A Climate Change Simulation of the Temporal Movement in the First and Last Fall and Spring Frosts in Iran

Global warming and climate are two of the most important environmental challenges around the word. Agricultural sector heavily depends on climate changes. Climate, as the main factor of time, place, production resources and efficiency, has the main effect on agricultural activities. The date of first zero-degree temperature in the fall and its last occurrence in the spring are important. This information is useful in determining suitable species for planting. Global warming has caused changes in the agricultural climatic indices such as the date of occurrence of late spring and early fall frosts. The results of the studies done by researchers in Iran and various regions in the world in recent and ensuing decades represent movement of the occurrence of fall frosts and the last spring frost toward early winter and late winter, respectively.  The study area with latitude of 25 and 40° 00' N, longitude of 44 and 64° 00' E, and with an area of 1,648,195 square kilometers is located in IRAN. The study data consisted of two groups of observational and simulation data. Observational data includes data such as precipitation, radiation, daily maximum and minimum temperatures of 43 synoptic stations in various regions of Iran with full thirty-year (1981-2010). All data are collected from Iran Meteorological Organization. Simulated data of two future periods (2046-2065) and (2080-2099) by using the downscaling output of the two global climate models of GFCM21 and HadCM3 made the highest efficiency and the lowest simulation error in the temperature parameter estimation, being generated based on emissions scenarios (B1, A2, A1B) in version 5 of LARS-WG second group of data.
The Kolmogorov Smirnov Fitness test was used to estimate if probability distribution of generated data is close to the probability distribution of the monitored data of the stations under investigation. Mean and standard deviation of the data were analyzed using paired t-test and their significance was statistically significant at 0.05.
In this research, bootstrap method was used to investigate uncertainty. Bootstrap method is used to estimate the accuracy of estimators during independent observations. To calculate the confidence interval using bootstrapping method in SPSS software, at first, the monthly minimum time series of 30 years of stations (1981-2010) was prepared using Lars baseline and the range, mean and standard deviation of the monthly minimum temperature of each station were calculated at 99% level and compared with the mean and standard deviation of the minimum temperature of the observed data. If the estimated values of the models are within the confidence range of the observed data, it indicates the confidence in the desired level of trust and, if it is outside the range, it indicates the uncertainty to the estimated value.
Results and Discussion The validity of the Lars model in the simulation of the minimum temperature of the temperature with k-s test indicates that there is no significant difference between the simulated and the monitored data. Using T- test indicates that the differences except Bojnourd station in January, the station Bushehr and Shahr-e kord in March, Esfahan station in February and Zahedan station in August are not significant at 0.05 levels. In general, the LARS-WG model has an acceptable ability to simulate the minimum temperature data of the studied stations in Iran and the existing error is random.
The uncertainty analysis shows that the average of minimum temperature of months in all stations is 72.7% in the confidence range, but the standard deviation is 6.6% in the months in the confidence range. The results show a weakness of the model in estimating standard deviations. Two models and three scenarios are used to reduce uncertainty. Implementing several models and scenarios creates a wide range of analyses. In so doing, we can minimize uncertainty in the production of future weather data.
The results of the study indicate the movement of the first fall frost and the last spring frost in Iran is toward early winter and late winter, respectively, so that the first fall frost in the period 2046-2065 based on the GFCM21 model and the emission scenarios B1, A2 and A1B, will occur 13, 8 and 7 days later and in the HadCM3 model, and it will occur 9, 8 and 7 days later, respectively. In addition, in the period 2080-2099, based on the GFCM21 model and the scenarios B1, A2 and A1B, it will occur 18, 21 and 9 days later and in the HadCM3 model, it will occur 16, 21 and 9 days later, indicating a positive trend compared to the period 1981-2010. The greatest movement is observed in Khorramabad, Rasht and Gorgan stations. The changes in northeastern stations of Sabzevar and Semnan, the southern half of the country stations of Kerman, Bam and Abade, and most northwestern stations are less than other regions.
The last spring frost in the central climate based on the GFCM21 model and the emission scenarios B1, A2 and A1B will occur 16, 15 and 9 days earlier, and in the HadCM3 model, it will occur 13, 14 and 11 days earlier, respectively. In the 2080s, (2080-2099), the change based on the above-mentioned scenarios in the GFCM21 model will be 20, 22 and 13 days and in the HadCM3 model, it will be 20, 27 and 16 days, respectively. The most negative trend will be in Gorgan, Rasht, Ardabil and Shahr-e Kord stations. Khoy, Qazvin, Bam and Kashan will have the least negative movement.  The results observed in this study are consistent with the results of many previous studies investigating changes of date of the beginning and end of spring and fall frosts in Iran and other parts of the world and indicate the movement of the occurrence of the fall and spring frosts toward the winter frosts. Firstly, this time movement leads to reduced frost period and reduced production of rain fed wheat, and secondly, along with increasing length of the growing period, it increases evapotranspiration, drains soil moisture, reduces the flow of the hydrologic cycle change, and increases the plants’ need for water resulting in increasing use of water. These changes and their adverse effects could be a threat to achievement of sustainable development in our country. Thus, increasing awareness of how changes occur in the spatiotemporal distribution of frost indicators requires further studies and considerable attention in order to adopt strategies compatible with changes, particularly in Iran, which are more exposed to their destructive consequences.