bohlol alijani

Rainfall is the most important phenomenon or feature of the environment and so far many studies have been done about its causes. In any place, rainfall occurs when humid air and climbing cause are provided. Both of these conditions are provided by the circulation pattern. The study area is affected by some severe and sudden weather phenomena such as low annual rainfall, short rainfall period and rainfall in the form of heavy showers. Thus, it is possible that the limited and pervasive precipitation of the area is due to a different synoptic pattern. Because the relationship between circulation patterns and precipitation is significant, achieving acceptable results in the field of the relationship between these patterns with the limit and total rainfall of the studying area requires the analysis of synoptic maps. Therefore, the most important purpose of the present study is the synoptic analysis of heavy cloud rainfall of the studying area on Day 1398. Two sets of data were required for this study: A: Daily precipitation data of study stations on the day of heavy cloud rainfall on 21 Day (January 11, 2020) along with daily precipitation data in the days before the flood (96 hours before the flood) which was received from the main Meteorological Organization of the country. B: atmosphere data levels including: sea level (SLP), 850 and 500 hPa levels, vertical atmospheric velocity and wind flow levels of 1000, 850 and 500 hPa, specific humidity of 1000 and 700 hPa levels and 250 hPa surface flow winds for study days from the US National Center for Environmental Forecasting / National Atmospheric Research Center (NCEP/NCAR) were provided in the range of 0 to 60 degrees at north latitude and 0 to 80 degrees at east longitude, and finally, maps were drawn and prepared in Gardes software to provide the ability to interpret. The synoptic analysis of sea level showed that: on the day of the heavy cloud, a low-height closed center with a central core of 1,010 hPa in the northeast-southwest direction covered the entire study area. Then, the high-height with a central core equal to 1030 hPa is located at northwest of Iran, northwest of Europe and on Tibet. According to the location of high-pressure dams around Iran and the location of low-pressure centers on the study area and water resources in the south, a strong pressure has been created. Subsequently, with height increasing, low-height with central core equal to 1440 geopotential meters is located at northeast-southwest direction of entire study area. And the low height of northern Russia extends to the Persian Gulf and provides the conditions for severe ascent and instability in a very large area. The rear dams of Nave transferred the cold air of the high latitudes into the bottom of the Nave located on the study area and have intensified the instability. Also, the geopotential height of 500 hPa level of deep descent is located at the northeast-southwest direction of Iran and core of the Nave covers the Persian Gulf completely, that is the study area in the best condition and in front of the Nave, which is diverged by hot and humid weather. This deepening of the rotation and the penetration of the Nave to the lower latitudes caused the cold air to fall. The analysis of the 250-hectopascal-level flow-wind shows that the flow-wind with a core speed of 65 meters per second has covered the entire study area by crossing above the Persian Gulf, and compared to the previous days, the flow-wind is completely meridional. Synoptic analysis of the vertical velocity at the level of 1000 hPa shows that the maximum negative omega -0.2 to -0.15 Pascal per second in the northwest-southeast direction has covered the study area. The presence of negative omega index values ​​indicates the role of convection in intensifying precipitation in mentioned area and the dynamic ascent of air. The study map shows that compared to other countries in the study map, the maximum of negative omega is located on Iran, which is reduced along to the west of Iran. With increasing altitude, the maximum negative omega has increased to -0.3 Pascal per second and the core of the maximum negative omega is completely located on the study stations (Zahedan and Qeshm). Then, at the level of 500 hPa, the maximum negative omega has reached -0.6 Pascal per second and its value has doubled compared to the level of 850 hPa, which covers the northeast-southwest direction from Zahedan to the Strait of Hormuz. Cold air fall has increased with increasing of omega levels in the middle levels of the atmosphere.In other words, in the middle levels of the atmosphere, with increasing temperature difference between the earth's surface and the level of 500 hPa, the amount of precipitation has increased. Synoptic analysis of specific moisture level of 1000 hPa shows that the most moisture deposition was from south water sources to the study area, and the amount of moisture equal to 14 grams per kilogram has entered the study area from the Oman Sea and then its amount has been reduced crossing to other regions of Iran. Furthermore, at the level of 700 hPa, the maximum advection of hot and humid air is in front of the upper atmosphere of Nave from the Red Sea over the study area. There is a moisture strip from the southeast to the whole area under analysis. These suitable humidity conditions with the depth of the western wave have been able to cause heavy cloud rainfall. The maximum amount of moisture in the study area is equal to 7 grams per kilogram, which is a large amount compared to heavy rainfalls.

Extream snowfall event that may occur at any time during the cold season, has significant social and economic implications. Therefore, the economic and social consequences of these events reveal the importance of identifying the synoptical mechanisms associated with the extream snowfall events. In order to achieve this goal, using daily precipitation and temperature data during the statistical period of 1951-1 2016 and based on multiple criteria, the two three-days extream snowfall events were identified during February 7-9, 1972 and February 2-4, 1988. After selecting samples, a statistical analysis of the teleconnection indices was done and then, using the NCEP-NCAR reanalysis data, the combined patterns of surface and lower, middle and lower troposphere were plotted in the form of three-days mean. Results obtained from analysis of teleconnection indices and their correspondence to the synoptic patterns indicate the weakening of the tropospheric polar vortex and its division into multi-centers in the periods of extream snowfall events. In the event of February 7-9, 1972, though the centers were moved to mid-latitudes, but they are not completely out of the Arctic and to some extent maintain their position in this area. In February 2-4, 1988, the vortex centers have shown a more equatorwards displacement towards the mid-latitudes that the emergence of negative phases of the NAM and AO represent such a situation. However, in both events, the strong and main center of the polar vortex is located in the eastern hemisphere and therefore in a state close to Iran. The weakening of the sub-tropical jetstream in the eastern hemisphere, especially in the Mediterranean, has resulted in the transmission of potential vorticity tabs to mid-latitudes. The equatorwards progress of these tabs has led to the formation of the trough in the western and eastern Mediterranean regions that accompany with a ridge between them, led to the formation of omega bundle patterns and split flow, respectively, in the events of February 1972 and 1988 in this geographical area. The southern boundary of the progress of the troughs has specified by index contour of the edge of the vortex by 552 gpdam, that extends to the southern part of Iran and in the February 1972, event compared with the pattern of the February 1988, had the more-equatorwards progress toward the middle latitudes, and as a result, over Iran.

The interactions of circulation patterns are the interference or synergies of different circulation patterns from different latitudes and at different atmospheric levels. When interacting with circulation patterns, they will have different effects on the environmental phenomena of the Earth's surface than when acting individually. The mechanics of moving the telescopic link between the tropical zone and the subtropics is a major issue in geographical research. Considerable evidence suggests a dynamic relationship between tropical regions and mid latitudes. Tropical-extratropical interactions occur in a wide range of processes and at different scales.Tropical cloud plumes, reflects tropical- extratropical interaction in relation to the transfer of moisture from tropical to extratropical. TP was first defined by McGregor et al. (1984); a continuous strip of upper and middle clouds that are at least 2000 km long . clouds with minimum latitude of 20 degrees and maximum longitude of 5 degrees are in the tropical region. considers tropical cyclones as long bands of mid- and upper-level clouds moving from the tropical region to the polar-eastern direction to the subtropical region, especially continued by a tropical jet and a trough in its eastern part. TPs are relatively narrow at low latitudes (20–15 degrees) and widen at about 30 degrees north latitude. Studies of TP have expanded since the advent of satellite imagery in the 1960s. Prior to satellite imagery, McGurick et al. Described the development of TP in adaptation to a deep trough in subtropical jets and the turbulence of tropical winds, which ceases whenever this alignment is lost. The location and time of occurrence of plum clouds have been reported differently in different studies. In this study, we seek to investigate the Plum tropical clouds and the dynamic climbing factors that lead to their transfer to the midlatitude as a source of tropical moisture that leads to rainfall in Iran.

In order to investigate the role of TP event as an important factor in tropical-extraterrestrial interactions and as a source of moisture in the days with inclement rainfall, the 25th, 26th days of 2019 that Iran has experienced extreme precipitation were selected. The data used in this study are satellite imagery and atmospheric data. Since TPs are clouds that can only be seen in satellite imagery, IR Meteosat satellite imagery was used. Required daily atmospheric data, geopotential height (in meters), wind speed (in meters per second) and wind direction were used on an hourly time scale. The origin, path and direction of the clouds were identified using satellite images. In order to identify synoptic patterns at the time of TP occurrence, synoptic maps of geopotential height and jet stream for atmospheric indices (200 and 300 hPa) were drawn in GRADS environment using ERA5 data. Also, combined images of clouds with geopotential height and tornadoes were used for better investigation.

On March 25, at 0:00 a.m., the TP oceanic strip reaches 17 degrees along the North Atlantic cut-off low divergence zone, and along the orbital currents of westerly winds entering the tropics below the equatorial equator the subtropical jet stream is flowing. The bifurcation of TP corresponds to the bifurcation of polar front and subtropical jet streams. TPs correspond exactly to the kernels of jet stream. Jet stream core has not reached the east, southeast and parts of the northwest, so TP is not observed in these areas. The widening of the clouds occurred in the divergence zone of western trough over Iran and in the cut-off divergence zone of the Atlantic Ocean over western North Africa. At 06.00, with most of the jet stream core entering the northeastern and northern regions of Iran, TP has entered these areas. At 0:12, the wind speed of the core of jet stream has several degrees of southward displacement, which has led to the entry of TP into the southern and southwestern regions of Iran. At 0:18 East and TP continents originate from the Central African equator and enter Iran in the direction of the divergence zone of west trough and jet stream. Jet stream entered Iran in a more southerly direction, which prevented TP from entering northwestern Iran. On March 26, the subtropical jet stream is not orbital, unlike the day before. This factor can prevent the transmission of the TP orbit of the oceanic band to the east. The TP oceanic band reaches the Mediterranean with a south-north direction in the direction of the cut-off divergence of the Atlantic Ocean. Due to the location of jet stream core on the southwest-northeast diameter of Iran, the highest volume and extent of TP is observed in these areas of Iran. The entry point of TP corresponds to the entry point of jet stream core. At 18:00, the presence of the highest TP on the northeast of Iran indicates the presence of a speed core on these areas. On March 26, we see the southern transfer of TP in the direction of southwest-northeast diameter, which is in line with the southward displacement of the jet stream core to more southern widths.

On March 25 and 26 ,2019 The tropical intrusion of the extratropical dynamic factors has occurred. These factors are the deep extratropical western troughs and polar front jet streams. Their tropical intrusion has led to the transfer of tropical moisture to the extratropical region. The place of penetration of the western troughs into the tropics has determined the origin of the formation of clouds in the tropics. Also, the path and direction of the clouds from the tropics to the subtropics have been determined by the western trough divergence zone and the polar front jet stream at the level of 300 hPa and the subtropical jet stream at the level of 200 hPa. TP has entered Iran with both oceanic and continental origins and through the Red Sea and the Arabian Peninsula along the western trough divergence zone and speed core of the subtropical jet stream and polar fronts in a southwest-northeast direction. Two cloud bands merge on the Red Sea, Which lead to an increase in the Cloud moisture capacity on Saudi Arabia and Iran. With Transfers of clouds over Iran due to insufficient instability, clouds have led to precipitation. Tropical Plume clouds can be a source of moisture for offshore precipitation Tropical plume clouds can be a source of moisture for precipitation in extratropical. The presence of such a moisture source along with lower level moisture sources can increase the capacity of moisture, which in the presence of instability and lifting factors, cause more precipitation.

Investigating the components of general atmospheric circulation is important to discover the rules governing the country's rainfall. The relative vorticity as a key variable of synoptic motions is one of the best components in this regard. Relative vorticity is a measure of the intensity and direction of spin in a circular movement which is performed by a unit volume of air around the vertical axis perpendicular to the plane over which this rotation occurs. This research is looking for the relationship between spatiotemporal variations of relative vorticity and precipitation in Iran to improve forecasting skills.In this study the connection between the 500 hPa relative vorticity field and precipitation over Iran is investigated using canonical correlation analysis (CCA). Using of CCA statistical method is usual in climatological studies but it has not yet entered into the Iran climatological studies.

Two main data sets were used in this study; the time series of 500 hPa monthly relative vorticity fields and monthly precipitation for 97 Iran stations during the rainy season (November to February). The study area extends from latitude of 10 to 70 degrees north and a longitude of 10 to 70 degrees east over a region affecting Iran's precipitation.Relative vorticity monthly values (1981-2017) using the U and V component wind values obtained from NCEP-DOE reanalysis databases at grid points spaced by 2.5° at the pressure level of 500 hPa was calculated. NCEP-DOE Reanalysis II that is an improved version of the NCEP-NCAR Reanalysis I model that fixed errors and updated parameterizations of physical processes.The monthly precipitation data (1981-2017) were received from 97 synoptic stations of Iran and were used after standardization. To achieve the purpose of this study, at first the activity centers of vorticity and precipitation were identified by applying S mode principle component analysis (PCA). Then canonical correlation analysis (CCA) was performed on factor scores of these centers. The 30 years base period (1981-2010) was selected to applying CCA method while the years 2010 to 2017 were used as evidence.This multivariate statistical method was originally developed by Hotelling in 1936 from an interdependence model and first applied in climatology during the 1980s by Barnett and Preisendorfer and also by Nicholls in 1987.Canonical correlation analysis is a multivariate statistical technique for analyzing internal relations between a set of multiple independent variables (predictors) and a set of multiple dependent variables (predictants).This method is often used in atmospheric sciences to identify predictors within the datasets. Relationships between variables are highlighted through CCA.

The application of PCA led to 6 factors for the precipitation over Iran and 18 factors for the 500 hPa relative vorticity, accounting for 72% and 80% of the total variance respectively. The first meaningful factor of Iran precipitation is located in northwest of Iran.Second factor is extended from east to south and the fifth factor is in the Caspian Sea southern coasts.PCA factor scores time series of the each two sets were used for the subsequent CCA.CCA yielded three physically reasonable relevant pairs of patterns that describe the simultaneous responses of the precipitation field to the relative vorticity changes accounting for 82.5% of the common variance of both fields.The first CCA pair exhibits a correlation between the precipitation over east of Iran and the 500 hPa relative vorticity changes in the eastern Mediterranean and the Middle East. The second CCA pair reveals a negative correlation between the precipitation over the Caspian Sea southwest coasts and the relative vorticity activities, centered over Eastern Europe. The third CCA pair shows a correlation between the rain of northwest Iran and the relative vorticity activities over Turkey, Cyprus, and the Black sea.

The influence of the relative vorticity centers of activity in different regions of the Middle East, eastern Mediterranean, and Europe that appear in the form of the positive or negative relative vorticity on the Iran precipitation anomalies was investigated.In this case, three linear combinations were found by the canonical correlation analysis technique.According to the first pattern,  negative vorticity centered over the eastern Mediterranean and the Middle East is associated with below normal precipitation over the east and southern regions of Iran. In fact, the negative vorticity region in the eastern Mediterranean and the Middle East indicates the location of the ridge and the east of Iran locates in front of this ridge that is the area of descending movements that result in weather stability in this part of Iran.The second pattern reveals that however the relative vorticities will go up to the negative values in Eastern Europe; the rainfall will be higher on the southwest margin of the Caspian Sea. In the winter when Eastern Europe is located in ascending region of western winds (ridge), the Caspian Sea would be located in descending region of mid-level (trough) which will increase weather instability and increase precipitation in the southern coast.The third pattern says that as far as the relative vorticity tends to positive values in the Cyprus and Turkish cyclogenesis areas, the rainfall will be higher in the northwest of Iran. That’s because the extension of western winds in this area in winter could bring Mediterranean humidity to the northwest and west of Iran with no mountainous barrier.Therefore, these results can be used to increase rainfall forecasting skills in different parts of the country. The results of this study confirm the results of the study of Rezaei et al. (2012 and 2013).

In this research, we are trying to determine the “beginning time” as well as the “end” of the climatic seasons; and we will focus on identifying the displacement of these dates, which is influenced by the “climate changes” and “descriptionAbstract The purpose of this study is to investigate possible changes and displacements in Iranchr('39')s climatic seasons due to climate change. To do this, temperature, relative humidity, water vapor, wind and cloud data for 36 stations were received from the Meteorological Agency over 40 years. The data were divided into two 20-year series to allow comparison. Daily temperature data for each clustering time series were determined, then by considering 7-day sequences, the beginning and end of the seasons. The designated times were tested using the Rayman model. The results of comparing the seasons in the two time series indicated that in all stations, changes in climatic seasons occurred from Insignificant to significant. Climatic seasons in Iran do not correspond to calendar seasons, and climate change, especially temperature changes in recent decades, has caused the seasons to shift and shorten and lengthen. Although the beginning and end of the seasons do not generally correspond to their calendar dates, most of the days of these seasons occur in its calendar periods. The changes that have taken place have not only affected the length of the seasons, and these shifts have also changed the quality of the natural seasons. Keywords: Climate change, natural seasons, cluster analysis, Rayman model of the qualitative conditions” created in them, compared to the past climatic periods. “Meteorological Organization” data has been used in this research. Forty years of received data, was divided into two groups of 20. Applying SPSS, each group was divided into four stages representing each seasons. From these stages, the beginning time and the end of seasons were determined and the accuracy of the obtained dates was controlled with the comfort indicators of the Rayman model. The results of the comparison of seasons in two time series indicated that, the changes occurred in natural seasons from an almost non-existent one in all stations. Climatic seasons in Iran are not compatible with the summer season and climate change, especially the change in temperature in recent decades, has caused changes and shortening of seasons. Most of the days in these seasons occur during its monthly periods, although the beginning and end of the seasons generally do not match their calendar dates. Changes have not only affected the duration of the season, and these changes have also led to a change in the natural quality of the season.

In this essay, we investigated the effects of climate change on the rivers of selected basins of Guilan province, one of the northern provinces of Iran for the period 2020 to 2050 under three climate scenarios: RCP2.6, RCP4.5, RCP8.5. For this purpose, rainfall and temperature data from 45 climate data stations and 20 hydrometric stations from 1983 to 2013 were used. The average precipitation and temperature at basin level were calculated by drawing both Isohyet and Isothermal lines by usage Kriging method. Mann-Kendall and Sen’s slope estimator tests were used to determine the significance of the data trends and their slope, respectively. The results showed that temperature has increased in all catchments during the study period and this trend was significant in most of them but no significant trend was observed for precipitation. Discharge has also decreased in most basins and this trend was significant in Shafarood, Navrood and Chafrood basins. However, for future periods, precipitation is not significant in any of the climate scenarios, but the temperature is increasing in all scenarios except for the RCP2.6 scenario. Rivers discharge in the RCP2.6 scenario is not significant in any of the basins, but in the RCP4.5 scenario the Shafarood and Ghasht-Roodkan catchments have a significant reduction in the 95% confidence level. In the RCP8.5 scenario, the Chafrood and Shafarood basins have a 99% confidence reduction trend. Population and technology growth, increased water consumption and climate change have led many researchers to study and model water resources in the present and future periods. Especially in areas like Iran that are facing a lot of water stresses. The purpose of the present study, which was carried out in the Guilan province, is to provide information on the present and future status of surface water resources, and to prepare them for facing the problems of potential water resources exploitation. In this study 45 synoptic, evaporative and rain gauge stations and 20 hydrometric stations data with sufficient statistics were used. The period of study is also between 1983 and 2013. In this regard, after calculating the average precipitation and temperature values of each basin using Kriging model, first, the annual average of precipitation and temperature values ​​of each basin were calculated. Then, multivariate regression was used to obtain the regression equations between precipitation, temperature and discharge data, then by using SDSM model and climate scenarios (RCP2.6, RCP4.5, RCP8.5) future temperature and precipitation data were generated. By placing these generated data in the Created regression equations, the discharge of the rivers was calculated for the period 2020 to 2050. The trend of time series and their slope were analyzed respectively by Mann-Kendall and Sense tests. The study of the annual average precipitation trend of the selected catchments during the study period showed that all the basins had no significant trend at any of the confidence levels (95% and 99%). However, for the temperature there is an increasing trend. In Chafrood, Zilaki, Chalvand, Lavandevil, Tutkabon, Chubar, Lamir, Hawigh, Dissam, Shirabad, Ponel, Samoosh, and Polrood basins there is significant trend at 95% confidence level. For the Hawigh River basin there is significant trend at 99% confidence level. Also in most of the basins there is a downward trend of rivers discharge. In addition, in the three basins of Chafrood, Navrood and Shafarood, there is a significant decreasing trend at 95% confidence level, which is also significant at 99% confidence level for Navrood and Shafarood rivers. Analysis of future data showed that precipitation is not significant in any of the climate scenarios, but the temperature is increasing in all scenarios except for the RCP2.6 scenario in RCP2.6 scenario. For rivers discharge there was no significant trend in any of the basins, but in RCP4.5 scenario there is a significant decrease in 95% confidence level in Shafarood and Ghasht-Roodkan. Also in the RCP8.5 scenario, a significant decreasing trend of flow discharge at 99% confidence level is observed for Chafrood and Shafarood basins. Finally, the catchments were grouped according to the level of risk involved with decreasing discharge. The results of grouping showed that most of the basins in the three scenarios were in the medium risk group but Shafarood, Chafrood and Ghasht-roodkhan watersheds have higher risk than the other watersheds, respectively. Investigation of river discharge trends for the period 2020 to 2050 in different scenarios showed that the basins of Ghasht-roodkhan, Chafrood and Shafarood are more sensitive to climate change than other basins. Overall, escalating temperature trends in future and precipitation irregularities can create very difficult conditions in future to use these resources. Especially, this studychr('39')s concordance with other studies in Iran and the study area confirms that such crises are more likely to occur..

Probability distributions and different mixed regression models are used to study of wet and dry spells. In this study, eight stations on the southern coast of the Caspian Sea were used for 55 years (1960 to 2015). One and two day wet spells are the most frequent in the area. Also, four and higher days wet spells in the western region is more than the east. The best probability distributions of wet spells are two-parameter gamma, two parameter normal log, two parameter logistic log, four-parameter generalized gamma, generalized three parameters gamma, two-parameter gamma, three-parameter gamma and a three-parameter logistic log. Also, the dry spells of the region are better fitted with generalized Parto, generalized logistics and generalized extreme value distributions. Due to the random behavior of the annual wet and dry spells, the best generalized linear mixed model for wet spells is the negative binomial log, Log Poisson, log normal and gamma logarithmic, also the Log Poisson, log normal and the negative binomial distribution was determined for the annual dry spells.</div>

The weather fronts are  known for their large vorticity, dense, moisture, and statical Stability gradients,   and their longitudinal scale is one unit greater than their width. The width of the front is known as the baroclinical zone, in which the front lines have a very large temperature gradient, which is determined by the angle between pressure and temperature lines. Position of a front is located in warm side of the extreme temperature gradient, inside the heat transfer zone and  intensity of the front is determined by the size of the horizontal or quasi-horizontal temperature gradient.Even the numerous expert synopticians disagree with each other in the position of the fronts, their types and intensity, in the manual drawing method of the fronts. So their drawn  fronts are very different While objective front is based on numerical methods and its purpose is to avoid applying people''s tastes in their manual method. The advantages of objective front metod in comparison with subjective front method are high speed front detection, the possibility of determining front frequeny, moving, and feedback of fronts with land side effects. So far, various methods have been developed for objective front method. They performed objective front method using numerical methods and the first and second derivatives of the temperature parameter on a regular grid points with a relatively low resolution of about 100 km. Inside the country, there has been no study about automatic and numerical front methods. On the other hand more than 90 percent of heavy rainfall in the tropics is associated with the fronts. Therefore, considering Iran''s location in the middle latitudes, it is very necessary to study and identify the fronts. So the climatological study of the manual front detectin is very time consuming, expensive and practically impossible. Therefore, in this research, the, automatic and numerical front detection have been discussed for the first time in the country.

In this study, grid point data  from the European Center for Medium-range Weather Forecasting (ECMWF) of type (ERA - Interim) is used with gaussian grid points. In this centre, different types of data are classified into different formats and in different time intervals and different grid resolution. In order to study  of the fronts, isobaric level data with 6 hour intervals and resolution of 0.75 × 0.75 degrees with grib format is used. This grid resolution is set in a regular 61×61 matrix with a grid distance of 83 km. Different quantities can be used to select the appropriate parameter to detection of fronts such as temperature, humidity, wind direction and wind speed, vorticity, thickness and thickness changes ,and temperature is on of  the most important of them. On the other hand, detection of the exact location of the extreme temperature gradient, which is accompanied by the effects of heating on the warm convergence belt in the warm side of the front leads to warm weather, can be identified only by using the equivalent potential temperature.

The main idea for identifying frontal areas is to use a temperature parameter in two-dimensional horizontal coordinates. The line representing the front in these areas is identified using a frontal identification function. In order to identify the front, the masking conditions are applied once or several times. In other words, in this equation, the horizontal gradients of the equivalent potential temperature are used, which should not be less than the value of the K-threshold value. >K  . Several indicators are considered to identify the front. The first of them is that the front must be at a turning point in the curvature of the temperature lines which is along the temperature gradient. The second indicator is the location of the maximum values of temperature gradient,and the third criterion is the point where the second derivative of the temperature gradient is zero. Various experiments have shown that the smaller the temperature derivative of the front temperature parameter, the less error there will be (J. Jenkner, 2009). Thus, the Front Termal Parameter (TFP), invented by Renard & Clarke (1965), was used as the main method of frontal reconnaissance. TFP = In this equation, second derivative of the temperature parameter has been used, which has converted the temperature gradient, which is a vector quantity, to a scalar quantity.

Examination of the results of objective fronts showed that the detection of fronts near the ground due to the interaction between the boundary layer and the fronts is very erroneous and the fronts are practically indistinguishable. On the other hand, at higher levels, shallow fronts at numerical output are not detected. Therefore, the appropriate level for automatic identification of fronts in the study area, 700 hPa level was selected. Examining the results, it is inferred that cold and warm fronts are often found at the bottom of the ridge and above the ridge of the upper surfaces, and these fronts, during the formation stage, are often discontinuous and gradually evolve during the developmental stages. Strengthening the front will take a more integrated form. Studies have shown that cold fronts produce stronger frontogenesis than warm fronts. Also, the output of objective fronts showed that TFP is a good parameter for detecting the front in this region and with the results of previous studies such as Hewson (1998: 49), Jenkener et al. (2010: 9), they show a good match. The results of this study can be used in the discussion of climatology and forecasting of fronts and can be helpful in the discussion of flood management due to heavy rainfall on the front.

Introduction :

Dusts are referred to as aerosol particles that are made up of different sources of land and humanization, and after which time, again, they fall on the surface due to their size and density (Salman Zadeh et al., 2012). This phenomenon can damage infrastructures, telecommunications and agricultural products and affect transport through reduced visibility and cause a lot of economic damage. (Song et al 2007., Cao et al 2016). The purpose of this study is measuring and spatial analysis of the city of Tehran in a one-year statistical period. 

Materials and methods:

 In this research, we used the laboratory method to measure falling dust, collecting dust using Marble Dust Collector. For this purpose, the falling dust was collected using a Marble Dust Collector in 28 stations in Tehran during the statistical period. In order to analyze the spatial distribution of dust, dust was collected from 28 dust collecting stations, and Tehran PM10 data taken from the air quality control company, the number of construction urban under construction in Tehran were obtained from Tehran Municipality Organization, mean maximum wind speed parameters, average relative humidity,days of rainfall above 5 mm,the average temperature of Tehran taken from the country's meteorological organization in the one-year statistical period (1/10/96 - 30/9/97) to enter the Arc Map10.5 environment and preparing the desired layers Were prepared. Statistical analysis of the data showed that Dust collected, pm10 and the number of running construction projects have regional (trend) behavior. Therefore, Universal trend is better suited. Due to the high preconditions for stagnation use of Universal trend In the area with fewer meteorological stations (Chitgar, Geophysics, Mehrabad and Shemiran) Universal trend is not applicable, Therefore, the IDW method was selected for climatic parameters. Also, the vegetation cover and factories file Shapes were taken and by analyzing Euclidean distance of each of these complications in GIS for Tehran, there impact on the dust in each area were considered. Then all the layers were weighed to determine the weights using the Reclassify tool. Then, using Expert Choice software, we compared all the layers two by two till estimate the value of each layer relative to the other layer. We multiplied the values obtained at each level. We transferred all layers to the Fuzzy Overlay tool. And draw up the final map of the spatial analysis of falling dust in Tehran city using the Gama 0.9 function. Also, daily speed and wind direction data were received from the Meteorological Organization of the country during the one-year statistical period, (30/9/97- 1/10/96). And with the help of the WRPLOT software for statistical analysis and the location of the wind, the windrose was drawn. Results and discussion The results of computations performed on the data obtained from the collecting of falling dust in Tehran showed that the weight of falling dust in the winter of 1396 is 18943.5 tons, in the spring of 1397 it is equivalent to 27119.5 tons, in the summer of 1397 it is equivalent to 17111.2 tons and in the fall of 1397 it is equivalent to 23002.3 tons. Also, the results showed that the highest falling dust was collected in spring, autumn, winter and summer, respectively. The spatial analysis map of Tehran's falling dust is a combination of 9 layers, based on the weight assigned to each layer. The results showed that the highest amount of dust in the winter of 1396 was found in west of Tehran. We had the lowest amount of falling dust in the north and northeast (regions 1 and 4). In the spring, summer and autumn of 1397, the halo of the most falling dust was displaced slightly eastward and settled in the southwest. The lowest amount of dusts in these seasons was located in the north and northeast. The halo with the lowest amount of dust falling has expanded further in the autumn than spring and summer.

 Conclusion:

 The results of this study showed that the spatial distribution of falling dust varies in different seasons. Which shows that the source of falling dust in the city of Tehran is not uniform throughout the year. Field precise surveys have shown that the increase in falling dust in different parts of Tehran is directly related to urban construction. So that in the statistical year of the study, construction and subsequent falling dust has been less in eastern Tehran than its west and this increase is also associated with pm10. The largest amount of pm10 was reported from the west and southwest, which simultaneously collected the highest amount of falling dust. The highest density of factories and the lowest vegetation density are in these areas. The climatic factors also contributed to these conditions. So that, It was reported that the highest number of rainy days to exceed 5 mm was reported in north and north east of Tehran, where the lowest amount of dust was collected. And the highest average temperature in different seasons is reported from Southwest of Tehran, which has the highest amount of falling dust in spring, summer and autumn. But in winter climate conditions were slightly different from other seasons. So that, the highest relative humidity reported in other seasons from the West has been reported from north and northeast this season. The dust collected in winter is higher in the west than in the southwest. But the average maximum wind speed, which is in the west and south, is in the winter, spring and autumn to the west and southwest Which is from sand quarts of Quds, Shahriar, and Malard cities, especially the sandy-sand dune areas and abandoned agricultural land in Baharestan, Islam-Shahr and Robat-Karim, then dust from these areas enters Tehran west. In addition, the wind disperses the dusts generated by construction around the city. In the summer, in addition to the west and southwest, there is wind for north and south east. The northern wind comes from Shemiranat, bringing fresh air to the north and north-east of Tehran. The southeast wind passes from the Pakdasht sand and cement factories in Tehran and the abandoned agricultural land of Varamin and contains dust. The low wind speed in these areas gives more time to hangs off more particles. And of course, climatic conditions with the lowest relative humidity, the highest temperature, and a lack of rainfall above 5 mm also help to pollute the southern part of Tehran. Keywords Spatial analysis, Sediment trap, Tehran City, falling dust

Recognizing the interactions of the large-scale components of atmospheric circulation creates an appropriate capacity to examine the regional climate variability and improve description of land-atmosphere connections. Assessment Iran vulnerability to climate fluctuations is very important. Part of this recognition will be achieved by assessing the components of the atmospheric circulation. The relative vorticity distribution is an important index of synoptic motion in mid latitudes. Regions of positive relative vorticity are associated with cyclonic storms in the Northern Hemisphere. Thus the distribution of relative vorticity is an excellent diagnostic for weather analysis. Vorticity, the microscopic measure of rotation in a fluid, is a vector field defined as the curl of velocity. Relative vorticity is a measure of the intensity and direction of spin in a circular movement, which is performed by a unit volume of air around the vertical axis perpendicular to the plane over which this rotation occurs. Relative vorticity is a good quantity for studying atmospheric changes, because it presents the main order of magnitude of daily cyclonicity or anticyclonicity.

. Caspian Sea south coast future climate change estimations through regional climate model
many physical of the procedures related to climate change are not perceived thoroughly. Scientific knowledge used to show those procedures completely, and to analyses forecasts is so complex, since most current studies about climate physical model have been done through semi experimental and random models and most of the current analysis techniques are still going through early stages. One of the important aspects of this study is modeling physical procedures of sea level rise geographical pattern, which is used practically for SLR threat evaluation of special geographical location, meaning Caspian basin. Since Caspian basin is a closed sea, it is heavily influenced by climate change and meanwhile is changing due to physical level and environmental change. It is necessary to define Caspian coast climate change possibility with specific focus on climatology and meteorology fine data, also to define the scale of sea level fluctuations for the sake of exact planning in different fields. This study aims at presenting a new dynamic method, via using an integrated model system named SIMCLIM, which can clarify SLR satellite changes well.
According to scientific examination existing in this study, based on scatter scenario 4.5 RCP and 8.5 RCP for the following years, until 2100, temperature and precipitation change proposal have been presented. On one hand, Caspian coastal climate change analysis and estimation were based on climate patterns and water flows in the form of regional climate statistical model in order to simulate and forecast, on the other hand surveying chronological changes of Caspian sea coast slope with satellite height measurement was done to measure sea surface height fluctuations The present study has used SIMCLIM model for the first time in order to clarify Caspian sea level changes, elements, and effective climate reasons, all simultaneously in one project. The project base is according to coastal systems and procedures. Coast line shore change simulations are based in Bruun law.
In future the frequency and intensity of extreme events temperature and precipitation will increase. Extreme events illustrate changes in extreme temperature and precipitation measures, in comparison with the base period of 1981-2010 which convey precipitation sum or the temperature beyond 95 percentile of base period. Temperature and precipitation coefficient of variation for the whole Caspian basin is positive and it varies from 25 to 88 percent. A disordered pattern is dominating south basin of the sea. Sea level changes, considering vertical earth movements, which is 2 mm in a year, resulted from subsidence of Caspian pit seabed have been obtained for both scenarios. In general, annual sea level average while ignoring seasonal changes, is increasing consistently and it was calculated 1.22 cm each year according to high estimation procedure in scenario 8.5 RCP and it was 0.93 cm based on scenario 4.5 RCP. Predicted results were compared with real results of base20-year period from 1995-2015. Base period results in three levels of sensitivity of low, mid, high shows 8.4, 10.1, and 11.8 cm rise; after comparing them with model forecast results, meaningful coordination at the level of 95 percent was found out. In both scenarios, all over the Caspian shoreline water advance and destruction will exist. In the worst case scenario of 8.5 RCP of 2030, current coast will decrease about 23 meters and in 2060 it will be about 53 and in 2100, there will be 117 meters advance towards land.
Precipitation and temperature percent for 2030, 2060, 2100 will change increasingly. Spatial variability and annul coefficient of variation are various in different regions. North, western north, eastern north and east will include the least temperature fluctuations, and the highest percent of precipitation with the highest coefficient of variation all convey chronological period precipitation distribution with disordered accumulation and more local difference in this region in comparison with other regions. Then Caucasus mountainous region will have the highest increase in precipitation with a suitable scatteredness, during a year. The southern part of Caspian Sea will be with the highest increase in temperature and the least amount of increase in precipitation in percent. High coefficient of variation in this area illustrates abnormal and disordered pattern on the threshold of precipitation for both scenarios.
 fluctuations in sea level based on subsidence of Caspian pit seabed was calculated.In general, average annual sea level is increasing which will be 1.22 cm, per year for scenario RCP 8.5 and 0.93 cm for scenario 4.5. Due to incapability of world community in decreasing releasing greenhouse gases, it is expected scenario that 8.5 RCP to come to reality.
 Caspian Sea shoreline is influenced by water advance and destruction. The difference between two scenarios in 2060 will be 3 meters and in 2100 will be 12 meters. Instinctually, such advances in coasts with less depth and less slope will be more. This study suggests that coastal changes are inevitable. However, this region inhabitant owns no systems or no systems have not yet developed to aid them be able to adopt with the climate changes.
 
Keywords: Sea level rise, South Caspian basin, Extreme event, Coefficient of variations, shoreline.

  The activity of synoptic cyclones plays an important role in determining the local climate and the formation of large-scale atmospheric circulation through the vertical and horizontal exchange of heat, humidity and momentum, coupled with interaction with large scale circulation centers (Zhu et al, 2001: 1523). The cyclones generally are transmitter the bad weather conditions and also represent the initial mechanism of transmitter moisture and heat to the pole. Systematic changes in geographical location or the intensity / frequency of cyclone activity will have significant disparities among other regional climate impacts (Wang, 2006: 3145).
The effect of mountainous obstacles on synoptic systems, especially the cyclone systems, has known. The mountain range is one of the factors, In addition to disrupting the face of the earth's uniformity, also disrupt the climatic uniformity. The purpose of this study is to determine the effect of thermodynamics of Zagros Mountain on the changes in cyclones entering the country from the west. For this purpose, the daily precipitation data of 13 stations of the Meteorological Organization in West of Iran were received. Also geopotential data were extracted from the NCEP / NCAR databases with spatial resolution of 2.5 × 2.5 degrees and ERA-Interim data from ECMWF databases with spatial resolution of 0.125 × 0.125 degrees, thier framework is 0 to 80 degrees east and 0 to 60 degrees north.
Using the Factor Analysis method, April 14th-18th, 2003 was selected as the best pattern. After selecting the sample day, sea level pressure maps and geopotential heights of different levels were prepared and analyzed. The result of the study of these maps showed that the cyclone reaching the Zagros Mountains, dynamically strengthened from the day it formed until it arrived in Iraq. When approaching the Zagros, the vorticity and its omega are reduced, but crossing Zagros, a positive vorticity increase happens. These types of cyclones call Zagros cyclones. The relationship between the amplified cyclone with the divergence region of the middle and middle levels were observed at all stages. The Zagros roughness, like a wall, initially causes the cyclone reached with Iran to weaken and become bipolar. But the passage of the cyclones from it, the thermodynamic conditions of the descending air in the lee mountain range, that makes them revival. As the roughness collides, a weak core remains in the Zagros range, and another nucleus is formed by passing through the mountains in the central regions of the country, and is reinforced in the next hours; and finally, the cyclone is amplified and it leaves Iran completely. These cyclones can be called zagros second cyclones. Mountain barriers consider as the factors destroying the homogeneity of the local climate.
Sometimes they act as the planets like the Rocky Mountains. Iran's land are heterogeneous due to elevations in the north, west, and other areas, Iran is heterogeneous in term of geomorphology and climatology.
One of the most outstanding effects of roughness on the climate is the change in the structure of systems passing through these barriers. Zagros Mountains is one of the main mountain ranges of Iran, with an almost northwest-southeast direction with a maximum height of about 4,400 meters zardkuh, has a significant impact on immigrant systems in the country.
A study on the cyclone on April 14th , 2003 showed that this cyclone was formed on the April 12th on the northwest of Europe, moving towards the Mediterranean Sea. its trough arrives in the country on the April 14th and it reaches the slopes of Zagros on the 16th. As Zagros is approaching, changes in pressure in the back and the lee of Zagros are increasing. Vorticity and divergences are completely different in two parts. In the altitudinal areas in the Zagros line, during a few days and during the passage of the cyclone, there is a negative vorticity. The vertical velocity also demonstrates subsidence in Zagros altitudinal areas. The results vividly prove that the cyclone is(get) weakened in collisions with the Zagros, and its movement gets slowness(slow), but it does not disappear. But also it is re-reinforced on the Zagros lee in the central of regions, and continued its route to outside the borders of the country.
Keywords: Lee cyclones, cyclonic vorticity, Vertical Velocity, humidity flux, Zagros

This study investigated, the role of variables and agroclimatic indices on rainfed wheat yield in Kurdistan province. The database was formed by collecting 31-year circuit data on planting area, production, losses and yield of wheat in 10 regions of Kurdistan province, and data of climatic elements on the hourly, daily, decade, monthly, seasonal and yearly levels related to 22 nearby synoptic stations. Data base completed after data preparation. 113 climatic and agroclimatic indicators were calculated using 15 primary meteorology elements of meteorological stations. Finally based on thecrop calendar and phonological stages of wheat, to investigate their effects on yield, 128 independent variables were selected. In order to calibrate the dates of the calculated phonological stages, the estimated agronomic calendar was compared with the recorded calendar results of neighboring rainfed wheat research stations of International Center for Agricultural Research in Dry Areas (ICARDA) in Kurdistan and other adjoining cool provinces. To identify and isolate variables that independently of each other affect yield, most correlated (Significantly) variables were eliminated. The correlation of the variables determined with wheat yield was measured. The effect of variables on wheat yield rate (kg/ha.year) was evaluated using multivariate regression “Enter” and “Stepwise” methods. Identified effective variables and indicators were interpolated based on geographical and height characteristics. According to the spatial variations of variables, the spatial model of wheat yield was introduced for province and areas of the province.
The results of this study showed that with a 99 percent confidence, climatic elements (variables) vary in different regions. Most of the independent variables have a significant effect on wheat yield in simple linear regression, but in Stepwise method, due to the internal correlation between variables, just variables entered that have insignificant correlation with each other and have more effects than other variables. The variables affecting the performance are differentin various regions, and from the point of view of effectiveness, the arrangement of the variables in different areas vary too. In other words, even in two regions with a climatic type (based on the Modified De Martonne method), both agro-climatic indices and wheat yield are significantly different. The impact of effective variables on yield at any time and place depends on the time of year and the phonological stage of wheat. At one time the environmental conditions of different regions in terms of temperature, humidity and precipitation differ, based on phonological stages of the regions. The time of the vulnerability of wheat varies from place to place. Wheat vulnerability at flowering stage is more than other stages. The effect of independent variables on yield at different times of year is proportional to the phonological stage in years Different and different in different regions. In Kurdistan province, the number of rainy days of the year, total degree hours the temperature reaches below -11 °C (sum of hours with below -11 °C temperature) from germination to tillering stage, the annual precipitation, the rainfall in the fifth decade of the water year (the precipitation of 11-20 of November), annual relative humidity and total degree hours the temperature reaches above 30°Ctemperature (sum of hours with above 30 °C temperature) in milky and dough stage is the determinants of the production of rainfed wheat. In Baneh and Marivan areas, the coefficient of variation (CV) is lower and in Bijar and Divandareh regions CV is more than other regions. Kamyaran region has the highest yield, Baneh and Marivan were ranked secondjointly. Sanandaj and then Bijarhave the lowest yield. Each region has a model for wheat yield and determinant factors vary from region to region. Although the annual production of Bijar is higher than other areas, wheat production in the Bijar region has a higher risk than other areas.

In the upper level (300 hPa) a widespread positive vorticity has seen on the Mediterranean and the Black Sea. In this level, the length of summertime became more than ago from 1990s and the negative vorticity has increased in the recent decades. In the 500 hPa level the positive vorticity intensity on the Cyprus and Turkish area has decreased from 1990s. The cold season in the lower level is finished earlier than middle level because at this time air is warmer than sea but at the middle level the cold period takes longer so in this level cold air mass privates yet. There is an increasing trend of negative vorticity in the west and positive vorticity in the east of the Caspian sea in the cold period of the 850 hPa level that is in agreement with a decreasing of the intensity of Siberian high pressure and a weakening of the Black Sea low pressure system from 1980s.

The variation in the rainfall regimeincluding the striking aspects of climate change. Reduce or increase the amount of rainfall on many environmental and climatic phenomena such as runoff, flooding, air temperature, air humidity as well as the many human activities such as agriculture, type of housing and its effects. On the other hand the growing need for understanding climatic features of the necessities of human life today.
The first long-term data to identify areas of precipitation in Iran Hour Precipitation 53 synoptic stations from 1984 to 2013 were collected from Meteorological Organization. First to obtain day precipitation and more precipitation 7 categories 1/0 days of rain, the daily and hourly to precipitation rainy days spread over 7 floors, 1-day precipitation, precipitation sequence, two days, three days or annual precipitation sequence 7 days and was extracted sequences reviews. To perform cluster analysis and zoning of the Euclidean distance and Ward method to minimize the sum of squared deviations in the relevant classification groups. In order to study the characteristics of both indices rainfall coefficient of variation and uniformity profile is used.
Results and Discussion In this study, using the characteristics apply cluster analysis showed that 7 days of rainfall and precipitation regions in the country. As the number of rainy day, rainfall, rainfall distribution is different in each of these areas. Region 1 area dry with sparse rainfall, storms and rainfall when the distribution is irregular density. This region has the highest spatial variability and the highest coefficient of variation is annual. Only in the summer because of the the summer monsoon rains, the coefficient of variation has experienced less rainfall distribution is appropriate. Unlike the summer, the autumn had the highest share of rainfall. The area of the temporal distribution of rainfall and uniformity rainfall, the lowest annual index is uniform. Region 1 includes stations Bandar Lengeh, Konarak, Chabahar,Zahedan, Bandar Abbas, Bam, Zabol Iranshahr and Kish. The second Region is a dense irregular rainfall. This region has the highest coefficient of variation is the summer season. In this Region due to low and sparse showers, rainfall has been high Temporal and spatial variations of rainfall. Region2, the area includes stations in Abadan, Yazd, Tabas, Fasa, Bushehr, Kerman, Birjand and parts of East, Central and parts of South West Iran is included. .The Third Region includes the coast of the Caspian Sea, which has the lowest coefficient of variation each period and yearly. Region 3 includes the Caspian Sea coast which has the lowest coefficient of variation each period and yearly. The temporal distribution of precipitation areas is almost uniform density. region 4, covering the North West and North East Iran, that includes the stations of Ardabil, Gorgan, Pars Abad, Khoy, Bojnord, Tabriz, Quchan and Shahrud. It has precipitation regions in three ten-year period when distribution is uniform. In the spring due to Azerbaijani and distribution of spring rains this season than the coefficient of variation is the lowest was seven. Region Rainfall 5 has a high coefficient equal to 146 and lack of uniformity is the uniformity index is equal to 52 which represents the precipitation average density. Region 6 Tehran stations, Dowshan tppeh, Maragheh, Karaj, Qazvin, Shahrekord, Mashhad, Orumiyeh, Zanjan included. This area equal to 111 and uniformity coefficient of variation is equal to 59 and indicates a lack of proper distribution when precipitation. In other words, is the average density areas. Region 7 West and South West regions of the country, mainly in the covers. Features irregularity of rainfall and precipitation medium density in this Region of the country. Region 7 includes stations Hamedan, Yasouj, Ilam, Khorramabad, Arak, Hamedan Nojeh, Kermanshah and is Saqez.
Seasonal investigation showed that the coefficient of variation of rainfall in the winter when precipitation system of the country to reach their maximum value and almost all parts of the country are included and have appropriate uniformly distributed rainfall. Coefficient of variation of summer, the rainy season in most areas of Iran has been discontinued, the reason why the coefficient of variation All areas have reached their maximum value. The coefficient of variation region1 declined to the central regions of Iran. By comparing rainfall areas in terms of spatial and temporal variability in three decades, the study found that, compared with the average coefficient of variation of the second decade of the first and third reduction. What consideration is being discussed, the increase mean coefficient of variation third decade. By comparing the uniformity index of rainfall Region in three decades, was found that changes in rainfall zones 5 and 4 were unchanged in three ten-year period. average uniformity precipitation index (H) All regions showed that in the second decade, index H, has increased compared to the first decade, but declined in the third decade of this index. This indicates that the temporal distribution of rainfall Iran has experienced in the third decade of focus. In other words, most rainfall areas, Showery, short-term and focused and limited to certain times of the year.

Climate change is one of the crucial factors, which threaten many sector such as agriculture, water resource for decades, and the sector is more sensitive to climatic conditions. Communities are the most vulnerable to the adverse impacts of climate change and variability because of their low adaptive capacity. One of the challenges of climate change and human spatial dimensions of climate change in international borders where climate change, and creates special challenges. Populated places in the East where rapid urbanization, industrialization and agricultural intensification result in vulnerability to climate change, water shortages as the main concern arises.
Adaptation to climate change is the adjustment of a natural or human system to moderate the impacts of climate change, to take advantage of new opportunities or to cope with the consequences. Trying to identify the attitudes of people and their mental models of climate change can provide application to manage the post-change. Culture and engineering modeling approaches minds of scientists for climate risk management and climate change consequences have adopted. The review focused on farmers’ perceptions on changes in temperature, precipitation (rainfall), adaptation measures taken by farmers, barriers inhibiting these adaptation measures and the socioeconomic determinants of adaptations to climate change in Sistan plain.
The aim of this study is to provide mental system model, and understanding of climate change is to adapt these areas. To carry out this study to develop a theoretical framework for the model to adapt to climate change was discussed in Helmand. The field study was to assess the views of people on climate change action. The review found out that most farmers in this region are aware that the continent is getting warmer, and precipitation or rainfall patterns have changed. People with new changes and features adaptive approach to the challenges ahead were investigated. This data is based on knowledge (awareness) of water and climate change adaptation and mitigation strategies and be ready. So how compliance action is preventive in nature and to reduce the repercussions of climate change and the potential benefits of a region in the face of these side effects are formed. Most respondents aged over twenty years are at least a decade to climate change are felt to be most frequent subjects 30 to 40 years old. The data collected were processed using statistical techniques and modeling for ranking and evaluation of adaptation strategies were created and ASI index. The results for the insights, policy makers and service providers for local development is important, and can be targeted measures used and the promotion and adoption of coping mechanisms with the potential to build resilience and adapt to climate change and the resulting effects environmental prepare.
The results showed that most people in the region following the election of climate change is adaptive behavior. In total, there are 15 strategies in the region. The ASI index rating of strategies to change the pattern of cultivation, selection of resistant strains, reducing the amount of land-cultivated variety is the pattern of adaptation to environmental changes. Ensuring awareness of and adaptation to climate variability call was conducted with the cooperation of the people. Therefore, variability of climate and natural features of the area was measured by various options. The results show that already sampled respondents in the community are aware of climate change. 60% of respondents strongly observed signs of climate change and the dry season and low rainfall and warmer temperatures to believe. The main adjustment options adopted by farmers to temperature in the region include change of product types and number of ships that 61.6 percent of the farmers that their efforts. Another priority is that 39 percent of them tend to change sowing dates and planting varieties resistant to drought. The main recommendations for adapting to new circumstances in this region to stimulate the economy and livelihood of local people can be to diversify crop production (food for example, and cash crops, annual and permanent crops greenhouse) and the use of foreign income from farm sources (ecotourism, rural tourism) can be cited.

Blocking can be effective in Occurrence of damaging climatic hazards. In order to investigate the role of blocking in the event of heavy snowfall and persistent 31January 31 to5 February 2014, maps Average air pressure at sea level, 850, 500, 300, layer thickness map between 1000 and 500, the position of zero degree isotherm at ground level, U-Wind, V-Wind, Omega (Vertical Velocity, relative humidity, temperature and potential temperature are analyzed. The results showed that Iran is located influence strong and deep right, blocking trough of Omega has a very strong ridges width of 70 degrees north. With the falling of cold air from higher latitudes along with strong high pressure center located in the Caspian Sea with 1050 hpa pressure, With plentiful moisture and temperature conditions especially at the level of 500 and 850 hpa, Regarding the nature of blocking and quasi-stationary conditions continue for 6 days, most parts of Iran was accompanied with snow and some areas due to their position and other conditions were exposed heavy, sustained snow. Investigation the dynamic components showed that in adulthood blocking these components reached its peak and led to continuous heavy snow in most parts of the country. Identification blocking systems that led to heavy snowfall prediction using maps and issue timely early warnings can help planners and decision makers affected areas to prepare for and prevent further damage.

The more exposure to Climate change / variability¡ the more vulnerability and a community with low adaptive capacity and high sensitivity is more vulnerable. Vulnerability reduction depends on adaptation policy and strategies. Designing and assessing these strategies require climate vulnerability (CV) measuring. To produce a new CV index¡ as a main propose of this study¡ first: The score of exposure factor for two five span years was calculated based on four synoptic stations data (Zabol¡ Zahedan¡ Iranshahr and Chabahar). Second: The scores of adaptive capacity and climate sensitivity were determined using all of the country census and yearbook data for 1385 and 1390. Third: Due to the nature and factors of vulnerability¡ a climate vulnerability index was developed based on the multiplicative-exponential model (CVIMEM). Forth: The index was calculated for the province and sub regions. The result shows¡ although the Sistan and Baluchistan (SB) adaptation capacity was increased¡ but because of the increased exposure and sensitivity¡ this province is 16.3% more vulnerable. Area with very high vulnerability label expanded from 57.5% to 100%¡ which reflects the spatial expansion of vulnerability over SB. The overall result is that vulnerability reduction needs for accurate and continuous measurement¡ on the increase adaptation capacity and mitigate climate sensitivity.

In climatic studies، although the total amount of precipitation is an important factor for determining weather conditions and، finally، ecology، its seasonal distribution and، in other words، compliance with environmental needs، especially in agriculture، is significant، too. In this research، first، the aim was to recognize precipitation regimes at the province scale for each location in Kurdistan province; then the precipitation regimes were compared and، the basis type and classification of each were found on the map. Therefore، 83 synoptic، climatology and rain gauge stations data were used in this study for a period of 30 years (1978-2007). The statistical problem of stations was completed using the regression model relative to 30 years in the most homogenous station. To perform of this classification، first، monthly precipitation of each station was divided by the total precipitation for the same year in order to obtain relative precipitation in each month for the stations. After that، cluster analysis was used along with Ward technique and the classification of the precipitation regimes of the province was prepared. Based on this method، there were two different regimes of precipitation، namely winter and winter – spring precipitations، which were separately illustrated; the winter precipitation in west and the winter-spring precipitation in the center of Kurdistan province were dominate. The winter regimes contained 44% of annual total precipitation، which related to the winter season. After that، autumn and spring precipitations had 28% and، 27% annual total precipitation، respectively. In the winter-spring regime، more amount of precipitation occurs approximately equally or with a little difference of about 2% in winter and autumn، so that the winter and spring seasonal precipitation came up to about 36% and، 34% of annual total precipitation، respectively. After that، autumn season had 28% of annual total precipitation of this area.

Different local and temporal distribution of rainfall across the Earth has been amongst the determining parameters in many civilizations’ fate through history. Rainfall fluctuations and changes in climate phenomena are the monumental causes of these anomalies. Scientists have done a large number of researches to find the causes of the onset of widespread precipitation and its effects on agricultural crops، forecasting the onset of widespread rainfall، the teleconnection on widespread rain and the presentation of proper cultivation calendar for winter cultivation. Cold season brings about a great amount of widespread rainfall in many places in Iran. However، the basic consumption of water is during the warm season not only in civil but also in agricultural sectors. Therefore، being aware of the onset of widespread winter precipitation (OWWP) and its year to year fluctuations is a pressing issue. To examine and analyze the pattern of atmospheric circulation for the earliest OWWP، a 33-year period of rainfall data from 50 synoptic stations and one rain gauge station within four areas of Iran were analyzed. To find the early onset of the widespread rainfall، the average daily precipitations of all stations through each area were calculated. Furthermore، OWWR has two particular features per year. Firstly، the day having the higher standard deviation than the average rainfall of all the areas’ stations would be the onset day. Secondly، there should be at least two consecutive days having precipitation in more than 50% of all stations in the given area. As a result، there was a specific onset of rainfall for each area during 33 years. Moreover، if the OWWR in one year had started before the rainfall onset of that year، it would have been the year with the early onset. Consequently، the geopotential and vorticity maps of 500 and 1000 hPa showed the presence of a significant mridional component of atmospheric circulation in the earliest years with abundance of blocking highs and cut-off lows especially in the East Mediterranean and Iran. In addition، the anomalous positive relative vorticity in the earliest years lasted until the end of winter but the negative anomaly of relative vorticity showed the lowest amount compared with the other years. Finally، the result of Tukey’s test (HSD) showed a meaningful correlation (at 5% confidence level) between the OWWP and the total amount of rainfall in those above mentioned earliest years. In conclusion، 1974 in the northwest part، 1976 in the west، 1991 in the south and southwest and 1982 in the center and east parts of Iran presented the earliest widespread winter rainfall during those 33 years. In those mentioned years، the polar vortex had the highest positive anomaly and the high pressure of Saudi Arabia had its most optimal condition on the Arabian Sea which caused a wet year for Iran. Also in the mentioned years، heavy rain and flood have been seen in the semi arid areas of the East Mediterranean، Saudi Arabia and Sienna desert.

In order to evaluate the climatic potentials of Kerman province, the hourly weather data of temperature, relative humidity, and wind speed of the nine synoptic stations of the province were obtained for the existing data period( ranging from as early as 1957 to as late as 1993 up to 2005 to 2007). The hourly human comfort index of Physiological Equivalent Temperature (PET) was computed for each calendar month using the RAYMAN software. In the second step, the beginning, duration, and the end of the comfort period were determined for each station.
The results showed that the comfort period begins in January in the south and delays until March in the north. But it begins as late as April in the mountainous region of Baft. The comfort period ends in December in most of the province. The most uncomfortable climatic factor in the province is the temperature. That is why that the comfort period is shorter in the south than in the north. The length of the comfort period ranges from7 moths in the south to about 10 months in the north.

To model the relationship between three Geo-Climate factors of altitude, latitude and longitude and annual and seasonal precipitation in and Kurdistan Province, monthly data from 83 synoptic, climatology and pluviometer stations for a period of 30 years (1985-2008) were used. Statistical defects of stations in 30 years were completed with the most consistent station based on regression model. Model of choice for establishing this relationship was multiple-regression model using stepwise method of variables. Validity of models was also evaluated by testing four hypotheses of linearity of the relationship, lack of correlation of model errors; normality of remnants and constancy of variance of the remaining were evaluated. The results of implementation of this model on the annual and seasonal precipitation indicated the different combinations of each of these three variables on the spatial distribution of seasonal and annual precipitation. So that, the combination of the two variables of longitude and latitude, respectively justifies 69, 66 and 46% of spatial variability of autumn precipitation, annual precipitation and spring precipitation. The combination of the two variables of longitude and latitude explains about 63% of spatial variability of summer precipitation and combination of the three variables of longitude, latitude and altitude explains 47% of precipitation spatial variability in the winter.

Agricultural sector is directly affected by climate change, and certainly, the exacerbation of climate anomalies in the future, can threaten the supply of human food. Therefore, the agricultural sector can have the greatest impact on the phenomenon of climate change and also climate change will exacerbate drought and disrupt agricultural activity. Therefore, it is necessary to predict or simulate this effect using various available tools in the field of management, to ensure consumer food security and the maximum welfare of producers, with the necessary planning and policy making. The aim of present study was to investigate the viewpoint of farmers in Aligoudarz (Lorestan province) regarding climate change and the factors affecting it. For this purpose, a descriptive research method was used. The statistical population was Aligoudarz farmers and the sample size was 116, which were selected as random sampling. The questionnaire was used as the main tool for collecting data. Besides, the 30-year weather data were used to check climate change in the area. The results showed that more than 42% of the people have been familiar with the issue of climate change through the media including radio and television, and more than 60% of respondents have a negative attitude toward climate change. This topic was emphasized in more than 14 questions from the questionnaire.

Human life has been affected by the weather conditions. Since weather conditions may be favorable or adverse, human has tried to defend himself against climatic conditions through understanding the nature of the climate. These efforts led to the identification of the origin and how they were created. Such knowledge is also more accurate and more scientific.In synoptic climatology, by relying on the accepted principle of explanation and analysis of environmental changes of the earth surface through the changes of pressure patterns, it is possible to more explain, analyze, and forecast the climatic phenomena of the earth surface.One of the most important climatic disasters that threaten our country, are cold wave and sever freezing that in some years covers large areas of the country. Freezing usually occurs with the entry of the air masses of below zero degrees. These air masses accompanied with relatively stable and multi-day cold waves that may lead to adverse effects. For example, scarce and extreme cold of January and February 2005 in Iran, which has covered a wide and extensive part of the country. For synoptic explanation and analyze of the sweeping cold wave of Iran, minimum temperature of the stations within the province of Chaharmahal & Bakhtiari was selected and then the data of sea level pressure (SLP) & geo-potential height of middle level of atmosphere was select for explaining this event.

A synoptic method based on stream analysis is applied to understand the governing mechanism of summer rainfall occurrence in the south of Iran. Based on this, the rainfall data of 152 stations of Iran were analyzed for a 33-year period (1970-2002). Investigating the spatial and temporal distribution of summer rainfall, a typical rainy region is recognized in the south east of Iran. It is found that July 1994 had the greatest and most widespread rainfall during the study period. In order to understand the circulation patterns causing the summer rainfalls in the south east of Iran, 6-hour, daily and monthly mean values of geopotential height, specific humidity and zonal and meridional wind components of the different atmospheric levels were obtained from NCEP/NCAR reanalysis dataset. Using the abovementioned dataset, the geopotential height, streamline, vector wind and relative vorticity composite maps, the hovmoller diagrams and vorticity cross-sections are produced and analyzed. Also, the monsoon depressions track is drawn for July 1994 and summer monsoon intensity is determined for the study period by using the WY, OLR and AISMR indices. Finally, their relationship with the summer rainfall of the south east of Iran is analyzed. The result showed that there is a triangular area in the south east of the country located to the east of 58:30 E and south of 28:30 N which has rain almost every summer. It is also found that the monthly and interannual variation of summer rainfall over the south east of Iran is in close relationship with the variation of summer monsoon intensity over India. The most humid period in southeast Iran, July 1994, is associated with the increased summer monsoon intensity, increased monsoon depression numbers over west India and the positive rainfall anomalies over India. Additionally, the upper and middle troposphere subtropical anticyclones over southwest Asia were stronger and experience the considerable north and eastward propagation. Conversely, the cyclonic circulation of the lower troposphere was significantly stronger. The results revealed that the eastward extension of the Iranian subtropical anticyclone at mid-troposphere and the associated increase of anticyclonic circulation over northern India and Pakistan are followed by the westward movement of monsoon depressions and their entering the Arabian Sea. In this case, the monsoon depressions by creating or strengthening the convergence centers over the south and south east of Iran have an important role in increasing the cyclonic circulation and precipitation occurrence. It is also found that Iran low is the main factor of moisture transport and the rainfall occurrence of 1-10 July 1994 in southeastern Iran. The formation of this low pressure in the north of the Persian Gulf, in addition to the increase of positive vorticity over the area, is the key factor in 5-10 July rainfalls of south eastern Iran, by making suitable southern winds over southeastern Iran and transporting the Oman sea moisture in a thin layer to the study region.