نشریه تحلیل فضایی مخاطرات محیطی
سال یکم شماره 4 (زمستان 1393)

Tectonic geomorphology is part of Earth Sciences, which deal with study of the interaction of tectonic and geomorphology. In other words it studies the effective tectonic processes in forming and changing the landforms. Geomorphic and morphometric indicators are suitable tools to the morphotectonic analysis for different areas. These indicators are used as the base tool to identify and recognition of tectonic deformation or estimates of the relative instability of tectonic activity in a particular region. Some of geomorphic indicators has been widely used, then the results of research projects are used to obtain comprehensive information about active tectonics. Full assessment of contemporary tectonics and tectonic activities, especially the young tectonic and its hazards need to Full understanding of geomorphologic processes speed and made for this purpose, geomorphological methods play an important role in this context.
This research uses a descriptive-analytical approach, using library studies and aims at determininge the activity of Neotectonic in 7 Watersheds of Tehran metropolis (from west to east: Kan, Vesk, Farahzad, Darakeh, Velenjak, Darband and Darabad). In the first step, using topographic and geological maps of under the studied area, faults, drainage networks and watersheds are identified, then to evaluation the indicators of Mountain Front sinuosity (Smf), the main river sinuosity (S), the drainage watershed asymmetry (Af), rivers density index (D), hypsometric integral (HI), the ratio of the watershed shape (BS), the ratio of valley floor width to valley height (Vf), river longitudinal gradient index (SL) and Index active Tectonic(IAT) have been determined. Survey of these indicators by topographic and geologic maps and Google Earth images of the under studied area using software of Google Earth, Arc GIS and Global Mapper are derived and calculated. In the following, parameters and how they are calculated are given:-Mountain Front sinuosity is the result from equation (1):Smf = Lmf / Ls (1)
In the equation (1), Smf is index of sinuosity Mountain Front. Lmf is the front along the foothills and mountains of the specified slope failure and Ls: straight line along the front of the mountain.
- The main river sinuosity index is as follows: S = C / V. In this formula, S is main river sinuosity. C: along of the river. V: valley along of the straight line.
- Rivers density index, drainage density is obtained from the formula:µ= Li is length in kilometers of drainage Watershed, A is area in square kilometers, μ is total drainage watershed in terms of kilometers per square kilometer.
- Hypsometric integral is an indicator which represents the distribution of surface heights variation from equation (2) is obtained:HI= H - Hmin / H max – H min (2)
In this equation Hi is hypsometric integral, Hmin and Hmax respectively are the minimum and maximum height and H is the height of watershed.
- The ratio of width to height of the valley floor is another geomorphologic parameters to investigate the tectonic forces in the region .This index is obtained from the equation (3):VF = (3) VF, represents the relationship of the valley floor width to valley height, VFW: the valley, Eld and Erd to the height of the left and right and Esc is valley floor elevation valley.
- The ratio of the area ratio of the area and the equation (4) is obtained:BS= Bl / BW (4)
-BS; the shape of the watershed; Bl; length dividers watershed of water to the bottom of the watershed outlet and BW: width of the flat portion of the watershed.
-The longitudinal gradient index (SL) for a range of drainage path is calculated and determined by the relationship: SL = (ΔH / Δ L) * L. In this regard, SL: the longitudinal gradient index, ΔH: height difference between two points measured, ΔL: during the interval and L: total length of the specified channel to assess where the index to the highest point of the canal.
The classification provided for indicators Sl, Smf, Vf, Bs, Af by Homduni et al (2008), this indicator is obtained based on the amount of 1, 2, 3 classified in three classes. Index of active tectonic (Iat) Geomorphic indicators by means of different classes Calculated based on the value of (S /n) is divided into four classes, That the division are characterized by class 1 with very high activity Neotectonic, Class 2 with high Neotectonic activity, Class 3 with medium Neotectonic activities and and Class 4 with low Neotectonic activity. In this classification of Class1 have the highest and Class 3 have the lowest Neotectonic activities (Table11).
On the basis of Iat indicator Neotectonic activities in the under studied area were assessment and results were is in table (13). Based on the data in Table (13) , watersheds of Kan and Darband hava a high Neotectonic activities and located in Class 2 and watersheds of Vesk, Frahzad, Darakeh, Velenjak and Darabad have a medium Neotectonics activities and and located in Class 2, and Neotectonic activities are a high relative tectonic activity in all watersheds. Geomorphic indicators are reflecting activities in the metropolitan Tehran watersheds can say that tectonically active watershed has not yet reached stability and tectonic activity are relatively high. Geomorphologic indicators drainage watershed asymmetry, the main river sinuosity, the valley floor width to height ratio of density of rivers and valleys, structural geology and tectonic activity in the7watersheds of Tehran metropolis better show it.
The results show that Tehran metropolis Watersheds have a high relative tectonic activity in all watersheds, because of the proximity to the major faults (such as Mosha- Fasham and North Tehran faults) and minor faults, tectonic activity exists. Finally it can be stated that, due to the presence of multiple faults and background seismicity and tectonic activity in Tehran metropolis and its watersheds, occurrence of earthquakes in the study area is not unexpected and this issue requires serious consideration and management.

Today urban livability reflects a powerful discourse in urban development and city design that is prevalent in urban planning literature suggests that there is an ideal relationship between the urban environment and the social life .On the one hand, the livability indicates the strong urban influence and attraction. On the other hand, the livability will further strengthen the urban connectivity and influence by attracting more investment, human and cultural resources. The livability of a city is closely related with a healthy and ecological city and sustainable urban development. This study aimed to measure the livability in the neighborhood of region(2) of Sanandaj city and research methodology is descriptive-analytical. A base map of the study area was prepared using Arc view Software. The region (2) is located in the central parts of the Sanandaj city.and the population of region is 239,965. The sample size was calculated using the formula Cochran. Therefore, 370 residents of neighborhood filled the questionnaire and expressed their viewpoint about the indicators of livability. A data collection method with respect to the merits of subject is Library and field method. The filled questionnaire by residents of different aspects of livability is measured. According to the Social features, facilities, geographic, economicfacilities and services available in the region , urban managers and experts have weighted the dimension and index of urban livability.The index of economic, social and environmental livability was calculated and the sum of these three dimensions is considered as total livability.To assess the livability of neighborhoods, data from filled questionnaires by people have been analyzed by the software GIS, SPSS and Excel. Using hot spots, three indicators and total livability of each neighborhood displayed.The results of the analysis of economic indicators showed that the areas in the western parts of the city are hotter and more color spots, But in the East and South East areas neighborhoods, like Shahrdari, Sepahdegaran have in colder and less color spots. This actually shows the cluster distribution of economic indicators. Also the results of the analysis of social indicator showed that spatial distributon is cluster neighborhoods like Khosow Abad, Masnav, Chahar Divari, Mobarak Abad are in the hotter spots and neighborhood Adab, Varmaghani, Hassan Abad are in colder spots.The resualts for environmental indicator reveals that spatial distribution is cluster. Mriginal neighborhoods are in colder spots and Nezam Mohandsi and Shardari town and Degaran allocated the lowest Z. In contrast neighborhood like Mobarak Abad and Khosrow Abad are in hotter spots. Analysis of hot spots for total livability implies that neighborhood in West area of city follow clusters of hotter spots and the South East neighborhood follow colder spots. This can result in injustice in space services and the lack of performance in order to improve the quality of the environment and quality of life in area, livability is defined as one of the aspects that could contribute to a high quality of living, because high quality of living will affect citizen's lifestyles, health condition and shows stability of the built environment. most researchers agree that livability refers to the environment from the perspective of the individual and also includes a subjective evaluation of the quality of the place so measurement of urban livability for all places promote the perception of urban managers and planners and with such knowledge, the path will be open for practical, creative and futuristic management of the urban environment. In relation to the livability of neighborhoods to each other, spatial and non-spatial analysis shows that areas with different ratings are compared to each other. With respect to results of measurements of livability: centrally located neighborhood is more livable than their peripheral counterparts which may calculate that location has significant importance in the pattern of livability. Therefore spatial distribution of dimension and index of livability is not the same extent.The results showed that between main dimensions of neighborhood livability is not different. But in terms of spatial distribution, three dimensions are not equally distributed and it is cluster. Ranking based on total index indicate neighborhood of Khosrow Abad with score (3.279) is ranked at first and Sharif Abad with score (2.228)is ranked at last.

The Iranian plateau formed by the active tectonics of the Alpine-Himalayan belt, is situated between the Eurasian and Arabian plates. The plateau is considered as one of the most seismically active regions in the world and is faced with different earthquakes each year. Active tectonic conditions, different faults and seismic sources and a large population in earthquake-prone areas makes it necessary to perform more considerations and scientific studies in order to analyze the seismic hazards and risks.
In this paper, different aspects and effects of the Iranian seismicity has been determined. In order to review the status of seismicity and distribution of earthquakes in Iran, we need first to consider the tectonic setting, structural environment and the active faults of the country. To date, there have been some different studies to divide the the seismotectonic setting of Iran into different seismic zones which are explained in this paper briefly. Moreover, the seismicity and most destructive past earthquakes in the Iranian plateau and distribution of earthquakes are shown.One of the most important tools in studying earthquakes is to perform continuous recording and monitoring of the seismic event and ground motions which is implemented using seismic and strong motion networks. The systematic networks have been set up within the country and are working and responsible for data collection and monitoring of seismic events permanently. These networks including the Iranian Seismological Center (IRSC), broadband seismic network of the International Institute of Earthquake Engineering and Seismology (IIEES) and strong motion network of the Road and Housing and Urban Development Research Center (BHRC) are also introduced in the current study.
Given the high seismicity rate in Iran and rapid development and growing of the populated cities and buildings on seismic hazard prone areas, attention to seismic hazard and risk assessments has been become as a particular issue that should be addressed carefully. Therefore, seismic hazard analysis and estimation for the constructions of human structures has become an enforcement for which several seismic regulations and codes have been defined. In this regard, deterministic and probabilistic seismic hazard methods have been developed as the two most important techniques. The deterministic method is a conservative approach that is mostly used to determine the highest level of strong ground motion (acceleration) for a special site (such as dams and power plants). On the other hand, the probabilistic method provides probabilities of different strong ground motion levels considering different uncertainties and the useful life of a structure.
In addition, considering the level of seismic hazard in a region and its population can lead to risk assessment, vulnerability and resiliency of the human societies. Thus, parallel to seismic hazard and risk analysis, it is so important to conduct crisis management, reduce efforts and a continuing assessment of the situation in the country. In the present study, problems and challenges facing the crisis management, as well as urban distressed areas are mentioned.
Regarding the existence of constant threat of natural disasters, especially high risk of earthquakes, there is a serious need to conduct more scientific researches in various fields, including detailed research on various aspects of seismology in Iran, retrofitting of constructions, crisis management and disaster risk reduction. To achieve this purpose, we need a scientific network in Iran. There sould be several experts and organizations as the members of this network who are able to understand and control the earthquake effects on the society. Necessity of such a scientific network is due to that it is impossible to take efforts in order to reduce the earthquake risks without a holistic perspective and earthquake data completion.
In this regard, we need significant infrastructures in terms of human resources and technical cooperation to motivate a set of organizations, universities and research institutes. The responsible organizations such as geological survey of Iran, National Cartographic Center of Iran, meteorological organization, Institute of Geophysics of the University of Tehran, International Institute of Earthquake Engineering and Seismology, Road and Housing and Urban Development Research Center, National Disaster Management Organization, Red Crescent Society of the Islamic Republic of Iran, as well as universities and NGOs must work together to make it possible to review and integrate the existence potentials and to share the information and data of the earthquakes in Iran and define various response scenarios faceing natural disasters, especially earthquakes.

In advance crisis management of natural disasters, particularly earthquakes in urban areas is one of the necessities of urban planning. However, nowadays with the help of technology we can determine the risk of crisis in the urban areas and settlements. Due to population growth and increasing urbanization, the occurrence of natural disasters such as earthquake can cause terrible disasters in the cities. The need to reduce the vulnerability of the cities is one of the main objectives of physical planning of urban areas and city designing. The city of Kashmar in one of Iran's earthquake-prone areas (due to its adjacency to the Lut fault) has witnessed the sever destruction from the September 25, 1903 earthquake (with a magnitude MS= 5/9) and Torbat Haidariye earthquake on 25 May 1923 (a magnitude MS= 5/8). It is very important to identifying vulnerable areas to earthquakes in advance. Accordingly the objective of this study is to identify the vulnerability of urban areas of Kashmar city to the earthquake by using VIKOR model of urban planning. The vulnerability of the city was computed on several parameters among which the population density is the most important one.
In order to carry out the research eleven population and other indices were used. These indices are as follows:1.Building Materials;
2. The quality of the building;
3.Old buildings;
4.Number of floors;
5.The materials of facades of building;
6.Compatibility of land uses;
7.Access to network passages;
8.Distance from the main fault;
9.The building density;
10.Numbers of population; and
11. Relief and rescue centers.
By using the VIKOR ranking model the vulnerability of the urban areas of the city was identified and classified. The correlation between the city vulnerability and each of these indices was calculated. The impact of the indices on the city vulnerability was calculated according to the AHP model.
The results of the study showed that the zone 3 had the highest and the zone 8 had the lowest physical vulnerability in the model. Based on the results of the Spearman correlation, the impact of the population on the vulnerability was about .5866 which is relatively noteworthy. This means that highest degree of vulnerability can occur in very populated areas of the city. All of the city was regionalized according to the degree of vulnerability to earthquake.
The lack of amenities and facilities such as health centers, fire stations, building materials and weak areas within the city will increase the losses and casualties. It is noteworthy that comprehensive city planning in the future must improve and the needed facilities should be provided. In addition providing services to the residents, especially in critical times after the earthquake should be provided.

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.

The best path to development is the primary focus on the potentials and threats of the environment and accordingly efficient use of the land. In this regard, it has a closely relation between agricultural and rural development and natural resources. The type of land use is a main factor in soil erosion and sediment production in the watersheds. In this research, it has been studied and evaluated the soil erosion in the Aleshtar plain catchment with aim of developing agricultural exploitation.
This study is based on PSIAC model. The PSIAC method has been designed based on the estimating of sediment potential with 9 important effective factors contains surface of the earth, soil type, weather conditions, runoff conditions, topography, land cover, Land use, current erosion condition, slope of river erosion and sediment transportation in the soil erosion. In the process of this research using geographical information system (GIS), the mentioned data analyzed, integrated, and finally layers of information were prepared. Followed by extraction of units, erosion zoning of the studied area has been implemented.
The total area of the studied area is 80305 hectares and is located in the northern parts of Lorestan province (southwest of Iran) and geomorphologic features are almost mountainous and 39.65% of their area are mountains and hills. The maximum altitude is 3600 meters; the minimum is 1500 meters. and the average height of 2116 meters. Its climate type (based on De Marten method) is Mediterranean climatic pattern exists and the average annual rainfall is 506 mm. The Aleshtar City is the only urban center in the area but there are 208 villages. The economy of the settlements is based on agriculture (farming, gardening and animal husbandry).
Based on the findings of this research, 37.92% of the total land area of the basin is eroded (classes I, II, III). The land consists mainly of low slope and plain basin and is suitable for plantation (I). In this zone, 98 rural settlements (47.11%) are located. Relatively deep soils and flat are the features of these lands so the rate of erosion is low (II). 84 rural settlements (40.38%) are classified in this class. Shallow soils, these lands need to have conservation measures and can be managed under the operation of arable, rangeland, forest and resorts (III). 1 rural settlement (0.48%) is located in this class of erosion. 62.09% of the total basin land is located in the classes IV and V. A total of 25 rural settlements (12%) are located in this class. These lands under certain conditions can be planted; because erosion in the land is relatively high and the limitations in comparison with class III is more. Therefore they need more protection operations for exploitation. Also in these lands that are located in the high topography of the basin; erosion is extreme (Class V), which makes arable exploitation impossible.
Generally the land use in Aleshtar basin is faced to erosion limitation, so the control of the soil erosion and soil conservation and water resources management are essential. However, the locations of the most rural settlements were based on low to moderate erosion zones which indicates that the ancient has had a traditional preparatory thinking.
As a general recommendation, it can be said that in any location, including rural and urban settlements, along with the development of agricultural activities, attention to the erosion and zoning is essential.

Mountain systems have an important role on meteorological variations. Different components of the mountain affect the atmospheric parameters and have essential role in atmosphereic circulation. Garmesh wind is one of the most well-known phenomena that are related to mountain systems. In this research, mechanism of garmesh wind are identified using database of garmesh wind in the last 29 years and using remote sensing technology from 2005 to 2010.
To survey the Synoptic and dynamic conditions of atmospheric patterns in the Garmesh wind’s events in the region, SCDATA of several synoptic stations in Gilan province, including Rasht, Bandar Anzali, Astara and Jirandeh are used which had continuous long-term data in 1982-2010period After Identification of days with Garmesh wind, daily images of Modis sensor of terra and aqua satellites in visible band and 7-2-1 band are monitored for checking the cloudiness on the both sides (southern and northern slops) of Alborz mountains and data of Jirande station in southern slop of Alborz mountains are used for detecting atmospheric phenomena like precipitation and snowfall. Also for studying the synoptic and dynamic pattern of this phenomena, reanalysis data from NCEP/NCAR were used.
In this research, Based on the presence or absence of the atmospheric phenomenon (like rainfall and snowfall), three categories were identified. In the first category, Garmesh winds were happened in clear sky conditions and without any atmospheric phenomena on both side of mountain’s slope. In the second category, only cloudiness was seen at the time of the Garmesh wind. In the third category, precipitations (in this research, snowfall) were seen in southern slope of Alborz Mountains.
Statistical analysis of Garmesh wind in central plains of Gilan
Totally, Occurrence of Garmesh wind was 479 days in Rasht, during 1982-2010. The frequency of occurrence of this phenomena was in January, February, November and December and rarely, in September and June. Clouds that observed in the time of Garmesh wind were: Altocumulus (type 4), Cirrus, CirroCumulus.
Patterns of Garmesh wind mechanisms on western half of Alborz Mountain:B1. Garmesh wind without any phenomena
This category includes11 cases of total 47 studied cases. 29 January 2008 is an example of clear sky condition in the time of Garmesh wind. In this pattern, in the surface zonal extension of Mediterranean dynamical low pressure’s contours from west of Caspian to Gilan plain and at the same time formation of cold high pressure cell on Zagros mountains caused strong pressure gradient on southern coastal zone of Caspian Sea, As it led to the the increase of wind velocity in Rasht airport synoptic station from 11 kilometer per hour in 00 UTC to 36 kilometer per hour in 12 UTC. Dominance of warm core on southern Caspian versus dominance of cold surface air on Iran Plateau indicates adiabatic warming in northern slope of Alborz Mountains.
B2. Garmesh wind with cloudiness
This category includes 34 cases of total 47 studied cases. Free of air mass’s patterns in the surface and conditions of atmospheric flows in low-troposphere that are similar to previous category, transition of height trough in mid-troposphere and high-troposphere can be name variant component verses previous category.
B3. Garmesh wind and precipitation (snowfall)
This category includes 2 cases of total 47 studied cases. At the same time, surface high pressure was on Iran Plateau and low pressure system was on Caspian Sea and also Gilan providence that caused the formation of Northerly stream and west-east stream to southern coastal zone of Caspian Sea and backward of Alborz Mountains like other patterns, snowfall occurred on southern slope of Alborz Mountains. Strong southern and south-western stream and strong positive vorticity on southern slope of Alborz Mountains by deep height trough in low-troposphere has an important role on intensification of vertical motions on lee ward of Alborz Mountains.
Garmesh wind is an atmospheric phenomenon that occurs as a result of interaction between atmospheric systems in synoptic scale and topography on back ward of mountain. In the other words, existence of Alborz Mountain’s as a great wall has an important role in the interaction between synoptic systems and formation of Garmesh wind.
Formation of Garmesh wind phenomena in Gilan province, is affected by extension of Siberian high pressure’s counters and sub-tropical high pressure on central of Iran Plateau and also existence of advection of pressure’s counter like sub-polar low pressure and or the Mediterranean Sea on north of Alborz mountains are required. Without any notification to origin of air masses, three categories has been observed based on existence or absence of Phenomena (in this research, sowfall).
In 700 and 500 hPa, Geopotential height patterns and relative vorticity field indicate that in the first category, wide parts of Iran is affected by high height and negative vortisity like low troposphere, during peak hours the wind. But in the second and third category (specially in third category ) existence of upper trough and easterly extension of trough caused to reduction of height and formation of strong positive vorticity in upper level and all over of air column in both south and north slopes of Alborz mountains.