عنوان مقاله [English]
Temperature is one of the fundamental elements of the climate of an area, whose transformation can transform the climate structure of any place, for this reason, the study of the temperature trend in different temporal and spatial rules occupies a large part of climatology researches. Most of what is referred to as global warming or climate change includes mostly warming changes and the upward trend of the three components (average, minimum and maximum) of air temperature. Currently, climate threshold phenomena are in the center of researchers' attention because the risk of increasing the frequency, duration and sensitivity of climate thresholds has increased due to the increase of greenhouse gases and aerosols in the atmosphere. The LARS-WG model is a model that downscales the output of GCM models.
Researches that focus on the temperature parameter; It is increasing day by day, among them is the research related to the increase in frequency, intensity, recorded global warm periods and the continuity of heat waves, which was done by Perkins et al. (2012). Yu et al. (2019), in their study investigated the temperature changes in the world and the results showed that the temperature anomaly is higher in the oceans and southern latitudes compared to the land and northern latitudes. Hu and Huang (2020) investigated the high temperature anomaly and its relationship with the general circulation of the atmosphere, and the results of their research showed that the highest temperature anomaly occurred in the Arabian Peninsula. Rohbakhsh Sigaroudi et al. (2017) investigated the anomaly of the average minimum and maximum temperature of the warm period of Iran in the period (1951-2010) and concluded that the western half of the country had the largest decrease in the average minimum and maximum temperature. Karmi-Mirazizi et al. (2018) investigated the synoptic patterns that lead to temperature anomalies and thermal changes in the western and northwestern regions during the statistical period (1989-2018). Rababi Sabzevari et al. (1401), in the west and northwest of Iran, analyzed the synoptic patterns that lead to temperature anomalies for 1989 to 2018, and the results indicate the existence of the mid-latitude meridional current as the main cause of temperature anomalies.
Ardabil province is located in the northwest of the Iranian plateau with an area of 17,953 square kilometers and has the coordinates of 37 degrees 7 minutes to 39 degrees 43 minutes north latitude and 47 degrees 19 minutes to 48 degrees 55 minutes east longitude. In this research, in order to achieve the goal of the research, the long-term statistics of the minimum, maximum and daily temperature averages of the selected synoptic stations of Ardabil province (Ardabil, Pars Abad and Meshginshahr) were analyzed. For this purpose, first, the different intensities of the temperature anomalies of the stations were calculated based on the data of 1980-2020 using the Z index. Then, to generate the data of each station under the conditions of climate change, after the preparation and quality control of the data, the variables of minimum and maximum temperature, precipitation and sunny hours were entered into the LARS-WG model on a daily basis and following the evaluation of the ability of the LARS-WG model in simulating the data observed in these stations, the data of the future period (2021-2021) of these stations was produced, and the ability of the LARS-WG model in simulating the data observed in the synoptic stations of Ardabil province was evaluated. This process is divided into three stages, which include spatial analysis, model validation, and generation of synthetic weather data. The model used is CanESM2 under RCP scenarios. The daily minimum, maximum and average temperature data of synoptic stations during the past statistical period (from 1980, 1985 and 1995 to 2020, respectively) were used to evaluate temperature changes and anomalies in the coming decades (2021-2100) And the frequency of each of the temperature anomaly intensity ranges of the three studied variables was counted and their percentage was calculated. Temperature anomalies were calculated using Z index.
The comparative graphs between minimum and maximum temperature observation data values and their values produced by LARS-WG model for selected stations of Ardabil province confirm the existence of a small difference between these two data and show the high efficiency of this model in simulating Creating the studied variables and producing synthetic air data. The evaluation of the frequency of anomalies of the three components of temperature in this province under three RCP scenarios showed that in the hot months of the coming period, warm anomalies are predominant (more than 50%) and normal conditions are second (30 percent) and cold anomalies have the lowest percentage.
The predicted frequency of temperature anomalies using the CanESM2 model fine-tuning under the average scenario (RCP4.5) is higher than the optimistic scenario (RCP2.6) and under the pessimistic scenario (RCP8.5) is higher than the average scenario. The difference between the estimates of the RCP8.5 and RCP2.6 scenarios and the maximum difference between the two hot and cold anomalies reaches its maximum in August. The highest and the lowest percentage of average warm anomaly frequency belong to Pars-Abad and Meshkin-Shahr, respectively. The highest percentage of cold anomaly was calculated in Ardabil and the lowest in Pars-Abad.
The order of the different intensities of the temperature anomalies of the three studied components in Ardabil province under the RCP4.5 scenario, from the highest to the lowest percentage, is: normal conditions (31%), moderate heat (29.4%), weak heat (21.4 percent), very hot (6.5 percent), slightly cold (6.1 percent), moderately cold (4.2 percent), very cold, extremely hot and extremely cold (about 1.5 percent)). It can be observed that among the types of temperature anomaly intensities, there is a predominance of moderate heat and weak heat, and extremely hot and extremely cold anomalies are rare and include about 1%. In the other two scenarios, the percentage of warm anomaly prevails over normal conditions and cold anomaly.
In the RCP2.6 scenario, the warm anomaly has the highest frequency in August and the lowest frequency in October, and the cold anomaly has the lowest frequency in August and the highest frequency in September. In the RCP8.5 scenario, the warm anomaly is more frequent in August and July and the cold anomaly is more frequent in May and June.