یاسر زکوی

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?

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.

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.

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.

Global warming process is one of the most important climate changes of the current century that researchers have addressed in regional and planetary scales. Global warming and climate change is one of the most important environmental issues in the world. The phenomenon of climate change, especially the increase in the minimum and maximum temperature of the studied area, will be overshadowed. Finding the future climate of each climate zone and examining the system of their changes and examining the consequences of climate change can open the way for planning. In this research, the author tries to show a perspective of the conditions of climate change in the next 50 years in Khuzestan province, emphasizing the element of temperature.

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.

According to the degree of correlation between the average temperature data and the predictor variable data, it has the highest correlation with the ncep_temp predictor variable, which is shown in graph (3) of the annual correlation between the ncep_temp predictor and the average temperature data. shows that the annual temperature in Ahvaz station is 96%, Abadan station is 95%, Dezful station is 94%, Shushtar station is 95%, Bagh Malek station is 88%, Bandar Mahshahr station is 94% and Omidiye Aghajari station is 95%. . The average temperature changes in the province is 25.7 with two optimistic and pessimistic scenarios with an increase of 0.4 and 0.7 respectively. Therefore, the trend of the temperature climatic element regarding the studied area and the future period is changing and increasing. In Khuzestan province, with optimistic and pessimistic scenarios, the frequency of heat waves increases by 2 and 1 days respectively. In the past period, in the northern regions of the province, Dezful station, Shushtar and the southeastern regions of Omidiyeh Aghajari province had the highest frequency of heat waves on average, 22, 19 and 18 days per year respectively.

.The most important results of its implementation are as follows: 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. 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 studies of temperature increase in Khuzestan province are aligned and consistent with the studies and researches of researchers such as Abbasnia (2016) and Ansari (2016). Because climate change can have an important effect on maximum and average temperature.The results of evaluating the performance of SDSM model using statistical tests and different error measurement indicators showed that this model is investigated in Khuzestan province and has a suitable accuracy for simulating climatic variables in the studied area.As a result, according to the monthly forecast for future periods, according to the existing scenarios, the results obtained are as follows:_ July is the hottest and January is the coldest month of the year in all studied stations of Khuzestan province during the forecast period.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. Based on this, the consequences of climate change in the southwest of the country (Khuzestan province) have been calculated. it will reduce the coldness of the air and moderate it, and severe frosts will be reduced. The study of hot days zoning shows an increase in the number of hot days in the future climate period, among other results of data analysis in the future period. The number of hot days has increased and it is consistent with Pudina's studies (2014). Investigating the spatial behavior of heat waves in Khuzestan province. The results showed that there are high occurrences of heat waves in the east and northwest of the province. They are significant in terms of location, in Dezful and Shushtar stations located in the north of the province and Omidiye Aghajari located in the south of the province, they decreased by almost 2 days and in the rest of the studied stations, they increased by an average of 4 days, which according to the research of Esmailnejad (2004) approximately It is aligned and in recent years, this consequence has been frequent. 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 number of dry days in the future will increase in all stations. Currently, finding out about the amount of climate changes and the behavior of climate variables in order to apply the necessary measures against the effects of climate change has been discussed and the focus of attention of many researchers, especially climatologists. Recognizing and evaluating climate changes in the coming decades with the aim of proper environmental planning in order to adapt to future climate conditions and reduce its effects is an effective matter.