Assessment of Downscaling Methods in Predicting Climatic Parameters under Climate Change Status: A case study in Ardabil Synoptic Station

Climate change is an unprecedented change are taking place. Changes of meteorological parameters such as precipitation, maximum and minimum temperatures. Since weather forecasting is important for these parameters, in this study, the performance of Statistical Downscaling Model (SDSM and Lars-WG) were used to predict temperature and precipitation and mean of these changes for the periods 2046-2065 compared to the base period 1983-2013 at Ardebil station and the model HadCM3 with A2 scenario were predicted. Downscaling models were used for data analysis were Lars-WG and SDSM. The results showed that the Lars-WG model with low mean absolute error for the stations is more accurate than SDSM model.