Modeling and forecasting of climate parameters using CanESM2 model under RCP scenarios (case study: Karaj station)

Climate change is one of the most important challenges of this century. The consequences of these changes and how to adapt to them as well as reducing the causes of climate change are important points of this phenomenon. Currently, there is scientific and definite evidence about the warming of the earth and the unprecedented increase in temperature on the surface of the earth and the atmosphere caused by it is a human activity, it is a proof of this. The most important parameters affecting the phenomenon of climate change are precipitation and temperature.

The CanESM2 model was used to predict the climatic parameters of temperature, precipitation and wind speed under the RCP to predict the climate change in Karaj station.

The results showed that the average rainfall in the Karaj station was 96 mm in the historical period which is according to the scenarios RCP2.6, RCP4.5 and RCP 8.5 will decrease in the near future (2060 - 2030) and 62 % in the near future (2060 - 2030) and 81 % in the future (2070 - 2099) than the observed period (1985 - 2017). The results of the simulation of the average temperature according to RCP2.6, RCP4.5 and RCP8.5 scenarios showed that the average temperature in the future period is close to 0.53, 0.17 and 0.19% compared to the observation period (15.81 degrees Celsius) will decrease, while in the future period (2070-2100) under the RCP2.6 scenario, it will decrease by 1.11 percent and according to the RCP4.5 and RCP8.5 scenarios, it will increase by 0.39 and 2.13 percent. The average simulated wind speed showed that the wind speed was 27.89, 25.03 and 24.55% in the period from 2030 to 2060 and 34.16, 25.37 and 23.84% in the period from 207 to 2100 under the RCP scenarios compared to the value observed (2.41 m/s) will increase.

The evaluation results of CanESM2 model in this study can be considered as an acceptable statistical result to investigate the changes of climatic parameters. Observing the pattern of consumption and optimal use of water resources as well as preventing the increase of greenhouse gases can control the trend of increasing temperature and decreasing rainfall.