| چکیده انگلیسی مقاله |
Introduction: By examining the trend of air temperature changes, it is possible to search for traces of climatic changes in the area of Iran. Temperature is one of the most important meteorological parameters that is used in many studies. This parameter is of special importance in climate change studies, as the increase in temperature is considered one of the most important human environmental issues. In this research, the purpose of the research is to look at the average temperature changes in the base and future period of Khuzestan province. The evaluation of the model and the reproduction of climatic variables and the perspective of the future climatic conditions are examined, and this question is raised: Is the Sdsm model in Khuzestan province highly accurate?
Materials and methods:The area studied in the current research is the synoptic stations of Khuzestan province. In this study, meteorological data including the values of minimum temperature, maximum temperature and average temperature for the studied period have been used. In this research, we used SDSM statistical micro-scale exponential model for temperature prediction and 6 synoptic stations of Khuzestan province, which had 45-year (1961-2005) and 40-year (1966-2005) climatic statistics, were selected. The outputs of the CanESM2 climate model have been used under RCP2.6 and RCP8.5 scenarios. The data of the base period (1961-2005) were used for the first 30 years of data (1961-1990) for calibration and the second 15 years (1991-2005) for the syntactic evaluation of the model performance. Error and accuracy measures are evaluated.
Results and discussion: MAE, NRMSE, RMSE, MSE and R2 were calculated based on the average values of the variables in each month. These values were obtained according to the daily temperature produced by the model and the observed values for calibration and validation data. The results showed that according to the NRMSE, the error rate in temperature estimation is acceptable (less than 10%) and is almost the same in all stations. The results showed that according to the high correlation coefficient of 87%, the performance of the model is confirmed. Finally, it indicates that the model has relatively good accuracy in estimating the climatic variable of temperature. In most stations, they overlap the most in the first months of the year, which is the reason for the accuracy of the model in the first months of the year. In the stations of Ahvaz, Bandar Mahshahr, Omidiye Aghajari and Bagh Malek in the first seven months of the year, the highest overlap and accuracy are included, and in the last five months of the year, the average retrospective temperature in these stations is 2.4, 2.4, 2.6 respectively. and 2.7 degrees Celsius shows the difference with the observational data. Dezful, Abadan and Shushtar stations have the highest overlap and accuracy in the first three months of the year and July. In the rest of the months, the average retrospective temperature in these stations is 2.6, 2 and 2 degrees Celsius, respectively, the difference with the data Shows observations. The temperature has increased in all periods and for the RCP2.6 scenario, it increases more than the RCP8.5 scenario. The highest RCP2.6 average temperature increase in Ahvaz is predicted to be 1.9 degrees and the lowest RCP8.5 increase is 0.2 degrees in Dezful and Shushtar stations. The average temperature in the forecast period with RCP2.6 and RCP8.5 scenarios is 26 and 25.7 degrees Celsius respectively, which shows an increase of 0.7 and 0.4 degrees compared to the previous period, and also the highest average temperature in the period Predicted with RCP2.6 and RCP8.5 scenarios and the observation period is approximately 28.2, 27.5 and 27.3 degrees Celsius corresponding to Shushtar station and the lowest average temperature is approximately 22.7, 22.6 and 22.2 degrees Celsius corresponding to Bagh Malek station respectively. In most of the studied stations, the increasing and decreasing trends of the observation and forecast period are similar. Aghajari station shows the most overlap. Shushtar, Abadan and Omidiye Aghajari stations have the highest temperature with an average temperature of 27.3, 26.5 and 26.4 degrees Celsius, respectively, and Bagh Malek station, which is located in the east of the province, has the lowest temperature with 20.9 degrees Celsius.
Conclusion: The most important results obtained from the performance evaluation of the SDSM model using statistical tests and various error measurement indicators showed that this model has been investigated in Khuzestan province and has the appropriate accuracy to simulate climate variables at the level of the studied region. It is absolutely necessary to evaluate the effects of global warming on the occurrence of climatic extremes. An increase in temperature has occurred in all studied stations in the coming period. In two scenarios, RCP2.6 (commitment of countries to reduce greenhouse gases) and RCP8.5 (in case of non-compliance to reduce greenhouse gases) were measured in the studied periods. Meanwhile, during the annual study period, the areas adjacent to the southern coasts of Iran will have the lowest temperature increase, so that the temperature increase in the stations located in the land is more than the stations in the coastal areas. The highest RCP2.6 average temperature increase in Ahvaz is predicted to be 1.9 degrees and the lowest RCP8.5 increase is 0.2 degrees in Dezful and Shushtar stations. In this research, the trends and types of seasonal changes have been investigated. The results obtained from the data analysis show that in all stations, in Khuzestan province in general, the average temperature parameter shows an increasing trend. Research has shown that the maximum temperature trend is an increasing trend in the base period of 1961-2005 and this trend will continue in the future periods. In the future periods, the temperature trend in the last few decades, the increase in the earth's temperature has upset the climate balance of the earth and has caused extensive climate changes in most areas of the earth, which is referred to as climate change. The minimum temperature is increasing, and as a result, it reduces the coldness of the air and moderates it. |