Journal of Spatial Analysis

---

Climate is one of the important natural factors that affect all stages of life, particularly human exploitation. Selection of the type of clothing, housing, cultures, architecture, civil engineering, and settlements are influenced by climatic factors. It can be said that the climatic circumstances of the surface of the earth and atmospheric circulation patterns have an important role in shaping and organizing the environment (Alijani, 2009). In some cases, the normal weather conditions become abnormal and cause many damages, which are mostly catastrophes rooted in climatic changes, such as hail, frost, heat and cold waves, floods, storms and so on. Blizzard is one of the atmospheric phenomena, which happens as the result of snow combined with wind (15 meters per second), and low temperatures (below zero°C), and it causes severe losses.

Due to its special geographical location, Iran is placed in the transition region of the large-scale patterns of common tropospheric circulation, and is the intersectional place of the of extra-tropical and tropical circulation system. This feature along with its complex topography caused the land to have a considerable climatic diversity. The climatic diversity makes the various climatic phenomena to be observed with intensity, energy, and different frequencies, therefore, the climatic phenomena with high intensity always causes damage to natural resources and the human civilization. This undesirable phenomenon is called climatic risks. Since the West Azerbaijan Province is located in mountainous areas and high latitudes, the feature is triggered many climatic risks such as flood, hail, snow, snow storm, and so on. Therefore, snowstorm is one of such phenomena that have occurred every year or every few years due to the specific characteristics of the region and have caused damages in the fields of transportation, energy, livestock, closeness of schools and offices.

The purpose of this study is the statistical and synoptic analysis of snowstorm in west Azerbaijan province. Therefore, the data related to the present weather codes were collected during the period 1986 to 2009 from the National Meteorological Agency. The data related to the weather codes entered in Excel, and data related to the snowstorm were selected through Filter tool and isolation of codes related to the strong snowstorms (codes 37and39) and weak snowstorms (codes 36 and 38). Then the data related to the snowstorm was entered in SPSS, and the statistical analysis was performed. In the next step, three cases of the strong and common snowstorm (code 37 and 39) were selected for synoptic analysis. Then, the synoptic maps of the different layers of the atmosphere were selected as the samples for strong snowstorm for the days before the event of the phenomenon, the day of event, and the day after the event of the phenomenon by the using of the accuracy of 2.5 degrees from cdc.noaa.gov website. The study area has been selected in 10 to 80 degrees north latitude, and 15 to 90 degrees east longitude for identifying the patterns that affect West Azerbaijan Province. The data was received on wind speed and direction in digits from the National Center for Environmental Prediction. Then, the maps of the wind direction and speed were provided in Grads. Finally, the daily analysis and interpretation of pressure (500hPa at sea level), instability (700hPa level and the ground level), Earth's surface temperature, wind speed and direction maps for 700hPa level, and identification of patterns that have caused snowstorm in West Azerbaijan province were carried out. Statistical and synoptic analysis of snowstorm phenomenon in West Azerbaijan province during was performed in the period 1986 to 2009. To do this, using codes 36 to 39, which represent a variety of snowstorm (weak and strong), the frequency of snowstorm days on monthly and annual average, distribution of the snowstorm in the extracted stations, the frequency of strong snowstorms (codes 37and39), weak snowstorms (codes 36 and 38), all types of snowstorms (codes 36 to 39), and the frequency of storms in the station level were compared. Out of 322 snowstorms occurred during the period 1986 to 2009 in seven synoptic stations 108 have been determined as strong snowstorm and 214 as weak snowstorm. In order to analyze the synoptic snowstorm in West Azerbaijan province, in the first place, the strong snowstorms were identified, and then five of the strong and comprehensive storms were selected for the synoptic analysis. The snowstorms of choice are as follows: On 18 January 1986, on January 19, 2000, on February 7, 1992, on February 5, 1997, and on December 25, 1990.

For applying the study, pressure maps, Omega (700hp level at ground level), Earth's surface temperature, and wind speed and direction at 700hPa were analyzed, and patterns and conditions that are causing this phenomenon in the West Azerbaijan province were identified.

      In this study, to perform statistical and synoptic analysis of snowstorm in Western Azerbaijan province, the statistical data were examined during the period 1986 to 2009 from 7 stations, and the results of the statistical analysis showed that:

• Out of a total 322 snowstorm event days of 7 synoptic stations during the period 1986 to 2009, 108 and 214 days were strong and weak snowstorms, respectively.

• Review the annual and monthly snowstorm during the study period showed that the 1992, 1997, and 1989 with a total of 69, 29, and 25 days, as well as the 1999, 2006 and 2007 with 0, 1, and 1 day have the most and the fewest days of snowstorm, respectively. The statistical analysis showed that the snowstorm phenomena happened in January, February, March, April, November, and December. January had the most and April had the fewest snowstorms with 119 and 3 days, respectively. February with 39 days, and April and November, with the number 0 and 1 had the most and the fewest days of strong and constant snowstorms.

• Distribution of the snowstorms in the stations indicated that out of the studied seven synoptic stations, which had a great impact on the synoptic situation of the region, topography, and height, Sardasht-Maku station had the most, and stations of Khoy, Mahabad, and Orumiyeh by having no snowstorms had the fewest days of snowstorm.

• The results of the maps of the different levels of the atmosphere and Earth’s surface in the days before the storm, event day and the day after the snowstorm were selected for the snowstorm pattern, which indicated that the snowstorm in the winter due to low compliance pressure formed in the earth's surface with synoptic patterns of middle levels of the atmosphere have provided the conditions for the event, in a way that among the sample cases of the strong snowstorms occurred in the West Azerbaijan Province two circulation patterns were involved in the formation of natural hazards: The Caspian Sea low pressure pattern- Eastern Europe high pressure pattern and the north of the Black Sea low pressure pattern.

---

Agricultural crops have damaged a lot due to the aftermath of late spring frost, and because low temperatures have damaging effects on agricultural production, it is essential to anticipate and prevent potential damages. Often, atmospheric temperature variations are very urgent due to the high temperature of the systems and the plants cannot adapt themselves with severe oscillations and, have been damaged. The aim of this study was to analyze the climate of the spring frost in Kermanshah, identifying the sea level equations and the late spring freezing frost of the period from 1990 to 2015. This survey has been done to determine the period of the freezing phenomenon, determine the minimum daily temperature of 7 stations placed in Kermanshah,  Hamedan, and Ilam. After analyzing the data of spring frost freezing of Kermanshah province using the main component analysis technique and hierarchical clustering method, the most common 10 patterns of late spring coldness of the area were studied and determined. In 10 resulting cluster, 8 clusters were related to the high-pressure pattern of Siberia. From the total 91 days of spring frost freezing in Kermanshah province (79% (72 days)) is due to the high rainfall of Siberia, 12% (11 days)  is due to the Mediterranean climate and 9% (8 days) is due to the Van lake climate. These pressure patterns were named according to the location of their deposition, which caused the loss of the environment and the freezing frost of the spring.

---

The statistical and spatial analysis of extreme rainfall is considered as one of the components of the management tool to prevent or control the risks caused by this phenomenon. The purpose of this research is to statistically investigate and spatially analyze the extreme precipitations in the Kashan Plain.The extreme rainfall of Kashan synoptic station were statistically analyzed in the period of 1971-2022 AD and the water year of 1350-1351 to 1401-1400 for a total of 18618 days.Then six cases of widespread extreme rainfall were selected and analyzed with the rainfall data of 13 synoptic stations and 11 rain gauge stations using geostatistics and spatial analysis methods.The extreme rainfall zonation maps of Kashan plain were prepared using by variogram models and kriging method.The results showed that the frequency of heavy and super heavy rains in winter and very heavy rains in spring is more than other seasons.The very high correlation of annual rainfall with the total and frequency of extreme rainfall shows that the volume of annual rainfall is more affected by the concentration of rainfall in short periods of a few days than by the distribution of rainfall throughout the year.Therefore, it was found that extreme precipitation plays an important role in the total precipitation and surface runoff, and as a result, the water balance of the region.The zoning maps showed that the rainfall of April 8, 2020, which is concentrated on the western belt and the heights of the basin, causes the erosion of the heights and causes floods in the foothills and low-lying areas of the plain. Also, rains such as the rains of March 8, 2019, which are most concentrated in the central areas, have a high potential to cause flooding.