نشریه جغرافیا و مخاطرات محیطی
پیاپی 21 (بهار 1396)

Temperature is important in the consumption of water and energy through which influences the activities of humans, especially in urban areas. The high variations of temperature in both diurnal and annual scales increases the consumption of energy in winter and summer seasons to moderate the climate to live with. The higher the temperature range the higher the energy consumption. In hot season the higher consumption of water makes the critical impact of temperature manifolds. These circumstances become crisis as we take into account the warming of the temperature and decreasing the water and energy sources of the country, especially in dry regions such as Qum region where the water is already scarce.
The climate of Qum is getting warmer with more heat waves in summer increasing the demand for more electricity and water consumption. Based on the present conditions and increasing trend of global warming the managers and people should become aware of the higher water and energy demands in the future.
This study aims to identify the effect of temperature on consuming water and electricity and gas to manage the consumption of energy and environmental pollution by using less and healthier energy. It is hopeful that the findings from the study can help to manage the energy and purge the environment ofQom. This study tries to uncover the energy and water crisis of the city to make the managers to take actions before the crisis happens.
Material and In order to study the relation between temperature trend and utility consumptions in the city of Qum, the daily min and max temperatures of Qum weather station during 2007-2013 period were obtained from the Meteorological Organization of Iran. The daily utility consumption data for water, electricity and gas have been obtained from the related organizations for the same period.
To calculate the relation between temperature and energy consumption the daily temperature index was defined:〖TI〗_t=T_ti w_i
〖 TI〗_t = daily temperature index
T_(ti )= daily min or max temperature
w_i = the consumer index of year i and was calculated from: w_i= P_i/P
P_i = totalconsumers of year i
P = total consumers of the base year.
The monthly variations of energy consumption was calculated from: E_(ij )=ij /¯E j
ij = consumption of month i of year j
j=consumption of year j
The relation between temperature and energy components of gas, water and electricity is high and significant. This value is .80 for gas, .79 for water and .71 for electricity. Natural gas is very sensitive for min temperature while the other two are most related to max temperature. The analysis of results showed that the relation increased after a threshold. This threshold was 2000000 cubic meters per day for natural gas, 250000 cubic meters per day for water and 8000 mega wat per day for electricity. This means that all of these components are not sensitive to temperature increase because people use them for their normal life. But only when the temperature increases the extra amounts should be used to keep the living conditions tolerable. These thresholds could be used as an indicator of global warming impact on energy consumption. Which changes the normal life trend and takes it toward the hazardous fates at critical steps.
The thresholds show on the other hand the impact of extreme temperature values such as very low or very high temperatures. For example in winter very low temperatures are very important in increasing the consumption of natural gas to make homes warm enough to live in. Iranians do not use electricity for warming house. This is why that the consumption of electricity is not very critical in winter. But cooling the houses is dependent only on electricity in the warm period of year. Water consumption has also been highlighted in the warm season due to its use in air conditioners and green space maintenance. During the cold season water is used only for living basic needs.
There is a direct relation between temperature increase and energy consumptionespecially in the extreme values of temperature. This means that normal temperature increase or in other words the normal variations of temperature do not change the energy consumption dramatically. Only critical warming or cooling of the weather affects the energy and the users and managers should be aware of this problem. Water and electricity are sensitive for higher temperatures of warm season while natural gas is sensitive for very cold temperatures in winter season.

Natural and anthropogenic factors in recent decades caused water crisis and the drop in groundwater levels in most regions of the country, including Khorasan Razavi province.The Standard Precipitation Index (SPI) has the ability to assess meteorological drought and its impact on groundwater drought can be evaluated through the appropriate indices, e.g. Groundwater Resource Index (GRI) and Piezometric State Index (PSI). Their capability has been proven in many studies around the world (Memarian, Balasundram, Talib, Sood, Abbaspour, 2012; Verdi Pourazad, Azarakhshi, Mosaedi, Farzadmehr, 2014; Rezvanian, Assadi, Goudarzei, 2013; Yasamani, Mohammadzadeh, Mosaedi, 2012; Imani, Talebi Esfandarani, 2011; Shakiba , Mirbagheri, Kheiri, 2010; Shahid &Hazarika, 2009, 1989-2006; Mendicino &Senatore, 2008; Khan ).The main objective of this study is to evaluate the effects of drought on the changes of groundwater resources by using statistical time series analysis of meteorological drought and groundwater drought indices, temporally and spatially.
In this study for evaluating the effects of meteorological drought on groundwater table, the indices SPI and PSI during a 30-year period (1984-2014) were calculated and analyzed using the Mann-Kendall time series analysis and Pettit test.IDW (Inverse Distance Weighted) interpolation approach and Hot Spot Analysis were employed in spatial analysis of groundwater drought and its relation to meteorological drought was evaluated through the Pierson’s correlation coefficient.
Interpolated maps of SPI index showed that during the period 1999-2000, 2000-2001, 2005-2006, 2007-2008, 2010-2011 and 2013-2014 watershed area mainlyisclassified into dry and very dry classes. However, the results of time series analysis of SPI in all stations except Androkh station in the period 1984-2014 shows that the gradual changes of SPI is not significant at the level of 0.05.As a result, it can be stated that the Chenaran-Mashhad watershed has not experienced a gradual change in rainfall and meteorological drought in most of stations in the last threedecades. The gradual changes of PSI time series at all observation wells were significant and decreasing except GhasemAbad, Kalat Nader, Meskaran, Noumhan and Hashem Abad observation wells.PSI index had a decreasing trend in all observation wells except in Television Boulevard.Abrupt changes of PSI in most of observation wells were significant and reducing. This time, mostlywas correspondedto the years 1997-1998 and 1998-1999.Zoning maps also show that the PSI index on the plain from 1984-1985 to 1999-2000 was situated in normal conditions, whereas from1999-2000 up to now was classified in dangerous situations and historical minimum categories. During the years 2011-2012, 2012-2013 and 2013-2014 historical minimum condition of PSI is clearly visible.Correlation analysis between the two indices SPI and PSI showed that in most cases and years there are poor relationships between groundwater drought and meteorological drought. By analyzing the moderate to high correlations between the SPI, and PSI indices, it can be established that in most cases the relationship is in the reverse form. According to the analysis of annual water flow records of the main recharging rivers, it can be revealed that the gradual change time series is not significant at the level of 0.05. Again, it confirms that there is no strong relationship between hydrological drought and groundwater drought in the study region.
The groundwater level of Mashhad plain from 1985 to 2014 has been experienced more than 25 meters of drop that mostly occurred between1999 to2003. During this period, the number of drilled wells is 1054. The measurement results of the groundwater level during ten years (1996-1997 to 2006-2007) show that the drop in groundwater levels of the Mashhad-Chenaran’s aquifer is in accordance with the exploitation magnitude by wells and aquifer recharge. In fact, uncontrolled exploitation of groundwater resources can be considered as a major factor of drop in groundwater level, which caused subsidence and leading salty water into fresh water in Mashhad plain.

Currently, more than half of the world's population live in urban areas and among them, many people live in areas with potential hazards and disasters that threaten them. Because the location of settlement and other facilities created by mankind is completely influenced by environmental and tectonic factors. The establishment of human settlements on land that is at risk of earthquakes makes inevitable the necessity of paying attention to policies, plans and programs for harm reduction and disaster management. Since the earthquake is sudden, it can reflect a vast area of the region and even impacts national issues. The dimensions of the accident are so extensive that they require international attention and support .In such a situation, considering vulnerability reduction and crisis management are integral parts of urban planning. Therefore, the resiliency id introduced as the concept of facing the problems, surprises and changes. In fact, the purpose of this approach is to reduce the vulnerability of urban areas and to strengthen the ability of citizens to deal with the risks of threats such as natural disasters. Because Iran is a seismic zone in the world, the incumbency to deal with this natural phenomenon is strongly felt. Attention to Ardebil city with standing in several faults around city and earthquake background and Ardebil potential as center of the province and the high population, the concentration of most administrative and economic centers of the province, the existence of worn, tidy textiles and etc. are at the expose of the possible occurrence of earthquake. In this regard, research is in connection with the stage before the crisis and it focused on disaster risk reduction. Overall the aim of this study was assessment of the situation of resiliency in Ardabil against earthquake and is the rating of four regions in terms of resiliency and vulnerability.
Material and The research case study is Ardebil city and four regions that according to the latest report in 2014 had a population of 496,973 people. It is a plain formed by Quaternary sediments. The area studied by the chain by faults Neour, Astara and Heer surrounded. The existence of these faults, their history of seismicity and the placement of Ardabil on loose alluvial formations, make this city prone to earthquake occurrence. However, in addition to the normal problems of the city of Ardabil, the human problems such as population density, building materials, etc. are not homogeneous. The status of natural and human problems of the city could be evidence of the claim that Ardabil against earthquakes can be vulnerable.
This study from the viewpoint of nature has an analytical –descriptive and from the viewpoint of goal is applied research. Also, the data and information required for this research are collected in two ways: library (documentary) and survey (field). In the survey method, data collection was done using questionnaires designed according to the research questions. Accordingly, the fourteen metrics of urban alleviation have been evaluated from the local elite point of view. The population of the research was the crisis management staff of four regions in the municipality of the city of Ardabil. In this respect, due to the uncertainty about the number of experts, the researchers performed purposive sampling from 50 individuals. Subsequently, the obtained data were first assessed through SPSS Software. The reliability of the research instrument was evaluated by Cronbach’s Alpha test which was determined to be 92.1. This coefficient value is deemed to be acceptable. Afterwards using T Test the resiliency of Ardabil was measured and then entered the data in Excel format and by using Multi-criteria decision-making models of Vicker, Electric, Tapsis, and Copeland's integration model, four regions of Ardabil city in terms of resiliency against earthquake were ranked. It is mentioned that the criteria for determining the weight of AHP in the Expert Choice software.
The findings show that the assessment criteria for the resiliency of Ardabil are lower than average. It can be said between theory mean (square with 4) by means of the obtained (experimental average of 3.33) there is a significant difference. This means that the city of Ardabil is vulnerable to the risk of earthquakes. This confirmed a significant level of 95% by T test. The results further showed that AHP method used to fourteen criteria, criterion of X13 (away from hazardous environments) to 0.142, the most valuable measure of resiliency in Ardabil in the discussion of earthquake risk was identified. Research findings suggest that the output of the Topsis, Vicon, and Electric models are different, so that the first level of resilience is in two models of Wikipedia and Electrics related to the metropolitan region, but in the topsis model, the first rank is related to the 4 regions, which has the last rank in the two models mentioned. Findings, on Copeland integration model framework show also that the order of 2, 1, 3 and 4 regions, in grades one to four resiliency of the municipality of the city of Ardabil are located. Region 2 is high resiliency because it has new and scheduled context and in front of the regions with the old and rural core communities has high vulnerability such as the regions 3 and 4. According to the rating of Ardabil city of resiliency, it can be said that the newly built regions such as new housing settlements, have higher rank. As can be said, 2 region developments in Ardebil germinate from 1991 and this urban region made planning region on Ardebil city, so that this region is a resiliency region. This region of Ardabil has building materials of metal and concrete skeleton (80%) and low population density (less than 100 individuals per hectare), most citizens live in apartments (80%), and there is acceptable access to rescue centers (a fire station with an acceptable number of fire valves, 3 hospitals and one Red Crescent center). In other regions (region 1, 3 and 4), it can be said that more than 80% of the materials of these regions are of bricks and iron, and about 20% are related to new buildings. Population density in the region is one under 150 people, and in 3 and 4 region, over 200 people with a one-story building and a lower region (fine-grained region less than 75 square meters). In terms of access to rescue centers, access in the 1 region is better than in 3 and 4 regions and worse than 2 region. The one-stop-shop is a firefighting center with a number of firefighters and 3 hospitals, and is relatively accessible to other Red Crescent centers. And the 3 and 4 regions each have a hospital and a fire station with a limited number of fire extinguishers. With regards to regions 3 and 4 of Ardabil, it may be argued that these regions have a high number of worn-out textures and most of the new constructions at these regions are done without any specific principles and/or planning. Also, most of the adjoining villages to the city are located in these two regions, which makes them more vulnerable.
The results regarding the Ardabil city resiliency (four regional municipalities of Ardabil city) is in the overall situation against earthquake, it is vulnerable. So that the sample t - test - related to municipal urban areas Ardabil experts, resiliency mean rate of Ardabil city is equal to the 3.33 that the value for the region number two is more than the average for the rest of the region and lower than average. In ranking of regions regarding the resiliency with fourteen criterions was weighted, with using integrated Copeland model, the region at the top two and four ranked last. The region of two is new areas with principles and program and the region’s four is areas with the old context of Ardabil city. In fact the findings shows that those new areas where is built new has suitable resiliency and the regions with very old context of city and villages have attached to the city and urban area hasn’t acceptable resiliency against the earthquake, to the phrase its can be damaged. Also in the priority resiliency measures against the city’s earthquake and weighting determined that physical aspect with access criteria to vital facilities, risk environments, improve the quality of construction and building materials and construction and human right density more important than other criteria and dimensions However, not from other criteria and dimensions was unaware. Due to the fact earthquake is the most important and promising Ardabil city risks, the role of Local resident’s involvement is very visible in rescue of those affected by the Ardabil possible quake. Hence, the adoption of community - based disaster management strategies, empowerment of civilians and the use of power popular participation to cope with natural disasters, such as the earthquakes and increasing regarding urban is very important. Adding that to prevent accidents has to change the culture of construction and 2008 standards improve that casualties and financial damage reduced to a minimum. Raising the quality of buildings, reducing congestion, improving access, and avoiding hazardous regions will increase the city's security. Items listed for regions number 3 and 4 were deemed high vulnerability is very vital and important to them resiliency.

In developing countries, the ever increasing human population and the associated anthropogenic activities have accelerated the phenomenon of urbanization in the past decade. With the rising population and the associated unsustainable practices, there has been an enormous increase in the quantum as well as the diversity of the solid waste being generated. The problem of solid waste has assumed significant dimension especially in the urban centers. Domestic, industrial and other wastes, whether these are of low or medium level, have become a perennial problem as they continue to cause environmental pollution and degradation.So,rapid urbanization and population increase have called for an improved waste management services.
In this research, authors tried to use Fuzzy Logic method to obtain Fuzzy maps and used FANP method to weight criteria analytic network process. The ultimate goal of this research is to select a suitable site for landfill based on the FANP methodin Ali Abad Katool city.
Study Area: Aliabad Katoolcity with an area of 1160 square kilometers is one of Golestan province cities. Which it is limited to Gonbadkavoos and Aghghola cities from the north and Gorgan city from the west and Ramiyan city from the east and the Alborz mountains and Semnan city from the south. It is located in latitude of 36 degrees and 36 minutes until 37 degrees and 5 minutes of north and longitude of 54 degrees and 41 minutes and 9 minutes of east,and based on housing census of 2011, has a total population of 132.757.
Material and 3-1- Multi Criteria Evaluation method(MCE)
In This method, in order to expose to a specific goal, it is required to evaluate several criteria (Voogd, 1983; Carver,1991; Eastman, 2012). The purpose of the multi-criteria evaluation is to select the best alternative (the best site or pixels) on the basis of their ranking by evaluating multi main Criteria.
There are several methods for the analysis of multi criteria evaluation. The most important of those include a weighted linear combination method, Boolean methods, value approaches functiondesirability, AHP, ideal point method and agreement method. Multi criteria evaluation often performed by one of these two Boolean overlay and weighted linear combination. The fist process involves the overlap Boolean whereby all criteria reduced to the appropriate logic modes and then combined by one or more logical operators such as subscription (AND) and sum (OR).Second process is the weighted linear combination (WLC) in which continuous metrics (factors) is standardized to the normal numerical range and then combined with a weighted average. The result is a continuous raster map which covers one or more Boolean constraints to match with the qualitative metrics and eventually lead to the final decision.
3-2- Weighted Linear Combination (WLC)
Weighted linear combination (WLC) method is themost common technique in the analysis of multi-criteria evaluation.This technique also called scoring method. This method is based on the average weight. Analyzer or decision maker, weighting the criteria based on the relative importance of each criterion. Then, by multiplying the relative weight in the attribute value, final value is obtained for eachan alternative after specifying the final value of each alternative, the alternative that has the greatest value would be the most appropriate alternative for the intended purpose. In this decision rule, the value of each alternative is calculated by the following formula (Shahabi & Niyazi, 2009).
3-3- Map Standardization in Fuzzy Logic
In fuzzy logic, according the value which follows the intended criterion, each region obtains the value membership that expresses the desirability of the area. This means that each area with a larger value membership has a higher desirability. Fuzzy logic isnot certainty like Boolean logic and each layer is rated on a scale from 0 to 1. Another influential factor in fuzzy map standardization is determining the threshold which is called control points. But, one thing that should be considered in choosing function is the type of intended criterion that is increasing or decreasing and shows the control points and type of fuzzy function.
- Pairwise Comparisons of Criteria and Sub-Criteria Internal Relationships
Pairwise comparisons of criteria and sub-criteria which they conducted with expert’s opinions are shown in this article.
4-1- Steps of Obtaining Criteria and Sub-Criteria Weightswith Fuzzy Analytic Network Process
Based on various sources and experts’ opinions and FANP techniques, pairwise comparisons were performed between criteria and sub-criteria (Because of the high number of pairwise comparisons tables they arenot mentioned). And then, according to pairwise comparisons, weightsof each criterion and sub criterion are obtained in 5 steps which are shown in.
4-2- Calculating Required Land for Aliabad City’s Landfill
To calculate area of the required land for landfill over the next 20 years,landfill trench method with a depth of 4m is done.Also distance between the trenches is considered equal to its width. With these assumptions, Useful areas, makes up 50% of the range set.
4-3- Obtaining Data Layer Maps
In this study, map production was conducted based on fuzzy logic. Each effective data layer on landfill site selection standardized in IDRISI software according to table 3 charts. As well as their fuzzy maps produced in this software. These fuzzy data layer maps are shown in. In conjunction with fuzzy logic analysis included both “fuzzy membership functions, which assigned ratings for attribute values in a given thematic layer between 0 and 1, and “fuzzy overlay tool,” which merged multiple fuzzy membership results into the composite index map.
4-4- Overlaying Data Layers
Produced maps have been overlaid by applying 5 operators 1-Gamma,2- Product,3- AND,4- OR, 5- SUM in GIS and IDRISI software to perform site selection and achieve suitable areas for landfill. And, urban residential areas were eliminated from the final layer maps. All maps are shown in the article.
Map production with Fuzzy Sum and Fuzzy OR operators is not a suitable method for landfill site selection due to the ignoring unfavorable factors. Unlike Fuzzy OR and Fuzzy Sum, Fuzzy Product operator considers conservative approach and just shows the best places for this site selection. Also, Fuzzy Gamma operator with the numbers of 0.3 and 0.5, Fuzzy Gamma and Fuzzy AND with the number of 0.9 respectively have a less conservative approach than Fuzzy Product. But in general, these operators with Fuzzy Product are suitable for landfill site selection. In the meantime, based on Natural Breaks (Jenks) method from relevant operators maps are listed with four categories, suitable, average, weak and very weak (the classification of these operators is given in Figure 5).Then suitable category became classified. Methods which their Spots area were less than required area of landfill for estimated population of next 20 years of AliabadKatoolcity were excluded. Finally (AND), (Gamma) methods with the number of 0.9, determined a suitable landfill site for a period of 20 years as seen in it. Details and the priority of suitable areas for landfill site selection are given in this article.

Lightning is a sudden electrostatic discharge during an electrical storm between electrically charged regions of a cloud (called intra-cloud lightning), between two clouds (CC lightning), or between a cloud and the ground (CG lightning).This phenomenon is one of the most important featureswhich are associated with extreme storms and seize the life of about 2,000 people in the world each year.The occurrence of lightning is related to the cloud microphysics in the mixed-phase layer becauselightning is frequent in convective clouds that contain many large hydrometeors in the mixed-phase layer.Also, air on the windward side of a mountain is forced to rise; anditoften leads tothecloudand lightning.In fact, lightning activities are highly variable on many spatial and temporal scales, and to some extent depend on the local convective regime.Lightning activities are not registered in the synoptic stations, but the thunder day statistics determined by human observers and compiled by the World Meteorological Organization (WMO) are one of the best sources of proxy information concerning lightning activity worldwide.Lightning day might include more than one hundred events; therefore, it cannot be a good representative for the lightning activitywhilethese stationsdo notshow offa good distribution.Accordingly, using remote sensing technology can be accurately measured lightning activity. Several space borne instruments have measured the global distribution of lightning one of which is Lightning Image Sensor (LIS).In this paper, diurnal, spatial, and temporaldistribution of the lightning phenomenon in Iran werestudied using LIS data.
Study Area: Iran, with an area of 1,648,195 km2 is located in the southern part of the temperate zone of the northern hemisphere.It is situated between 25° and 47°northern latitudes, and 44° to 63° eastern longitudes.This area is generallymountainous and semi-arid.The lowest area is 28 m lower than sea level located on northern Iranand its highest peak is Damavand with an altitude of 5,671 m/ASL.Existence of this diversity in roughness of the ground causes different climatic characteristics in various parts of the country.
Material and Two satellite-based lightning sensors have been successfully used by NASA since April1995. The sensors can detect the total lightning activities (cloud-to-ground flash and intra-cloud flash) on a global scale. One of these sensors is Lightning Image Sensor (LIS) which was launched on November 28, 1997 aboard the Tropical Rainfall Measuring Mission (TRMM). The LIS sensor detects lightning with storm-scale resolution of 3∼6km over a region of 600km×600kmof the earth’s surface. The LIS circles the earth with a velocity of 7km·s−1, and observes a point on theearth or a cloud for about 90s. This short sampling time during the satellite overpass limits the data usage for forecast and requires several years to compute high resolution climatology. Nowadays, LIS has collected lightning measurements for over 16 years making possible the compilation of total lightning climatology maps in high resolution such as 0.250 and 0.100 of horizontal resolution. In this paper, diurnal, spatial and temporal distribution of the lightning phenomenon in Iran werestudied using LIS data. Some geoprocessing functions in ArcGIS were applied tocalculate statistical values and to identify the locations of statistically significant lightning clusters. For generalizing geographic locations of lightning occurrence to an entire area a Kernel Density Interpolation estimator was introduced. Basically, a Kernel density tool calculates the density of point features such as lightning occurrence locations in a radius searcharound all similar features. Conceptually, a smooth, curved surface is fitted over each lightning flash pointincidentin Kernel density procedure regarding all observations. The surface value is highest at the location of the occurrence point and diminishes with increasing distance from the point, reaching zero at the search radius distance from the point. In practice, the density rate at each output raster cell is calculated by adding the values of all the Kernel surfaces where they overlay the raster cell centre, based on a quadratic Kernel function.
The result showed that diurnal cycle of lightning display a local maximum in flash rate in early afternoon (between 12 and 15 local time) and local minimum in flash rate in early morning to late morning (between 01 and 11 local time). Monthly variation of lightning indicated that maximum frequency of lightning occurs in April whereas the minimum happensin January and September. Annual distribution of lightning data indicated that the maximum frequency of lightning coincides with mountain areas. A majority of the lightning activities over the mountain region occurs primarily in southern slopes ofthe mountains. More specifically, this maximum occurs over the south and southeast facing slopes of the mountainous areaslikeZagros, Alborz, Binalud, Barez, etc. Western and south-western slopes of the Zagros Mountains have the highest rate of annual lightning in Iran.Central regions of Iran have the lowest frequency of lightningwhich are generally flat and arid.
The result of Kernel density function showed that distribution of lightning in January, November and December are alike and maximum density of lightning occurs in southwest of Iran (between Khozestan and Lorestan provinces). The maximum density of lightning in February, March and October are also in southwest of Iran but the lightning occurred in a wider area. The peakfrequency oflightningactivityoccurs inApril and Mayanditsspreadismuch more thanother months. In these months, west, southwest and northeast of Iran have maximum frequencies of lightning. In June, July, August and September, the distribution of lightning activities are different from other months and the maximum density of lightning are in southern Kerman, Sistan and Baluchestan and some areas of Hormozgan province.
Although lightning activity occurs in all regions, it appears that some areas havemore favorable conditions for the occurrence of this phenomenon. This study investigated diurnal, spatial and temporal distribution of lightning activity with 16 years (1998–2013) of LIS.The results provide valuable information on the distribution of lightning activity in Iran, sinceno study had been carried outbefore the distribution of this phenomenon in Iran.Results of diurnal cycle indicated that there was a marked daily distribution of lightning frequency during the afternoons peaking between 3PM and 5PM hours. These results nearly match the pervious findings; in such studies it was shown that all maximums in lightning were observed during the afternoons between 3pm and 7pm (EST). The increase in storms during this period is primarily due to the proliferation in energy provided by the sun during the warmer spring and summer months. The monthly distribution of lightning showed a distinct tendency indeed for all lightning to occur during March to May.The increase instorms during this period is primarily due to the increase in energy provided by the sun during the warmer spring. The result of lightning distribution analysis indicated that a majority of the lightning activity over the mountain region occurs primarily over the southern slopes ofthe mountains. Western and south-western slopes of the Zagros Mountains have the highest rate of annual lightning in Iran. Maximum frequency of lightning in January, February, March, October, November and December are also in this region but in warm season (June, July, August and September), south and southeast of Iran have maximum frequency of lightning activity.

Without any doubt, the Gilan plain in the northern regions of Iran plateau has the special conditions faced with heavy snowfall hazards in terms of damage amount. In the recent decade, the increase in frequency of heavy snowfall events in contrast with earlier decades, has caused a huge attention to this atmospheric hazard in Gilan province and also Iran. In most studies that were done on heavy snowfall events, the target was analyzing the synoptic-dynamic structure of case study and long term events. Overall, the main question about heavy snowfall in Gilan plain was the cause of this event in the central plain and another was the movement of the maximum snow depth area in this region from east to center and west. So, what is the structure for super heavy snowfalls in Gilan central plain in recent decade? What were the causes for the formation of two different spatial patterns of these three snowfalls?
The snow depth of the west, central and east regions of Gilanplain in the super heavy snowfall events (Gilan Meteorological Office).
Total snow fall (cm) Western plain Central plain Eastern plain
Station Astara Talesh Bandar Anzali Agricultural Lahijan Roodsar
7th -12th Feb 2005 10 No data 3 170 120 No data
7th -14th Feb 2008 36 59 204 136 91 66
30th Jan-4th Feb
2014 34 3 95 40 45 75
Material and 1- GFS-FNL data with horizontal resolution of 0.5 degrees as an input to the WRF 3.5.1 version.
2- Hourly data of meteorological parameters in the 12 synoptic stations of Gilan province for statistical analysis of used atmosphere characteristics
3- Visible band images and 1-2-7 MODIS sensor for Terra and Aqua satellites at the time of the snow falling.
4- Kiashahr (Gilan) radar outputs at the time of the snowfall
In this investigation, the role of effective regional factors and geographical components on formation of the maximum snow depth patterns in three systems with super heavy snowfall in Gilan province of Iran is investigated using numerical model of WRF with horizontal resolution of 7 Km. The overall results are as follows: In large and mesoscales, the source of these atmospheric systems are the cold anticyclones of North Europe and the semi-permanent anticyclone of Siberia that extend to lower latitudes with strong depth and its cold flow affects the northern part of Iran and also the south coast of the Caspian Sea.
The precipitation output of WRF numerical model for 7 Km horizontal resolution, perfectly enhances the spatial pattern of snow depth in these three recent systems that includes Gilan central plain and near the south of Anzali wetland. The important point in 10-meter wind output in the region is that in all three systems with the southerly movement of cold high pressure center to lower latitudes, cooling over the Caucasus and the high mountains of this area is intensified. These situations are seen appropriately in the 2-meter temperature pattern. Formation of cold flow from mountain to plain f caused by the existence of cold cores over the big and small Caucasus Mountains, led to form secondary high pressure in local scale over the Kura plain.
Settlement of secondary high pressure over western coast of the Caspian Sea (Kura plain) and the weakening of pressure counter over the southern coast of the Caspian and also the temperature difference between water surface of the Caspian Sea and the land surface temperature in the west of the coasts (Kuraplain) causes the formation of easterly flows from the Kura to the Southern Caspian water surface.
These easterly flows acts as a forcing in local scale in contrast with the westerly wind that is from the high pressure mass in Northeast of the Caspian Sea and causes the convergence of wind flow in the conjunction part of them and towards the lower latitudes. The convergence of 10-meter wind flow in the form of convergence band along the western coast of Southern Caspian enters to the small area of Southwest of the Caspian in the Gilan central plain or near the Anzali wetland and causes the intensification of instability in the lower layers of Troposphere.
The maximum snow concentration area dependson the convergence part of the flows in Gilan central plain. The images of MODIS Terra and Aqua and also the Kiashahr (Gilan) radar output in the 2014 snowfallconfirm the formation of cloud band coincident to the wind convergence band over the western part of the Caspian coasts that enters to the southern parts.
In recent decade, Gilan central plain has been affected by three main precipitation systems with super heavy snowfall. In order to determine the effective weather factors in regional scale in organizing the spatial pattern of the maximum snow depth event, the structure of these systems is investigated using the WRF numerical model with horizontal resolution of 21 and 7 Km. The output of the model has an appropriate accuracy in simulating the amount of precipitation and enhancing the two cores of maximum height of snow depth. (One in the central plain of Gilan and another near the Anzali wetland). The source of these three systems is the cold and high pressure polar air mass coming from the northern part of Russia and the semi-permanent high pressure of Siberia and accompanying with the deep troughs of atmosphere medium levels. The anticyclonic circulation with strong center over the North and Northeast of the Caspian Sea causes advection of cold air in lower layers of Troposphere. The cooling forcing, caused by the development of cold air mass over Caucasus Mountains and spread of mountain toplain cold flows, caused governing of secondary anticyclone in local scales over Kura plain in the West of the Caspian Sea.
The temperature difference between Kura plain and the Caspian water surface and also thepressure gradient between Kura plain and the Caspian Southwest coasts, is accompanied with the eastern flow of the wind field from Kura secondary high pressure. That in conjunction with westerly flows caused by clock wise circulation of anticyclone over the Caspian Sea, causes convergence of surface wind direction to convergence band along with Western coast of Caspian water surface.
The Converging flows are bearers of humidity flux and enteredto the small part in Southwest of the Caspian coasts that exactly matched with the highest snow depth in Gilan central plain. In the convergence part of the cold flow in MODIS sensor images of Terra satellite and also the image of precipitation intensity of Gilan radar output, thecloudy band is seen that confirms the results from numerical simulation and synoptic analysis.

The threshold word that entered the field of geomorphology studies by Schumm and Fabric in 1980 represents the time that a system reacts to an external factor such as climate change (Vitek&Giardino, 1993). The main difference between the internal and external types of thresholds is that internal alters donot change the structure of the system, but the outer threshold that is affected by external factors, changes and transforms it into a geomorphic system (Elverfeldt, 2011).A geomorphic system is confronted only with changes in external variables with external thresholds.Such as the reaction of alluvialfan systems, rivers, glaciers, etc., to climate or tectonic changes that make the geomorphic system more adaptable and adapt to new conditions(Huggett, 2011).One of the basic subjects in geomorphic studies is how to check the process of changes in the levels of the earth. Nowadays, the essence of geomorphic studies includes the analysis of form and geomorphic process on the level of the earth. In systematic view, geomorphic analysis is based on the form and process. Since geomorphic thresholds show the border conditions in making changes and in order to understand time changing, it is one of the basic concepts in systematic theory, it has a high value. GhezelOzanRiver and its branches in the Quaternary period have constantly been redirected to geological adaptation.As a result of these displacements, the process of alluvial to fluvial or fluvial to alluvial has changed in the opposite direction.These displacements are still ongoing and cause the river to stay away from the geomorphic equilibrium.The study of alluvial, fluvial and equivalent levels with the help of geomorphic thresholds is the main purpose of this paper. The GhezelOwzan river system is located in the North West of Iran and it pours in the Caspian Sea. This river finds its source in mountain of Kurdistan and length of over 550 km after crossing the provinces of Zanjan, East Azarbaijan, Ardebil and receiving multiple branches along your route anymore confluence with the river in Gilan province into the dam Sefidrud. Basin area is of nearly 49400 sq2. The river is located between the provinces of Kurdistan, Zanjan, East Azerbaijan, Ardebil, Hamedan and small part of Qazvin, West Azerbaijan and Gilanprovinces. The study area is located between 46.45°– 49.33°E and 34.92°– 37.92°N.
Material and This survey, which is based on library studies in the provinces, areas and balance on the way to systematic analysis, tries to study its threshold and categories in GhezelOwzan Basin. So, according to this analysis they are studied in three different areas, internal, external, synthetic samples of measurement curves of lithology, bondage and deviance, erosion_ ditch, gradient, geomorphology and geoneron to understand the subject better.Analyzing virtual form and processes basin have been carried out with the help of topographic, lithology, slope, drought maps (with the help of SPI and Moran index), geonerons (with the help of isotherm and isohyet maps, and using Justin), track ancient lake and erosional surfaces, geomorphological evidences captivity and diversion.
Rivers and captivity deviations can be detected in several ways: 1- Redirect with angles of 90 degrees or more along the rivers. Over time, rivers achieve a balance in their basin in terms of their topographical, hydrological and drainage condition.The bed of streams that are lithologically homogeneous there is no maze created by redirection. 2- Elementary and middle part of the river that is the source of the water, sediment and the coastal route (sometimes in the water), the sediments is of record. Alluvial deposits are not at the sources.The presence of alluvial deposits at the origin of GhezelOzan, either due to a redirection of the river, or due to the construction of the source ofGhezelOzan Plains 3- Over time a basin is almost symmetric, itmeans that the left and right banks of it become the same in size and is symmetrical over the time. It is the result of tectonic disturbance of fetal status or captivity and diversion of rivers; the main factor in much of GhezelOwzan, was to change the course of rivers. Shorter duration of waterways on one side than the other side of the river in GhezelOwzan, indicates the redirection of the river.4- The height difference is an inevitable phenomenon in the coastal watershed,but presencea difference in elevation along with less drainage length and diagenetic alluvial deposits in the dividing line, indicate the 90 degrees redirection of the river, relative to the previous track.The side of the river, which has a lower altitude, shows the length of the river's previous course. Such effects are very prominent in the direction of river redirection.Contour lines with deep pulses or deep sinuses between and below the contour lines of smooth to simple sinuses are a reason for river redirection.The prolongation of the equilibrium leads to a smooth contour lines, and the collapse of the equilibrium leads to the overcoming of recoil erosion and generates deep pulses in the contour lines.
The results showed that in the southern part of the zone a kind of geomorphic balance has yielded and the reason is the slow deplete of Bijar and its erosion surface configuration. By depleting these surfaces, the main rivers like Angoranchae and Sojasrood changetheir path and through a deviated path in present situation enter another place in GhezelOwzan Basin. The study of the zone geonerons also showed that Zanjanrood’s ford and Myane were absorbed; the amount of water which is less than the amount emerged it and if the rivers such as Angoranchae and Qaranghochae werenot joining on the path, so the river dried. In this case, the major sub rivers of the zone (Source and ford) are part of the reinforces and this occasion caused the GhezelOwzan River to be survived because of material and energy from sub rivers and to be away from their geomorphic equilibrium.

Climate change is one of the most discussed topics in climatology in the last two decades. Human as part of the climate system plays an important role in climate behavior. Especially, in the current era, increasing population and the human need for food and water sources and agricultural lands, loss of forests, desertification and increased use of fossil fuels lead to changes in the climate system. According to the Fourth Assessment Report of the Board of climate change among States Parties on Climate Change (IPCC), the global climate model predictions for the twenty-first century shows that global warming will continue to accelerate even if humans could take to prevent greenhouse gas emissions. It is predicted that by 2100 global average temperature change increases from 1.8 ° to 4 ° C and mean sea levels rises between 0.18 to 0.59 m up. The frequency and extent of events such as floods, droughts and heat waves are extended by increasing global average temperature. The effect of climate change on the planet is not the same. Some parts of the world are more sensitive to climate change than other areas. For example, areas with Mediterranean climate, their climate is highly dependent on temperature and precipitation, and thus these regions are experiencing stress in the face of climate change (IPCC, 2007).
High statistical downscaling methods have been proposed by Meteorological researchers. Two standard methods that are used extensively in downscaling of climate change models and can be used easily by users are LARS-WG model and SDSM. LARS-WG model is generating a stochastic model time series of climate models and SDSM is a combination of random generator weather and regression methods.
According to studies about downscaling, the SDSM has acceptable accuracy in downscaling climate data, however, most studies have been done on the basis of scenarios (AR4). However, this study intends to use the output of canESM2, one of the coupled climate change CMIP5 models based on new scenarios (AR5), to examine and simulate the climate variables, temperature and precipitation during the 21st century.
Study Area: Tabriz, East Azarbaijan province with an area of 1,200 square kilometers is located in 46 degrees 17 minutes east longitude and 38 degrees 05 minutes north latitude. Its height from sea level is 1366 meters. Tabriz is bounded on the north by mountains Einali and to the south slope of Mount Sahand and from the West to the plains of Tabriz and Urmia Lake.
Matarials and In this study, the effects of climate change in the study of Tabriz station due to long-term data were used. The basic observation period is 30-year period of 1990-1961. The daily minimum temperature, maximum temperature, rainfall in the corresponding period assessmented and validated by statistical tests and data were processed to produce daily random series. In this research, modeling canESM2 is the fourth generation of climate models by the Centre for Climate Modeling and Analysis of Canada (cccma) developed under the auspices of the country's environment. In this model, all the surface of the grid is 64 × 128 cells (charron, 2014). This study attempted to simulate climate, temperature and rainfall SDSM using multiple linear models and general circulation models of the atmosphere in the city of Tabriz. In this research, modeling scenarios canESM2, RCP8.5, RCP4.5 and RCP2.6 for future periods were studied in the 21st century simulations.
Result and Study Rainfall Changes
The results show that overall rainfall scenario evaluated in three studied scenarios, for the two periods 2010-2039 and 2070-2099 showed reduced precipitation and precipitation will increase for the period 2040-2069. On the whole the precipitation in the in the three scenarios examined, for two periods 2010-2039 , 2070-2099 will have been decreased and for 2040-2069 will have been increased. Also precipitation will generally increase in winter and the rest of the seasons will decrease.
Study Minimum Temperature Changes
Results show that the mean minimum temperature of Tabriz station in all months except November and December will increase in the coming period. In the period 2010-2039 the increase in temperature is not sensible, but in the period 2040-2069 and 2070-2099, the increase is quite significant and clear. Generally, the minimum temperature increases in three scenarios examined for three periods. The lowest increases in minimum temperature occur in the first period for the scenario rcp2.6 and the maximum temperature at the last period for scenario rcp8.5.
Study Maximum Temperature Changes
Results show that the mean maximum temperature as minimum temperature at Tabriz in the coming period will have a sensible increase and the mean maximum temperature of Tabriz station have increased in all months except October and November in the coming period. According to the results, we see that generally the maximum temperature in the scenario examined for three periods of study, increases the lowest maximum temperature rise in the first period for the scenario rcp4.5, and the highest maximum temperature rise in the last period for rcp8.5 scenario will occur. Generally, the maximum temperature increase can be seen in all seasons except the autumn rise in summer to 11 degrees temperature.
The results showed that temperature data have a higher correlation with the observed data; this is because of the less variability of temperature than rainfall and normal distribution parameter. The one of the reasons for the reduction of correlation in the rain is that various factors are effective on rainfall and other hand the precipitation is a discontinuous variable. So, the problem of solidarity in the development of future climate change models should be considered. Climate change can cause changes in climate variables time and space. The effects of these variables can have harmful effects on the ecosystem components. According to the results showed that in the 21st century temperatures are rising and rainfall is declining. Generally, precipitation in Tabriz station for two periods 2010-2039 and 2070-2099 decrease in three studied scenarios and increases for the period 2040-2069. The precipitation generally increases in winter and decreases in the other seasons. The mean minimum temperatures of Tabriz station in all months except November and December have increased in the coming period. The minimum temperature increases in the studied scenario for three periods. The minimum temperature increases in all seasons and in summer reaches to 8 degrees. The average maximum temperature increases in the studied scenario for three periods. Generally, the maximum temperature can be seen increasing in all seasons except the autumn rise in summer to 11 degrees temperature. Also as we approach the end of the 21st century this situation will be more intensified, This indicates that the climate change situation in the region is serious. However, more studies are needed to ensure more climate change in the study area.

In the general sense of the word, rainfall is the pouring of rain drops or frozen particles from the clouds which are formed due to a process known as condensation. Rainfall consists of rain, drizzle, snow and hail. When studying the clouds at middle latitudes, one has to focus on the basic types, convective and stratiform.Stratiform rainfalls have a low intensity and long duration. On the contrary, convective rainfalls from nimbostratus, altostratus, stratocumulus, and stratus clouds have a high intensity and short duration which pour from cumulus and cumulonimbus clouds. The occurrence of rainfalls in the form of convective and stratiform is one of the main dimensions of exploring the features of global rainfalls.
The logic of differentiating rainfalls was recognized by Simpson, Adler and North (1988), and Houze (1997) also presented some suggestions in this regard. Several researchers have presented different algorithms for differentiating among rainfalls, many of which are based on terrestrial information. Rolfova and Kysely (2013) differentiated among the convectiveand stratiform rainfalls of Hungary using the recommended algorithm and based on the time data of synoptic weather stations. Li, Zhai, Gao, and Shen (2014) introduced a new design for differentiating among rainfalls based on the combination of surface budget of differentiated rainfalls using the data simulation model. In another study, Tanvir et al. (2015) used a didactic algorithm for differentiating among the regime of convectiveand stratiformrainfalls which were obtained from the TMI microwave camera of the TRMM satellite. The results of their study indicated that this algorithm is capable of differentiating among different types of rainfalls with an acceptable accuracy rate. In the same vein, Thuraia, Gatlinb, and Bringia (2016) used the parameter for the features of rain drop size distribution which was gathered through radar information in Darwin, Australia. In a study conducted in the northwest of China which is among the driest regions in East Asia, Han, Xue, Zhao, and Lu (2016) demonstrated that during the period between 1961 and 2000, there weredifferent rainfall patterns in the annual precipitation of western and eastern parts of this region.
In the current study, convectiveand stratiformrainfalls have been separated (with the assumption that heavy rainfalls have a convective nature) through analyzing the synoptic codes of weather reports from six synoptic stations located at South Khorasan province in eastern Iran.
South Khorasan province in Iran has an area of 95388 km2 and is located between the latitude of 30° 31' to 34° 53' N, and the longitude of 57° 03' to 60° 60' E. This region has a dry and arid climate in low areas and a semi-dry climate in mountainous areas. The necessary meteorological data were collected from the synoptic reports of Iran Meteorological Organization for 6 synoptic stations at South Khorasan province which includes the amount of 6-hour rainfall, previous and current weather code during six hours and hourly data of cloud coverage, type of cloud, the degree of cloud coverage and temperature. Convectiveand stratiform clouds are poured from different types of clouds which are coded in the form of synoptic codes at meteorological stations. Therefore, in this study, the previous and current weather and the type of clouds are the first criteria for differentiating among the rainfalls. The two main groups of synoptic codes for showery convective rainfalls and storms were 80-90, and 91-99, respectively. Also, the codes for cloudbursts and lightning which occur outside the station include 17-19, 25-27, and 29 which fall into convective rainfalls. Three main groups of weather conditions for stratiform rainfalls include drizzle (50-59 codes), rain except for cloudburst (60-69) and snow (70-79) (Iran Meteorological Organization, 2009).
The second criterion for differentiating among rainfalls is the type of clouds. Convective rainfalls depend on cumulonimbus and cumulus clouds, while stratiform rainfalls are dependent upon stratus, stratonimbus, stratocumulus, and altostratus clouds. In this study, the files pertaining to synoptic data were decoded using SCdata software for each month of the year and for all stations. Also, non-zero 6-hour rainfalls were counted for all hours. Then, the rainfalls were categorized into convective, stratiform, and mixed groups based on the two pre-mentioned criteria. Finally, the time series of 6-hour convective, stratiform, and mixed rainfalls were obtained. Rainfalls more than 5 mm were converted into 6-hour convective, stratiform, and mixed rainfalls and their time series were obtained using weather conditions and/or cloud type.
The analysis of data and statistical investigation offered interesting results. For instance, from the total amount of rainfalls in Birjand weather station, 42% were stratiform, 47% convective and the number of occurrences of stratiform rainfalls (36%) was less than convective rainfalls. In fact, the results demonstrated that rainfalls of more than 5 mm result from the occurrence of stratiform rainfalls. In the stations at Boshruye, Ferdows, Nehbandan and Tabas, 73%, 77%, 59% and 69% of the rainfalls have a stratiform nature and less convective rainfalls occur at these two stations. The degree of stratiform and convective rainfalls in Qaen station were almost similar. In Qaen, Nehbandan and Birjand stations, the number of convective rainfall occurrences are 49%, 59% and 58%, respectively. Also, the amount of stratiform, convective and mixed rainfalls were similar in autumn and winter, while the amount of these types of rainfalls in summer is significantly different from the other seasons. Investigation of the other stations demonstrated that the rainfalls have a regular annual period, the maximum of which occur between November and April. This annual period shows that the maximum of convective rainfall is between May and October in Birjand, May and July in Boshruye, May and June in Ferdows, March and November in Qaen, April to November in Nehbandan, and May to September in Tabas. Since Birjand, Qaen and Nehbandan stations have a higher altitude above sea level compared to the other three stations, most of their summer rainfalls are from the convective type.
During the selected statistical period, stratiform rainfalls were reducing in all seasons, while convective rainfalls reduced in spring and summer. In Boshruye station, stratiform rainfalls have a decreasing trend in all seasons except summer, but convective rainfalls are experiencing an increasing trend in spring, autumn, and winter. In Ferdows station, stratiform rainfalls are decreasing in all seasons, while convective rainfalls show an incremental trend in all seasons except summer. As for Qaen, stratiform rainfalls have an increasing flow in autumn and winter, but convective rainfalls are experiencing a decreasing trend in all seasons. Both stratiform and convective rainfalls are decreasing in all seasons of the year in Nehbandan. However, in Tabas, spring and winter stratiform rainfalls are decreasing, while convective rainfalls are increasing in all the seasons. The average spring and summer rainfalls at South Khorasan stations are of the convective type, while autumn and winter rainfalls mostly have a stratiform nature. The pattern of autumn and winter rainfalls in all the stations of this province are very much similar. As altitude increases, the amount of convective rainfalls grows in all seasons, while the amount of stratiform rainfalls decreases in summer and winter. The inclination of convective rainfalls in spring and autumn are similar to one another.
There are significant differences in the dependency rate of rainfalls to altitude for both types of rainfalls in all the seasons. The results indicate that as seasonal temperature increases, the ratio of stratiform to convective rainfalls also increases at Ferdows, Boshruye, and Tabas stations and temperature growth results in changes in the amount of rainfalls. However, this ratio decreases for the rainfalls at Nehbandan station. As for Birjand and Qaen stations, the ratio of stratiform to convective rainfalls remains almost constant when the temperature increases and changes in temperature do not bring about any significant changes in the amount of rainfalls.
While many other studies use rainfall speed as measured by satellites and radars, the current study employed the 6-hour data of rainfalls, previous and current weather conditions, and the type of clouds as indicated by the synoptic data of meteorological reports in order to separate different types of rainfalls. The main advantage of this approach is that there is no need to convert these data, which is indeed the case with the data collected from radars. Also, their long-term time series is available and it is possible to conduct climatic analyses of stratiform and convective rainfalls. From this point of view, the method used in this study is an important step towards differentiating among the rainfalls at South Khorasan province in the long run. In the majority of stations, stratiform rainfalls have a decreasing trend, while convective rainfalls are experiencing an increasing trend. This issue may be attributed to climatic changes, which is in line with the findings of Rolfova and Kysely(2013). Since a vast majority of South Khorasan province stations have a dry and arid climate, and high-intensity rainfalls with short durations result in floods, rainfalls more than 5mm were considered as heavy rains. In all the stations, stratiform rainfalls are considered as the main type of rainfall (except for summer). In summer, all the heavy rains have a convective nature, consistent with the findings of Han et al. (2016) for China. In line with Rolfova and Kysely (2013) who found an increasing trend of convective rainfalls in spring, summer and autumn at all the stations of Hungary, the results of the current study indicate that on average, convective rainfalls have a positive correlation with altitude in the period between 1988 and 2014 at South Khorasan province. In Birjand, Qaen and Nehbandan, which have a higher altitude above sea level and are located beside high mountains, convective rainfalls are seen more often in summer.

Overshooting tops (OTs) are the product of deep convective storm updraft cores of sufficient strength to rise above the storms general equilibrium level in the tropopause region and penetrate into the lower stratosphere. Thunderstorms with OTs frequently produce hazardous weather such as heavy rainfall, damaging winds, large hail, and tornadoes.OTs are most identified in visible channel imagery as having a lumpy texture. However, they are only identifiable during the day and also most easily observed during early morning or late afternoon hours when the sun angle is low and the shadows on the cloud anvil cast by the overshooting tops are well pronounced. One of the most commonly used methods for detecting OTs is based upon the BTDs between the 6.2 μm and 10.8 μm (WV–IRW) channels. This BTD is positive above deep convective clouds and is related to the presence of water vapor above the cloud tops. Warmer temperatures in the lower stratospheric water vapor result in greater observed WV–IRW BTD values. The BTD of the ozone channel (9.7 μm) and the IRW channel also show a positive signature for cloud tops above 11 km. The signal in the BTD between the ozone and IRW channels is even more significant than the signal in the BTD between theWV and IRW channel near the tropopause.Thus, this BTD could be a better indicator of deep convective activity. The BTD between the carbon dioxide (13.4 μm) and the IRW channel is a good indicator of the height of the opaque clouds. The reason is that with higher cloud tops, the absorption effect of CO2 becomes smaller, producing a BTD of the CO2 and IRW channel that is close to 0 or positive, in the case of very deep convective clouds.
Material and In this study the convective system and its related overshooting tops that occurred in 27 march 2007 were studied using High Rate SEVIRI Level 1.5 Image Data from Second Generation Meteosat satellite. The data is transmitted as High Rate transmissions in 12 spectral channels. Level 1.5 image data corresponds to the geolocated and radiometrically pre-processed image data, with a spatial resolution (pixel size) of 3 x 3 km at nadir and a temporal resolution of 15 minutes. Preprocesses such as calibration, geo-referencing and brightness temperature calculation weredone using Envi software. Then, RGB color composites were used for monitoring convection as follow: Red: Cloud depth and amount of cloud water and ice, provided by the visible reflectance at 0.6 μm. Green: Cloud particle size and phase, approximated by the 1.6 μm solar reflectance component. Blue: Temperature, provided by the 10.8 μm channel. Overshooting tops weredetected using visible reflectance at 0.6 μm. Three OT detection methods, WV–IRW, CO2–IRW, O3-IRW brightness temperature difference (BTD), which use combinations of SEVIRI channels in the form of brightness temperature differences, have been tested and compared with OT detection in visible images. Then, the most appropriate BTD threshold was determined in any methods and areas identified as OT was compared in different methods. Finally, CAPE, low level jet, air flow pattern, relative and specific humidity Maps and graphs were presented and interpreted to understanding OTs occurrence conditions. To do this, all data was collected from ECMWF with resolution of 0.125˚*0.125˚ latitude/longitude.
Results showed that most of theOTs (but not all of them) wereformed in the region where the IR brightness temperature was lower than 215K. Using lower brightness temperature difference threshold ( or for CO2–IRW and WV–IRW and K for O3–IRW) led to exaggeration of OT number and extension in all three methods however they could identify all OTs. While using higher threshold (4 K for CO2–IRW and WV–IRW and 13 K for O3–IRW) led to the method failed to identify many of OTs. Thus, it was tried to determine the optimized thresholds that succeed to identify OTs as much as possible and have the least false detection. Finally, the thresholds weredetermined as follow: 3.1 for CO2-IRW, 3.5 for WV-IRW and 12 for O3-IRW. By these thresholds some OTs have not been detected and some pixels have been detected as OT falsely in all three methods, which was due to low spatial resolution. CO2-IRW BTD represent the best results because of fewer missed and false detections. So, while SEVIRI image and these methods have not enough to detectOTs precisely, they are very useful to assess temporal and spatial as well as their occurrence conditions.
Assessment of OTs occurrence conditions in 27 march 2007 revealed that there was a low pressure in west of Iran surrounded by some high pressureat low levels of atmosphere in occurrence day. High pressure in north of the Caspian Sea, north of the Mediterranean Sea and northeast of Africa was advected moisture air mass of the Caspian Sea, the Mediterranean Sea and the Red Sea to the low pressure in west of Iran. Also, there was a weak high pressure in the Arabian Sea which was advected warm and moisture air mass from the Arabian Sea, the Persian Gulf and the Red Sea to the low pressure in west of Iran. Low level jet in the study area has accelerated advection of warm and moisture air mass to this low pressure. Thus, air flow pattern resulted in moisture convergence from all resources in the region (the Persian Gulf, the Arabian Sea, the Red Sea,the Caspian Sea and the Mediterranean Sea) which has major role in the Mesoscale convective system (MCS) and OTs occurrence. So that special and relative humidity had reached 8-12 gr/kg and 100% respectively. Also, the special and relative humidity was high to tropopause and had reached 0.2 gr/kg and 90-100% in 200 hPa respectively. The maximum of the convective available potential energy (CAPE) was about 1200 Jkg-1 to 1500 Jkg-1 at the time of system formation Maximum of the lifted index was observed in the Red Sea convergence zone with value about -3 to -6,which induced to deep convection in this day.
In this study the convective system and its related overshooting tops occurred in 27 March 2007 was studied using High Rate SEVIRI Level 1.5 Image Data. Preprocesses such as calibration, geo-referencing and brightness temperature calculation weredone using Envi software. Then, RGB color composites were used for monitoring convection.Three OT detection methods, WV–IRW, CO2–IRW, O3-IRW brightness temperature difference (BTD) have been tested and compared with OT detection in visible images. Then, the most appropriate BTD threshold was determined in any methods and areas identified as OT was compared in different methods. CO2-IRW BTD represent the best results because of fewer missed and false detections. While SEVIRI image and these methods have not enough to detect OTs precisely, they are very useful to assess temporal and spatial as well as their occurrence conditions.
Low level jet in the study area has advected warm and moisture air mass in occurrence and previous day. Air flow pattern resulted in moisture convergence from all resources in the region (the Persian Gulf, the Arab Sea, the Red Sea, and the Mediterranean Sea) which has major role in the Mesoscale convective system (MCS) and OTs occurrence.The maximum of the convective available potential energy (CAPE) was about 1200 Jkg-1 to 1500 Jkg-1 at the time of system formation.Maximum of the lifted index was observed in the Red Sea convergence zone with value about -3 to -6. It revealed that low atmosphere was also instable in study daywhich induced to deep convection in this day.