seasonal and monthly study of rainfall in both the models showed that the autumn and winter rainfall will increase and the maximum rainfall will occur in november in the Caspian Sea area. Summer rainfall about 13% and Spring rainfall about 5 % will decrease in comparison to the normal level.