عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Climate as a complex system is changing due to an increase in atmospheric concentration of greenhouse gases produced by human activities, according to IPCC reports, leading to global warming .Assessing the climatic characteristics and identifying the climatic elements and parameters of a region can have a major role in land use planning and the management of that region. Variations in the component of temperature, as one of the most important climatic elements in the North West region of Iran, with significant spatial and temporal fluctuations, have a major role in the environmental management, road transportations, agriculture farming. So dealing with climatic change requires strategies for future adaptation. One of the most common methods for assessing the future climate is using the general atmosphere circulation models. A group of these models provide useful information about the atmosphere's reaction to the increase in the concentration of greenhouse gases. Considering the low spatial clarity of the general atmosphere circulation models and the need for powerful software as well as the great amount of time that dynamic downscaling consumes, the statistical models were taken into consideration. These models change the general circulation data from large scales to smaller ones and use the output of GCM models and other special scenarios of the model that generate meteorological data.The most important advantages of these models include their inexpensive, high speed and capability of being used without the need of supercomputers. One of these statistical models is LARS-WG that we used in this paper to simulate tempreture for future in North West of Iran.
The method of this research consists of two fundamental stages: first, downscaling the GCM data under the propagation scenario and the second step involves the clustering the daily temperature based on the past (1961-1990) and future periods (2011-2040) and comparison between these two periods. In the first stage of this research, for the statistical downscaling of the atmosphere general circulation model HadCM3 data based on the A1 scenario, the LARS-WG model, the 5.11 version was used, as one of the most famous models in generating random weather data. In this article, for evaluating the validation of the LARS-WG model in reproducing the meteorological data of temperature as the main component, data of the seven synoptic stations of Tabriz, Ardebil, Kermanshah, Hamedan, Sanandaj, Oroomieh, and Qazvin, in the North West of Iran for a 20-year period 1989-2008 were used. Note that by using statistics of the determination coefficient (R2), Root Mean Square Error (RMSE) and the Mean of Absolute Error (MAE), data evaluation produced by the model and the real data (observations) was done in the 1980-2008 period. In the second part of the research, the method of comparison of daily temperature components in different clusters, and based on the clustering approach within 6 conventional clusters for all the stations and the studied periods, was performed.
Results and Discussion
Although the comparison of monthly data for the two studied periods, July and January as the hottest and coldest months of the year respectively, had no changes in ranking compared with other months: the total average temperature of Jan has been changed -1.27 °C for the observational period and -0.86 °C for the future, on the other hand, the average of time series of the observational data were 24.2°C in July which will reach 25.12°C with the occurrence of climate change. Evaluations show that as a result of global warming, the maximum increase in the average annual temperature is seen 2.30°C for Ardebil and the minimum 0.22°C for Oroomeih. The results show that based on the statistical period of the past decades, the maximum average annual temperature is observed 13.94°C for Qazvin and the minimum 9.05°C for Ardebil. Although these conditions will change in the future and the warmest station will be Kermanshah, with the average annual temperature 15.64°C, it will be Ardebil station that will be presented as the coldest station with the average of 11.35°C.
Among the results of this research, the overall mean annual temperature increase for 7 studied stations was at the rate 0.94° C for the predicted years compared to the basic period 1961-1990. In evaluating the frequency of the thermal thresholds of the observational period which was done based on the scale of the six clusters, in most of studied stations, the highest frequency of days belongs to the sixth cluster. But the simulated data show the maximum concentration of the thermal data frequency for the first cluster in the case of Qazvin, Hamedan, Sanandaj, Oroomeih, and Tabriz stations.
In general, comparison between different stations in this area shows that the thermal thresholds of two stations namely Ardebil (in the clusters two to six), Oroomeih (First to Six) and Kermanshah (the clusters two to four) will be increased, while in other cases the thermal threshold will be decreased in the next 30 years. Therefore, one of the practical results of this research is its application in the agriculture. Based on the results of this research, we can conclude that the length of the crop growth period will be increased due to an increase in threshold and extension of warm periods. But it is obvious that the outcomes of warming and the lengthening of the growth season will have more serious consequences like the increase in water demand due to longer warm season, evaporation and perspiration increase in the growth of some crops and sometimes vegetation water stress, changing the planting time, development and disorder in adjustment of North West region.