Statistical simulation of extreme temperatures in Zanjan based on climate scenarios

Climate is one of the most fundamental factors in the structure of the planet Earth. Undoubtedly, the biological (including human) and non-biological fields are deeply and widely affected by climatic conditions. Climate change can have many feedbacks and consequences. During the last 30 years, the frequency of some Frein accidents has increased, and it is expected that more hazards related to weather will occur in the future. Due to the increase in climatic extremes and natural hazards in Iran, which is characterized by ecological sensitivity, these events have a significant impact on the state of water resources, agriculture, energy, tourism, and bio-climatic conditions; Therefore, studying this field is an inevitable necessity. The main goal of the current research is to investigate the simulation of average values and minimum, maximum and average daily temperatures of Zanjan based on climate scenarios and using the SDSM model.

The method of carrying out descriptive-analytical research and the method of collecting data is library (documents). SDSM model and climate scenarios (RCP2.6, RCP4.5 and RCP8.5) have been used to simulate temperature variables. The data used includes the average, minimum and maximum daily temperature recorded at the Hamdid Zanjan station during the period of 1961-2021 and the data of the general atmospheric circulation model to simulate climate variables in future periods. In order to obtain the most suitable atmospheric variables for estimating triple temperature profiles, the relationship between dependent variables (minimum, average and maximum daily temperature) with independent atmospheric variables (NCEP) was examined to select independent variables and recalibrate the model for dependent variables. Also, the Markov chain model has been used to investigate the probabilities of Frein events. In order to recalibrate the SDSM model, the observational data of Zanjan station and the data of NCEP National Center for Prediction of Environmental Variables were divided into two periods: 1961-1990 and 1991-2005. The first period was used to calibrate the model.

The simulation results of the three studied temperature variables showed that in all scenarios, they will increase the most in the period of 2082-2100 compared to the values of these variables in the base period (1961-2021). The monthly review of the simulated data and the observed data of the studied variables showed that based on the studied scenarios and the SDSM model, it was determined that from 2022-2100 the minimum temperature will increase by 2 degrees, the maximum and average temperature by 3 degrees. The average minimum and average temperature will increase the most in January and February and the least in October. While the average maximum temperature will increase the most in August and the least in April.

Result shows that all seasons of the year will become warmer, especially the cold seasons of the year. In other words, the cold seasons will be shorter. The number of extreme frequencies observed in all three temperature parameters for the 25th and 75th quartiles is less than the number of simulated extreme temperature events in all three scenarios. The highest number of extreme low frequencies is expected in January and the highest number of extreme high frequencies is expected in July.