Evaluation of CanESM2 output capability in simulation of Yasuj weather predictor by SDSM

Climate plans are used in macro-planning, especially for natural disasters (Rezaei et al., 2015). Statistical micro-distribution methods are more efficient due to easy and cheap calculations (Diersing, 2009). One of the statistical models is the SDSM model, which is the relationship between large-scale predictors and local-scale predictors based on multiple linear regression methods. According to research, the SDSM model has an acceptable accuracy in clustering micro data. On the other hand, due to the importance of Yasuj station and its location in Karun catchment area and the need for planning to manage water resources in this basin, the present study uses CanESM2 output, which is one of the climate change models of CMIP5. The IPCC, simulates and examines climate and temperature variables at Yasuj station from 2020 to 2067.​​Study Area Yasuj is a city in southwestern Iran, the capital of Kohgiluyeh and Boyer-Ahmad Province, located on the banks of Bashar River, at the hillsides of the Dena Peak. Yasuj city is located in a cold climate region and has a temperate climate that tends to be cold.
Study

The SDSM microcontroller model was developed in 2002 in the UK by Wilby and Dawson. This model is based on daily local climate data (temperature and precipitation) and large-scale NCEP regional data. The canESM2 model is the fourth generation of climate models developed by the Canadian Center for Climate Modeling and Analysis (CCCMA) and networks the earth in the form of cells measuring 128 x 64 (Charron 2016). In this study, NCEP observational data were used to compile monthly models and canESM2 model outputs were used to predict the amount of variables using SDSM software. NCEP atmospheric variables enter the regression equation of the SDSM model. After selecting the predictors, the observational data of the Yasuj Synoptic Station and the data of the National Center for Predicting Environmental Variables of Canada (NCEP) were calibrated. Then, in order to ensure the calibrated model, temperature and precipitation for the period 2035-2020 were simulated and by comparing the observed and simulated data, the efficiency of the model for Yasuj station was investigated.

In this study, based on the observed data and the global model canESM2, the mean minimum and maximum temperature and average precipitation during the three periods of 2035-2020, 2051-2036 and 2067-2052 were compared with the base period of 2005-2007 under three RCP2 scenarios. RCP2.6, RCP4.5 and RCP8.5 were simulated for Yasuj station and the accuracy of the model was evaluated. The maximum agreement is at the minimum and maximum temperatures of the observed and simulated data, which show the appropriate and acceptable efficiency of simulating the desired climatic parameters for the period. In general, the amount of precipitation will increase in all studied future periods. This increase will be more evident than RCP2.6 according to the RCP4.5 and RCP8.5 scenarios. In general, the maximum minimum temperature during the period 2035-2020 shows an increasing anomaly of about 0.5 degrees and in the future periods 2051-2036 and 2067-2052 it shows a decrease compared to the base period. The lowest minimum temperature is estimated for January 2035-2020 under the RCP8.5 scenario.The maximum temperature of Yasuj station during the periods shows an increase. Incremental changes are less in June and August and more in January to May as well as in October, November and December. Of course, these changes are more noticeable in November and April. The highest temperature in the coming years will be related to July of 2051-2036 under the RCP4.5 scenario.

According to the results, it was found that precipitation in the coming years will show an increasing anomaly, which is faster in the first period and slower in the final periods.Slight changes in precipitation along with increasing temperature have affected the quality of water resources. This is due to the importance of this station in Karun catchment. Therefore future planning of water resources management should deal with the least quantitative and qualitative effects of water resources in the basin.