Journal of Spatial Analysis

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Thunderstorm is one of the most severe atmospheric disturbances in the world and also in Iran, which is characterized by rapid upward movements, abundant moisture, and climatic instability. Since this phenomenon is usually accompanied with hail, lightning, heavy rain, flood and severe winds, it can cause irreparable damage to the environment. Investigation of spring thunderstorms has a great significance regarding the irreparable damages can cause by them and also because of the higher frequency of this phenomenon in the spring and the necessity for preparedness and disaster mitigation actions. To identify the locations of the major thunderstorm risk areas, the entire country with an area of 1648195 square kilometers, which is located between the 25°-40° north latitude and 44°-63° east longitude is considered.     Spatial distribution of the occurrence of hazardous spring thunderstorms was analyzed using a series of monthly thunderstorm frequency data obtained from 25 synoptic stations over a 51-year-long period (1960-2010). Ward's hierarchical clustering and Kriging methods were used for statistical analysis. Initially, total number of thunderstorms in April, May and June were considered as the frequency of occurrence of thunderstorm in different stations in the spring. Measure of central tendency and dispersion which consists of the sum, minimum, maximum, range and coefficient of variation, standard deviation, and skewness were used to clarify the changes of thunderstorms and to determine the spatial and temporal climatic distribution of spring thunderstorms. An appropriate probability distribution function was chosen to determine the distributions of the data.  Due to the large volume of data and the uneven distribution of stations, cluster analysis and kriging methods were used to classify different regions into homogeneous groups for zoning and spatial analysis of spring thunderstorms, respectively. The statistical characteristics of spring thunderstorms were reviewed and fitted with a 3-parameter Weibull distribution. Regions considered for this study were classified in four separate clusters according to the simultaneity of thunderstorms in the spring. After zoning, it was found that the highest rates of thunderstorm took place in the northwest and west of country. The northeast of Iran has the second highest number of thunderstorm occurrence. The least number of thunderstorm event had happened in the central and southern half of the country.     According to the descriptive statistics parameters, maximum number of thunderstorms occurred in May.. Based on the results of the cluster analysis, there is a similar trend in the central and eastern regions, the rest of the country was clustered into five distinct homogeneous regions, including the northwestern, western, southern, northern, central northern and northeastern regions. Zoning results indicate that the highest number of the occurrence of this phenomenon in the country is concentrated in the northwestern and western regions. Higher frequency of occurrence of thunderstorms in the northwestern and western regions may be attributed to local topographic conditions like high mountains, orientation of the terrain, solar radiation on slopes and existence instability conditions, hillside convection, the presence of water resources and specific climatic conditions in these areas. In addition, as a result of a continuous surface obtained by the method of interpolation with the least amount of systematic error and also the use of correlation functions for recognizing the spatial structure of the data and estimating the model error when using the Kriging method, the weights are chosen in order to have a more optimized interpolation function. Also the cluster analysis may significantly reduce the volume of operation without affecting the results and will help in finding a real band due to more appropriate classification of different geographic areas with greater spatial homogeneity and minimal variance within the group. Based on the results of the spatial analysis, it is clear that Kriging and Ward cluster analysis methods are appropriate for thunderstorm zoning and classification of different regions according to occurrence of thunderstorm, respectively.

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Global temperatures have increased in the past 100 years by an average of 0.74°C (IPCC, 2013), with minimum temperatures increasing faster than maximum temperatures and winter temperatures increasing faster than summer temperatures (IPCC, 2013). Total annual rainfall tends to increase at the higher latitudes and near the equator, while rainfall in the sub-tropics is likely to decline and become more variable (Asseng et al., 2016). Considering probability of occurrence climate change and its hazardous impacts, it seems essential to clarify future climate. General Circulation Models is widely used to assess future climate and its probable changes. Although the outputs of these models are not appropriate for small-scale regions because of its coarse resolution. Thus, statistical or dynamical techniques are used to downscaling the outputs of these models using observed data in weather stations. Despite the fact that frequent researches has done in relation with climate and climate change, but it is unclear yet future climate, especially climate change, in Iran. The goal of this study was to present the results of climate change predictions which has been done so far in Iran, in order to help prospective studies in this field. This step can be important to consider new questions and challenges. In this study, we assessed future climate change in Iran using results of statistical downscaling studies of atmospheric-oceanic General Circulation Model’s outputs. To do this, studies on prediction of precipitation and temperature parameters in Iran by different emission scenarios, atmospheric-oceanic General Circulation Model’s outputs and statistical downscaling techniques were gathered. Then a comprehensive view about Iran's future climate and specifically the climate changes presented by descriptive-content based analysis and comparison of their results. Used downscaling techniques in these researches were included: LARS-WG, SDSM, ASD, Clim-Gen and used General Circulation Models were: HADCM3, BCM2, IPCM4, MIHR, CGCM3, CCSM4 and finally used emission scenarios were A1B, A1, A2, B1, B2, RCP4.5. Based on climatically geographical differences in Iran, the results discussed separately in six different regions across Iran. The results of various regions are different because of usage of different models and different climatological and geographical conditions. These models simulate temperature more accurate than precipitation, because of more variability and temporal discontinuity of the precipitation relative to temperature. Assessment of results in 30-year periods from 2011 to 2099 showed that in North West of Iran (Ardebil, Azarbayejan- Sharqi and Azarbayejan- Qarbi provinces), precipitation will be decreasing, decreasing- oscillating, decreasing- transitional and temperature will be increasing. Decreasing- transitional trend, in other words decrease precipitation in cold seasons and increase of it in warm seasons, lead to a decrease in the snow occurrence and an increase in the rainfall occurrence. Thus, it can affect the frequency of floods occurrence. In west and southwest region of Iran precipitation has been predicted to have different changes in various sections of it. It will be decreasing-oscillating in Kermanshah and Kordestan provinces and oscillating in Hamedan province. Precipitation will increase in Lorestan and finally it expected to decrease in Khoozestan, Chaharmahal-va-Bakhtiari, and Ilam. However Temperature will rise across this region. In south and south east region of Iran (Fars, Hormozgan, Kerman and sistan-va-Baloochestan provinces), precipitation will be decreasing, decreasing-oscillating, oscillating and increasing-oscillating. Also in this region, temperature expected to increase similar to other regions. In east and north‌ east of Iran (Khorasan Shomali, Khorasan Razavi and Khorasan Jonobi provinces), temperature predicted to be increasing-oscillating, that it is different with other regions. Changes in precipitation will be oscillating and decreasing-oscillating. In the northern coasts of Iran (Gilan, Mazandaran and Golestan provinces), precipitation changes will be decreasing and increasing-oscillating and temperature changes expected to be increasing and increasing-oscillating. Thus, it expected to increase heat wave, drought, and aridness condition as the results of these changes. Precipitation changes in south of Alborz region and center of Iran (Semnan, Tehran, Qazvin, Markazi, Esfahan and Yazd provinces), will be decreasing, oscillating, increasing-oscillating. Also temperature will be increasing in this region. Considering the decreasing trend of precipitation and the increasing trend of temperature in the most of Iran, it is probable to increase the occurrence of climatic and environmental hazards such as flood, drought and heat waves in the future. These events can have serious effects on water resources, agriculture and tourism, especially in regions such as Iran where have sensitive environment.

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Abastract
Introduction
Road accidents is the outcome of driver behavior, road condition, vehicle status, and environmental factors. Therefore, identification and assessment of effective parameters on road accidents can be considered as an appropriate way to reduce the accident events, driving violations and increase the road safety. Determining the effects of meteorological factors on the road accident events has gained more attention in recent years.
  The The main objective of this study was to investigate the relationship between the number of road accidents and the meteorological variables in the intercity road of Grmi-Ardabil in the Barzand route.
Methodology:
In this regard, the effects of climatic factors (including rainfall amount, the minimum absolute temperature, and the number of frost days) on the frequency of perilous events were analyzed. The data of accident events (in recent 4 years) were obtained from the trooper department of Ardabil Province along with the meteorological parameters of Germi station through a 11-year period. The statistical tests were performed using R programming software through statistical analysis.
Findings and Discussion:
The results showed that the majority of accidents were occurred in winter season which is in consistent with the frequency of frost days and also corresponded to the absolute minimum temperature. According to the results, the highest significant positive correlation at (R²= 0.43) was observed between the number of injured people and frost days. In addition, the relationship between the absolute minimum temperature and the number of were identified as significant negative correlation.
Conclusion:
As a concluding remark, the poor road conditions caused by climate element can be considered increasing the frequency of accident events. Accordingly, the proper strategies related to behavior change could be
considered in setting the rules and regulations to reduce the accidents and the number of injuries.

Keywords: Climatic hazards, Correlation analysis, Frost days, Minimum absolute temperature, Germi-Ardabil road