مقالات رزومه دکتر زهرا حجازی زاده

By employing urban growth and development modeling, it is feasible to delineate a developmental trajectory that aligns with the specific circumstances of a city, considering environmental factors, natural elements, and population dynamics. The aim of this research is to propose an urban development model for Shushtar, which can serve as a valuable tool for analyzing the intricate processes of urban transformations. To accomplish this objective, two datasets were utilized: urban land use maps (including educational spaces, healthcare facilities, residential areas, etc.) and Landsat satellite imagery for key land uses such as rivers, barren lands, and forests, spanning three time periods: 1991, 2004, and 2014. These datasets were processed using GIS and MATLAB software. Existing urban land use maps were digitized and subsequently updated using Landsat satellite imagery. Subsequently, influential parameters in urban development were introduced as inputs to the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm. After training the model for the years 1991 and 2004, the predicted results of urban development using the algorithm were compared with the actual situation in 2014, demonstrating a high accuracy of 93.7%. The land use change map, resulting from the change detection process, can be generated based on multi-temporal remote sensing images and their integration with urban land use maps, enabling an analysis of the associated consequences. The use of intelligent algorithms in this research has facilitated modeling with a high level of accuracy. The obtained results are deemed acceptable, and this development has also been predicted for the upcoming years.

Spatial variations of pressure patterns under the influence of large-scale atmospheric circulation create different conditions in terms of the intensity of synoptic systems affecting on extreme climatic phenomena. Regarding large-scale patterns, not only the changes of extreme events are considered, but also the changes and developments of synoptic systems on a regional scale are studied. Weather extremes have a great significance for society, as they pose a threat to human life and can result in enormous economic damage and disruption. The physical understanding and timely prediction of extreme weather events are of enormous importance to society regarding associated impacts. Extreme precipitation events (EPEs) is one of the most frequent natural hazards that affects the domain, eventually leading to floods. Synoptic systems in mid-latitudes such as blocking, ridge and troughs cause spatial changes in westerly waves. Spatial variations of atmospheric waves occur when, which normally move from west to east, change their main direction to the north or south. The occurrence of precipitation in the Middle East is related to the changes in waves and the position of the Mediterranean trough. Extreme precipitation events in the Middle East often result from tropical-extratropical interaction, whereby midlatitude forcing and poleward transport of tropical moisture are of central importance. The Mediterranean Sea region is considered to be one of the most important and major areas for circulation in the Northern Hemisphere, so that most of Iran's rain cyclones are formed over the Mediterranean Sea. In other words, Iran's rainfall in the cold period of the year is influenced by the Mediterranean circulation patterns. Evidence shows that the large-scale atmospheric circulation over the North Atlantic plays an important role in the Mediterranean circulation changes. We investigated the effect of mid-latitude atmospheric circulation changes on the position of the Mediterranean trough and the occurrence of super heavy precipitation in Iran. In this research, two category of upper atmosphere data were used. The first is daliy precipitation data for 350 stations that were made available by the Iranian Meteorological Organization (IRIMO). The second dataset is the geopotential height, relative vorticity, potential vorticity, U, V-component of wind and Relative humidity, extracted from the European Centre for Medium-Range Weather Forecasts (ECMWF-ERA5) reanalysis with grids at 0.25×0.25 resolution. In this regard, 150 extreme and widespread rains were identified, then using the sinuosity index, the changes of the most frequent contours (550, 565 and 575 decimeters) during the precipitations were identified over the North Atlantic and Mediterranean. The aim of this study was to find the relationship between the spatial variations of the upper level waves over the North Atlantic and the Mediterranean (-80° W to 70° E, 10° N to 60° N). According to sinuosity index, the minimum sinuosity value is about 1 indicating zonal flow. Any sinuosity value greater than 1 indicates an increase in atmospheric waves. The spatial changes of the Mediterranean trough are due to the meridian changes of currents over the North Atlantic, Europe. The blocking system over the Atlantic was responsible for both the amplification of the downstream trough, as well as the formation and expansion of the trough towards the Eastern Mediterranean. The results show that extremely heavy and widespread rains occur under the influence of the formation of the Mediterranean trough and the expansion of winds from the European side and the strengthening of the North Atlantic trough. The results showed that the position and changes of the Mediterranean trough are associated with the circulation pattern of the North Atlantic. Multiple Atlantic trough are associated with each case of Mediterranean trough downstream. The formation of the Atlantic trough causes an increase in the range of atmospheric waves and the formation of a ridge over Europe and the development of the Mediterranean trough. Under these conditions the Mediterranean Sea experiences 8 longitudinal and latitudinal changes compared to its average. Therefore, the spatial variations of the Mediterranean trough are due to the meridian changes of the European flows and the expansion of the high north side (tropical side) downstream of the western wind. Simultaneously with the formation of blocking over Europe in its eastern part, the dynamic ridge causes the transfer of cold winds over the Mediterranean, which strengthens and expands the Mediterranean trough to the east. These conditions, with the strengthening of the conditions of ascent and eastward movement of the Mediterranean trough, the Arabian Subtropical Anticyclone (ASA) also expands eastward. During the heavy rains of Iran, by strengthening the conditions of ascent and eastward expansion to the Mediterranean trough, the ASA also expands to the east. Therefore, with the location of the ASA over the northern Indian Ocean, the Arabian Sea, and the Oman Sea, more moisture is provided to the atmosphere, which is accompanied by the intensification of extremely intense and widespread precipitation. In general, the position of the Mediterranean trough during heavy rains is such that the western and southwestern regions of the country receive most of the precipitation. These conditions are more severe due to the orographic factor of ascent caused by the Zagros mountains in this region.

The study aimed to explore land use changes and their relationship with the surface temperature using Landsat satellite images from 1990 to 2019. For this purpose, the urban land uses were classified and analyzed using 50 land sample positions from the visible composition of the Landsat  images using the supervised classification algorithm in the GIS. The results showed that urban lands had undergone significant changes. The surface temperature of the different uses using the glow temperature algorithm showed that free lands at 33.5°C had the highest temperature, while the lowest average temperature at 25.4°C was for the use of gardens. In terms of temperature variability, the gardens at 7.5°C had the most variable average temperature, while the water agricultural zone at 2.1°C had the lowest level of temperature standard deviation. The results of correlation analysis between temperature difference and land use change showed that the correlation coefficient between temperature changes and urban areas was 0.86 and 0.82 in the irrigated agricultural zone. Regarding the use of gardens, waste lands, and marsh areas, the correlation between periodic land use changes and temperature changes was more than 0.8, which is significant at the reliability of 0.95. But at the level of rangelands, rain fed agriculture and water zone, the correlation or significant connection were not observed at the level of confidence.

Global warming threatens human survival in today's scenario; and has become an environmental challenge. The climate data shows the warming trend in many parts of the world, which has led to a wide range of climate effects such as reduced precipitation, drought, and the occurrence of extreme events. The increasing vulnerability of many urban areas, especially in developing countries, has been one of the main concerns of life. Therefore, examining the risk of risks caused by global warming on a national and local scale is a fundamental step to increase the readiness of urban areas to reduce current and future risks caused by climate change. Droughts have effects on vegetation, soil and freshwater quality, and etc., and are a serious ecological problem around the world, its impact on crops and water availability for humans can jeopardize human life. Although drought has always been common, the drought risk has become increasingly prominent because of the climatic warming that has occurred during the past century. Therefore, these effects of are noticeable in all climates, and Iran, having a dry and semi-arid climate, is one of the countries that is always at risk of drought, and this causes great economic damage to the country every year.  in addition to this, the review of the history and climatic texts shows that the importance of the effects of climatic elements (rainfall and temperature) on the drought situation of the region in the coming period is essential. Until now, the study of global warming in terms of increasing the risk of drought using the sixth report and new climate data has not been studied in Tehran province. So this study aims to investigate the effects of climate change on increasing the risk of drought in Tehran province.

This research, First, the parameters (temperature and precipitation) for the synoptic stations (Abali, Shemiran, Mehrabad) for the period (1988-2020) were received from the Tehran Meteorological Organization. To projection in the future, down-scaling methods (SDSM-DC model) and The Mann-Kendall test were used to investigate the changes in temperature and precipitation. Climatic parameters change in space and time scale for many reasons. that these changes should be checked based on observations and statistical methods. Rainfall is one of those climate parameters that is not normal, and methods such as Menn-Kendall should be used to deal with such conditions; For this purpose, using Macro Excel, the value of age slope and Z statistic was calculated in the period (1988-2020) for the stations (Mehrabad, Shemiran and Abali) to investigate the trend of precipitation and temperature from the past to the present at a confidence level of 95-99% computed. In the following NetCDF data together with CanESM5 predictors from the base period (1979-2014) according to the most recent SSP release scenarios of the IPCC 6th Report were obtained from the Canadian Climate Change website. Among them, only Mehrabad station had a complete basic period compared to other stations, it was chosen as the selected station in Tehran. Drought indices are used as an index to track and quantify drought, this research is SPI index with DIC software has been used to evaluate the drought. in this index Precipitation, which has been one of its main components, whose output and results are more consistent with reality.

The results using the Mann-Kendall test showed that the examination of temperature changes in the stations (Mehrabad, Shemiran, Abali) was an increasing trend. Rainfall in most months of the year is a stable trend, only jumps are observed which can be justified by the increase in the frequency of rainfall. In the simulation with the CanESM5 model under the SSP5 scenario at Mehrabad station, the highest temperature was assigned to July and the highest rainfall will be in March. in this research, The drought survey showed that Mehrabad station experienced severe drought only during 1989-1993, while the duration of the drought period was longer in Abali and Shemiran stations and both of them faced very severe drought in 2014. in addition, this Investigation of three stations with a common period of 32 years in Tehran shows that Tehran has overcome the drought situation in recent years; But most of the time, the region may be in close to normal climatic conditions. But the risk of dry to very dry conditions will be very close. On the other, the results confirmed that drought depends on both rainfall and temperature.

As drought depends on both precipitation and temperature, The more the drought is accompanied by the trend of increasing temperature, decreasing precipitation, and the prediction of climate models, the more likely it is that climate change will occur due to global warming. As a result, the temperature of Tehran will increase. And while the rainfall is decreasing, it will be fluctuating and torrential. so In the future, Tehran's climate will have more fluctuations in rainfall and will be warmer than the current conditions. In addition, rains will occur more randomly but with more intensity. Tehran has had a drought in recent years, but most of the time the region has been in near-normal climatic conditions, but is the risk of dry and very dry conditions. This factor will create environmental challenges in the future. In addition to this, it is necessary to have a plan for climate risk management in the future due to the new climate of Tehran, which is prone to drought.

In examining natural hazards, such as hail, statistical analyzes can play a significant role. Due to the great importance of economic and side losses of hail in the northern part of Zagros with maximum frequency and damage, the necessity of studying its temporal and spatial location is felt very distinctly. Therefore, in order to estimate and estimate the probability of occurrence of this phenomenon, 10 hail data data of 10 synoptic stations of the region were used during the statistical period of 2014- 1992. In choosing the best method for calculating the distribution of precipitation probabilities, different types of probability distributions of discrete random variables were tested by means of both Kolmogorov and Anderson-Darling testsThe results showed that the good Poisson distribution test had a good fit for hail occurrence at a high level of 90.99%. Baneh station with the maximum frequency of hail precipitation has the lowest probability (0.023%) and Pearnshahr station has the most probable days without hail (0.39%). Therefore, the probability of occurrence of hail in Baneh has a higher percentage. In the next round, the negative binomial model satisfies the observations of this type of precipitation well. The calculation of probabilistic distributions by these two methods showed that the probability of occurrence of hail with the frequency of 1 to 6 times and more in the region and the highest probability is related to the frequency of 3 occurrences of 0.20%. At a frequency of 1 to 6 times, the probability of occurrence of this phenomenon is 5 times more than the probability that it will not occur, which indicates the region's high vulnerability to this type of climate risk.

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Evidence suggests that climate change will create uncertain regional agricultural production stability in the coming decades. This research investigated the impact of climate change on hydrology and sugar beet yield as one of the main crops in the Urmia lake basin using the Soil and Water Assessment Tool (SWAT). To address this, a baseline SWAT model was setup for 1986-2014. Afterward, the output was calibrated (1989-2004) and validated (2005-2014) in the SWAT-CUP software using the SUFI2 algorithm to simulate streamflow of 23 gauging stations and crop yield. The Nash-Sutcliffe efficiency was 0.43 and 0.53 for calibration and validation periods, sequentially. The Percent Bias was 45% and 16% for calibration and validation periods, respectively. As well as the agreement indices of 0.71 and the little Percent Bias (-6% to 10%) for crop production, verified the model's efficiency. The next step was downscaling and bias-correction of the precipitation and temperature data received from 3 climate models, namely GFDL, HadGEM2, and IPSL under RCP4.5 and RCP8.5 using CCT program. Then, the downscaled data were fed to SWAT, and Finally, hydrological fluxes and sugar beet yield were estimated for 2021-2050. Despite a dispersion of precipitation changes ranging from -12% to +35% in most scenarios, results highlight the pivotal role that the warmer temperature (+2.7°C) increases evaporation, resulting in sharpened pressure on water resources and runoff, especially, at the beginning of crop growth season. Finally, the negative impacts on crop productivity (-45%) is not unexpected. This means that sugar beet may suffer from climate change impacts, and the production of this plant will change over the next period in this region.

In this research, the sensitivity of the meteorological elements (such as mean temperature, relative humidity and wind speed) to different physical parameterizations in the numerical forecast model (WRF) was evaluated to simulate the climate of the city and adjust the Urban Heat Island of the study area.To study urban environmental issues, the Urban Canopy Model (UCM) was coupled to the WRF model. Several experiments were performed to achieve optimal configuration for simulation in the period from 18-21 August 2016 in the stable atmospheric conditions in summer. Selection of the most appropriate configuration with the least error is proposed as an appropriate setting for urban climate simulations and the study of Urban Heat Island (UHI). Increasing surface reflections to reduce UHI in the range was applied. Two indices of Root Mean Square Error (RMSE), and Mean Bias Error (MBE) were used to evaluate the predictive performance of the model and its corresponding observational values. The results showed that in the province of Tehran, in general, all configurations estimate the air temperature and wind speed less than real and relative humidity more than the actual value. In Alborz province, all configurations estimate the air temperature and wind speed more than real and relative humidity less than real value. By increasing the reflection of urban levels, the mean temperature of Tehran and Alborz provinces decreases 0.6 and 0.2 ° C, respectively. Wind speed, especially in urban areas, increases somewhat. We also see an increase in relative humidity (especially in urban areas) in the studied areas.

One of the patterns of major climate changes in tropical maritime regions is the Maden-Julian oscillation, which affects sub-seasonal time periods of 30 to 60 days, tropical and subtropical regions. This phenomenon brings the variability of various quantities of the atmosphere and the ocean, such as pressure, surface temperature, and the rate of evaporation from the ocean surface in tropical regions. In this research, first, the daily rainfall data of 48 synoptic stations, 1980-2020, was obtained from the Meteorological Organization. And quality control in three zero levels 1 and 2, including structural quality control, physical limits, correlation of parameters within the report, climatic range, temporal and spatial correlation, quality control.The Madden-Julian Oscillation is one of the large-scale climate change patterns in the maritime tropics, with subseasonal time periods of 30 to 60 days affecting tropical and subtropical regions. This phenomenon can cause changes in various quantities of the atmosphere and ocean, such as pressure, sea surface temperature, and the rate of evaporation from the ocean surface in tropical regions.In this research, the effects of Maden Julian fluctuation on the weather elements of Iran have been investigated with the aim of knowing the effects of different phases in order to improve the quality of forecasts and benefits in territorial planning. At first, the daily rainfall data of 1980-2020 was received from the National Meteorological Organization and quality controlled. Using the Wheeler and Hendon method, the two main components RMM1 and RMM2 were analyzed, based on which the amplitude of the above two components is considered as the main indicator of the intensity and weakness of this fluctuation. This index is based on the experimental orthogonal functions of the meteorological fields, including the average wind levels of 850 and 200 hectopascals and outgoing long wave radiation (OLR) between the latitudes of 20 degrees south and 20 degrees north. The clustering of the 7-day sequence with a component above 1 was used as the basis for clustering all eight phases, and by calculating the abnormality of each phase compared to its long term in the DJF time frame, the zoning of each phase was produced separately. In the end, phases 1, 2, 7, 8 were concluded as effective phases in Iran's rainfall and phases 3, 4, 5, 6 as suppressive phases of Iran's rainfall.Phases with a sequence of 7 days and a component above 1 were used as the basis for clustering all eight phases, and by calculating the abnormality of each phase compared to its long duration in the DJF time frame and by passing the data through the 30-60 day intermediate filter, zoning Each phase was produced in latitude 25 to 40 degrees north and longitude 44 to 63 east. With the investigations carried out and the output of the models and finally the production of zoning related to Iran's rainfall anomalies in the eight phases of the MJO, the country's daily rainfall data were analyzed in the period from 1980 to 2021, which finally after applying Data optimization filters, Iran's precipitation zoning output using Arc Gis software were produced separately for all eight phases. According to the outputs, the distribution of rainfall in the conditions of phase one can be seen with a variety of fluctuations, among which the share of rainfall and rainfall anomalies is greater in the southwestern and southern regions of Iran, especially in the regions of Fars, Hormozgan, West Kerman and Bushehr provinces. It is significantly different from other regions of Iran. In the region of the Caspian coast, the main reason for the rainfall is different from the rainfall in other regions of Iran, and it is not discussed in this analysis. Iran's rainfall anomaly in phase 2 has weakened compared to phase 1 of rainfall, and it can be felt that the anomaly is weaker in most areas. Iran's rainfall anomaly in Phase 3 of Madden Julian Oscillation has shown, we have significantly limited rainfall and almost locally. In phase 3, there is no rainfall in Iran, and obviously, with the beginning of the positive phase of the Madden Julian Oscillation, which includes phases 3, 4, 5, and 6, the changes in precipitation in Iran are different from the negative phases 1, 2, 7, and 8, and their changes can be considered in relation to each other.Eliminating the boundary between spatial-temporal scales and a deeper understanding of distant planetary systems is always an important challenge that the scientific community is facing. Undoubtedly, progress in medium-range and seasonal weather forecasting and our understanding of large-scale weather patterns and the identification of specific causes of their occurrence rely on our deep understanding of the behavior of atmospheric-oceanic patterns and their relationship with each other. to be Based on the direction of this research, the investigation of precipitation anomalies associated with the eight phases of MJO during the period of December, January and February 1980 to 2020 showed that the precipitation behavior of each of these phases is different from each other and the position, intensity and extent under the influence These abnormalities are variable in each phase.

Today, Iran is one of the most vulnerable countries to climate change due to its geographical and climatic features. One of the most important negative effects of climate change is the increase in temperature, which can increase the risk of wildfires. Wildfires are an environmental challenge and one of the threats to a large part of the forests in the world, including Iran. This study aims to investigate the effect of global warming on the increase in the risk of wildfires in Iran by using remote sensing technology and spatial analysis. 

The temperature data of the synoptic stations (Mehrabad, Yazd, Bam, Shiraz, Isfahan and Bushehr) in a 32-year period from 1988 to 2020 were first prepared from the Meteorological Organization. Then, Excel macros and XLSTAT plugin were used to check the temperature trend. To identify the vegetation cover, the Normalized Difference Vegetation Index (NDVI) was used from the Landsat 8 satellite with a spatial resolution of 27.84 meters, whose source of data was the Google Earth Engine. Then, the parameters of elevation, slope, aspect, and amount of solar radiation were used to calculate the topography. To identify the spatial distribution of fire occurrence, the kernel density estimation (KDN) was used by classification of areas into low-risk and high-risk areas based on NASA’s MODIS C6 satellite images (2000-2023).

The results of examining the temperature trend in all stations in the 32-year period showed an increasing and significant trend at 95 and 99% confidence intervals. This could be due the increase of greenhouse gases in urban centers, which is logical. The results of the NDVI showed that areas with high vegetation density were more susceptible to wildfires. Investigation of the solar radiation area showed that the northern highlands of Tehran, the banks of the Caspian Sea and northern areas of Iran, northwestern Iran (Ardebil and Tabriz cities), and central Iran (Kerman, Isfahan, Yazd and Shiraz cities) had a high pixel value, indicating that the amount of solar radiation was higher in these regions than in other regions of Iran. Finally, the spatial distribution map and the KDN showed that the provinces of Kohgiluyeh & Boyer-Ahmad and Khuzestan were more prone to a wildfires.

Iran has faced climate change caused by global warming. Considering the new climate of Iran, which will be hotter and dryer, it will be more prone to wildfires. Therefore, comprehensive planning to reduce the effect of climate change is needed in the field of crisis management in Iran, which can help reduce the vulnerability and increase resilience.

This article was written with the aim of revealing land use changes in Urmia city using remote sensing of Landsat satellite images for 4 periods of 8 years between 1990 and 2019. For this purpose, two categories of data will be used in this research. The first category includes data obtained from satellite images and the second category includes ground data taken from Urmia ground station, which includes temperature and other parameters used in this research. The results showed that urban land use in Urmia city has faced significant changes during the statistical period of 30 years. This user has had an increasing trend during all the studied periods, so that during the study period, it has faced a 5-fold increase. Swampy areas and sludge fields east of Lake Urmia have undergone a significant decline during 1990-2019 and has reached less than 6,000 hectares. The citychr('39')s barren lands, which cover a small percentage of the citychr('39')s area, have been declining over the 30-year period under review. The use of gardens has increased during all periods, so that in 2019, its area has reached more than 20,000 hectares. The use of irrigated agriculture has increased during all the studied periods and its area has reached more than 80,000 hectares by 2019. The area of ​​rainfed agricultural lands, after the rangelands, is the widest land use in Urmia, but with a relatively gentle slope has a decreasing trend. Water areas have also been declining, so that in 2019, it has decreased by about 26% compared to 2012. Rangelands, which is the largest land cover in Urmia city, has gone through three different processes during the study period. From 1990 to 1998, these lands did not change significantly, but from 1998 to 2005, the increasing trend and in 2019, with a 10% decrease compared to 2012, reached its lowest area during the statistical period under study, ie less than 20,000 hectares.

Development, as a concept, has been associated with various meanings, interpretations, and theories. Development is an evolutionary process whereby human capacity is increased to start new structures, solving problems, adapting to constant changes, and deliberately and creatively striving to achieve new goals. Forests are increasingly recognized as a key element for sustainable development and support several Sustainable Development Goals (SDGs), some of which include reducing hunger and poverty, regulating fresh water, climate practices, health and welfare, and biodiversity. One of the most important indices used to assess deforestation is the Normalized difference Vegetation Index (NDVI), which is used to assess forest change trends. The results of all studies that examined NDVI index will be questionable in the term of Sustainable Development Goals. This study investigates the trend of NDVI vegetation index during the period 2001 to 2018 based on the MODIS data in Malard city.

In this study, the MODIS vegetation data at a resolution of 1 km were used. The vegetation data, abbreviated MOD13A3, is monthly and with a 1 kilometer spatial resolution. This data covers 830 points for Malard city, so that it can be surveyed in 1×1 kilometers of 830 points in the city. Since based on research conducted by Farajzadeh et al. (2011:107), May to August have the highest NDVI, this index was extracted only in the highest NDVI months, ie May, June, July and August. The data were subdivided into three-year intervals and the rate of change was extracted based on the index introduced by the United Nations for sustainable development goals. Then annual land use was obtained for a deeper examination.in the final step we used an analytic-description method to describe the results in the connection with sustainable development goals.

The results showed that a decreasing trend was observed in the percentage of NDVI area in May, June and July between -0.03 and -0.9% in month. So that, under the maximum NDVI months, it was found that the amount of Barren increased about 9 km2 every 6 years and the amount of areas covered by forests and green plants decreased about 8 km2 every 6 years. Therefore, it is necessary to implement the measures and plans regarding prevent desertification in the city that will meet the goals of sustainable development

In recent years, attention has been paid to climate change, which could be the result of economic, social, and financial losses associated with extreme weather events. The purpose of this study is to investigate the variation of extreme temperature and precipitation in Kurdistan province. For this purpose, daily rainfall data, minimum temperature and maximum temperature of 6 stations were used during the statistical period (1990-1990). And their changes during the period (2041-2060) using the universal HadGEM2 model under two scenarios RCP2.6 and RCP8.5 and the LARS-WG6 statistical downscaling were investigated. In order to study the trend of climatic extreme indexes, rainfall and temperature indices were analyzed using RClimdex software. The results showed that during the period (2016-1990), hot extreme indicators have a positive and incremental trend. This trend is significant for the "number of summer days" and "maximum monthly of maximum daily temperature" indicators. This is while the cold extreme indexes had a decreasing and negative trend. This trend was significant only for the "cold days" index. Extreme precipitation in Kurdistan province has a negative trend in most stations. ،this trend is significant at most stations, that indicates a reduction in the severity, duration and frequency of precipitation during the study period. The results of the climate change outlook also indicate that the temperature will increase over the next period and rainfall will decrease.

With the increase of urban constructions and land use change, especially in big cities, the temperature of urban centers has increased compared to the suburbs, which has led to the formation of the phenomenon of heat islands in these areas. In fact, the heat islands of cities are closed isthmus lines that are known as the heat centers of the city, especially in areas built by humans and artificial structures. Since the purpose of climate studies in urban plans is to identify the environmental characteristics affected by the prevailing climatic conditions, so it can be of great help in optimizing the spatial structures. Climatic factors and elements in their quantitative and qualitative changes affect the environmental situation. Although these changes may be gradual and gradual, they can have lasting consequences. Therefore, the study of heat islands due to urban settlements has been considered by most researchers and its consequences for urban planning and global warming over the past decade have been considered with the expansion of urbanization and the occurrence of urban-related phenomena. The study of urban heat islands has begun in most of the most populous regions of the world.

In order to develop the present study, the OK numerical equation has been used. Due to the fact that numerical models can be programmed in the field of climate by certain conditions, so they use micro-climate scales in applications. Therefore, in recent decades, under the developed conditions of cities, numerical models have been widely used, among these models is the Oke numerical model, which compares the results of the observed data according to the numerical algorithm to analyze the formation of urban heat islands with Using a series of mathematical functions and fractions, they finally designed a numerical model to study the heat island in urban and densely populated areas.

First, the average height of buildings in the area was calculated based on Equation (3). Examination of the height of the blocks showed that the highest height is related to the urban block with 24 meters and the lowest height is related to the urban block with 5 meters. Therefore, by examining the height of urban blocks, it was estimated that the number of blocks with an average height of 10 to 12 meters is more, the number of these blocks is 99. Therefore, in areas two and six, most urban blocks have an average height of 12 meters, in other words, each urban block has an average of 4 floors. According to the classification of the average width of passages, out of 227 urban passages in the region, 123 passages have an average of 21 meters. Therefore, the maximum width of the passages in the area is 21 meters. Also, in the northeastern parts of the region (District 6) and the southwest of the region (District 2), the width of the passages has reached 26 meters, which is due to the location of these areas near the highways leading to these areas. In total, in areas two and six, most of the passages have an average width of 21 meters.Then the output of the Oak equation showed that the larger the ratio (H / W), the higher the heat island of the city (Table 1 Appendix). It can also be said that in most areas there was homogeneity between the height and width of the passages. The intensity of the heat island in the areas showed that the range is between 4-7 degrees Celsius, there is not much difference in terms of the intensity of the heat island in the whole region. The reason for this can be considered as proper planning and proper management in the field of how the buildings are located in relation to the width of the passages and observing the principles of urban planning. The results of H / W with UHI showed that if there is heterogeneity between urban blocks, the intensity of UHI will be higher at lower H / W coefficients than at higher H / W coefficients. That is, the greater the heterogeneity between the height and width of the passages, the greater the intensity of the UHI. Also, according to the following diagram, it can be inferred that in the studied areas, the low coefficient of H / W ratio has caused that most of the blocks have a homogeneous distribution and therefore the intensity of the heat island in the study area is not significant.

In this paper, we have tried to investigate the effect of urban geometry on the maximum intensity of the heat island, using GIS tools and the parameters of urban blocks and the width of passages. The OK numerical equation was used to investigate the intensity of the heat island. The results showed that urban geometry (height of urban block and width of passages) as two input parameters (H / W) affect the maximum intensity of the heat island of the city. In the second and sixth districts of Tehran, most of the urban blocks have an average of 4 floors (ie 12 meters). Also, the width of the passages in most areas of the region is considered in proportion to the height of the urban blocks. OKE equation simulation study showed that with increasing H / W ratio, UHImax growth is more significant, this result is somewhat consistent with the study of Gonzalez et al. (2011) and Osaki et al. (2011, 2018). Finally, the intensity of the heat island in areas two and six of Tehran's third district has not been felt, which indicates the proper configuration of the geometry of the buildings using the indicators used in the principles of architecture and urban planning in this area. Therefore, it can be said that this proposed model (OKE) can help to understand urban problems. Therefore, with proper planning and observance of urban planning guidelines by organizations and competent individuals in order to create better conditions, more targeted strategies can be adopted that can prevent the spread of the heat island phenomenon in large cities, including the metropolis of Tehran.

The phenomenon of climate change and global warming is one of the biggest challenges of the present age, which has affected the hydrological cycle on a global and regional scale. The purpose of this study is to investigate the effects of climate change on torrential rains And Temprature, Rainfall, Run off  in Tehran province. In this study, changes in torrential rainfall in Tehran and the frequency and intensity of torrential rainfall in the future and climate change and the rate of increase of floods on periodic floods have been investigated.

This research has been done in two study discussions (meteorological, hydrological). First, parameters (temperature and precipitation) for synoptic stations (Abali, Shemiran, Mehrabad) for the period (1988-2020) were received from the Meteorological Organization and rainfall and runoff data from hydrometric stations were received from the Tehran Regional Water Authority. Down Scaling model and methods in this research SDSM-DC, Mann-Kendall, Rclimdex, XLSTAT, to simulate future floods and SMADA, HEC-HMS model to simulate floods in current and future periods have been used.

The results showed that the temperature extreme indices in all stations had an increasing trend and the precipitation indices had an increasing trend only in Abali station. But rainfall in Shemiran and Mehrabad stations had a decreasing trend. Examination of rainfall changes using Mann-Kendall test in most months of the year shows a stable trend and jumps are observed in the rainy months, which can be justified by the increase in rainfall frequency. In the CanESM Model 2 simulation, emphasizing the RCP8.5 release scenario, an increasing temperature trend was observed for the coming decades. The highest temperature increase belongs to Mehrabad station with an average temperature increase of 5.1 percent for the period 2021-2083. The highest rainfall for all three stations is estimated in March next year. Therefore, with the increase of temperature trend, changes in the type of precipitation have occurred, which can be affected by urban microclimate. Simulation of the rainfall-runoff model of the basin with the HEC-HMS model showed that the volume of discharge in the future will be reduced by 5 percent and for return periods, the maximum discharge is estimated at 1501.7 cubic meters.

Due to Rainfall behavior is expected to increase in the coming decades, while reducing its fluctuations. It is predicted that the climate of Tehran in the future will have more fluctuations in precipitation and warmer than the current situation, and this increase and frequency of precipitation is likely to increase flood frequency and reinforce its occurrence, while rainfall will occur more accidentally but with greater intensity, leading to environmental and urban hazards.

The main aim of this paper is to determine the capable areas for cultivating pistachio through considering of Geo statistical Analysis the major effective factors. The necessary climatic daily data of weather stations For the 300 synoptic stations, the station was set up by 2016. The topographic data include relief, slope, aspect, and TIN layers extracts from 1:250000 topographic maps of the region. The maps of land use and vegetation land cover were prepared from the 1:250000 maps of national soil and water Research Institute. The spatial analysis facilities of GIS were utilized for numerical calculation and the spatial geodatabase of the region was established. Then spatial and description data was entered into the data bank. Finally by overlaying analysis in ArcGIS, cultivated area was classified according to its capabilities. The results showed that 707273/88 KM2 Of the area (43%), Not suitable for spreading pistachio cultivation (Including altitudes and urban use and steep slopes, seaside and riverside streams, shoals, saline and swampy lands) and 585130/39 KM2 (35/57%) From the country of Iran Area Including plain areas and agricultural use) was recognized as suitable for the expansion of pistachio cultivation. These areas are located in the east and south east, center and northeastern Iran.

Land Surface temperature is an appropriate manifestation of energy balance in the surface and greenhouse effect; because key parameterization in the physics of land surface processes is on a regional and especially global scale. It has been almost two decades since the MODIS sensor measured the surface temperature. Analysis of Land surface temperature (LST) Variation can help us understand the behavior of this key metering meter. The purpose of this study is to investigate the trend of land surface albedo in Iran. For this purpose; The Land surface temperature data of the Modis Terra sensor (MOD11A1) was used daily for the period 1379-1389 at a spatial resolution of 1. 1 km. After extracting the data in Iran, the Land surface temperature trend of Iran in 1884077 cells was examined using the Mann-Kendall test. The results of this study showed that in all seasons, increasing and decreasing trends in Land surface temperature are observed; however, the largest range of increasing trends of Land surface temperature in winter can be seen in January, February, and March. The results showed that in winter, the most significant increasing trends are seen in the heights, which can be related to the reduction of snow cover and reduced albedo in these areas. Using the digital elevation model of Iran, the Land surface temperature trend was calculated at altitudes of 100 meters, which showed that in January month, all height levels have an increasing trend in surface temperature, which is significant at the level of 0.05(the 95th confidence level).

The main sources of albedo change are variations in snow cover, variations in soil moisture, droughts, and variations in vegetation phenology, forest fires, and land use/ cover changes directly related to human activities, such as deforestation, irrigation, and urbanization. Forests obtain lower albedo values than shrubs, dry crops, grasslands, and bare soils. As a result, the conversion of forests to these land cover types leads to increases in surface albedo. This potentially has local and regional feedback, since an increase in surface albedo leads to a reduction in net radiation, turbulent heat fluxes, convective clouds, and precipitation, leading to a drier atmosphere Furthermore, black carbon decreases the surface albedo when deposited on snow and glaciers because it is incorporated in snowflakes, darkening snow and ice surfaces and increasing surface melt. Aerosols like dust transferred into the atmosphere and transported by the wind into the mountains where it settles on snow and glaciers, reducing albedo and leading to enhanced warming at higher elevations. It is noted that even though precipitation is the main driver of variations in soil moisture, its impact on albedo is controlled by evaporation, soil type, irradiation, vegetation, and topography. The present paper aims to evaluate the spatiotemporal variations of white sky albedo in Iran. For this, daily Albedo datasets from Moderate Resolution Imaging Spectroradiometer (MODIS) from onboard Aqua and Terra (MCD43A3v006) were applied from 2000 to 2019 with a spatial resolution of 500 × 500 m. MODIS provides black-sky albedo for direct and white-sky albedo for isotropic diffuse radiation at local solar noontime. For this, daily white sky albedo datasets from Moderate Resolution Imaging Spectroradiometer (MODIS) from onboard Aqua and Terra (MCD43A3v006) were applied. One of the main applications of the principal component analysis (PCA) is climatic zoning which is a method of determining environmental changes in temporal dimensions. A plethora of studies have been conducted using principal component analysis in the field of climatology but little has been done in relation to the albedo variation. To the best of the authors’ knowledge, this study uses a technique that has not been applied in scientific texts related to Modis albedo data. The questions that we will address in this study include: what is the temporal-spatial behavior of white sky albedo in Iran? How many components explain the variation of white Sky Albedo? What factors will distinguish white sky albedo in Iran?

In this investigation, daily white sky albedo datasets from Moderate Resolution Imaging Spectroradiometer (MODIS) from onboard Aqua and Terra (MCD43A3v006) were applied for the period of 2000-02-24 to 2019-06-03 (7040 days) with a spatial resolution of 500 × 500 m. Among the various MODIS datasets, white sky albedo datasets were extracted. The daily white sky albedo was averaged over the 19-year period for each pixel inside the border of Iran. The size of this array was 7541502 pixel *12month. Long-term monthly and seasonal means were also calculated by the available time series data. In the next step, the PCA method was applied to analyze the spatio-temporal variations of albedo in Iran. PCA is a method to reduce the number of the data and convert them into several finite components so that these few components explain the largest amount of the variance. This procedure is searching for the variable with the largest amount of the variance in space (PCA was invented in 1901 by Karl Pearson , and it was later developed by Harold Hotelling in the 1930s. In this method, initial variables are converted into n principal components each being a linear combination of the variables. In this way, the first principal component has the largest possible variance, and the components afterward explain a smaller percentage of the variance. Principal component analysis leads to the analysis of space-time array into two time-array and space-array. In this case, it is possible to identify what important spatial patterns the primary data have and at what time periods each of these patterns has been active or inactive. Because the principal components are finite, the temporal and spatial patterns introduced by the first component are more important than the temporal and spatial patterns of subsequent components.

The long-term average of Iran's white sky albedo was calculated; The results showed that the average albedo of spring, summer, autumn and winter in Iran 14.99%, 16.06% , 15.53%, and 19.58%, respectively. The evaluated long-term mean white sky albedo for each season showed that the highest value had occurred in winter. The dramatic increase in this value was placed along the Zagros, Alborz, Sahand, and Sabalan Mountains which exceeds 90 to 100 percent in some places. In the next step, the temporal-spatial variations of white sky albedo values in Iran were analyzed using principal component analysis, and the results showed that the three main components are able to explain 97.7% of the data variation. The first component explains more than 73%, of the total changes, the second component more than 20.8% and finally the third component explains more than 3.9% of the changes.

Spatial analysis revealed that the values which are higher than the mean are places in highlands and mountainous regions of Iran, such as the Zagros and Alborz Mountains, Sabalan, Sahand mountains and Zard Kuh-e Bakhtiari, which are associated with snow cover Therefore, the first component was named as snow cover as the maximum variance of albedo was explained by snow cover. The spatial analysis of the second component revealed that higher values were placed in small areas across Iran including, Hajaligholi desert Gavkhuni wetland, Qom salt lake, Sirjan salt lake parts of Loot desert. In the second component, most of the cell's scores upper of average in Iran corresponded to areas covered with salt. As the maximum variance is explained with salt cover, therefore, it can be named as the salt land. Spatial analysis indicated that in very limited parts of Alborz, Zagros, Alam-Kuh Mountain , Sahand, and Sabalan mountains Kino Mountain values are mostly positive which is related to the glaciers (regions with appropriate conditions to keep the snow cover in most of the year) and is the origin of the seasonal or permanent rivers Therefore, according to the cell scores (upper of average in Iran) in the third component, it was found that these cells corresponded to the , so it was named as the glacier component.

One of the most important energy sources in the world is solar energy, which is a renewable resource and does not cause any damage to the environment. Which all of these features justify using it as a clean energy source and economically viable cost.. Due to the relatively large area of the Iran in low latitudes and relatively dry climatic conditions, in terms of solar energy utilization it uses excellent conditions. Solar power plants are considered as power generation and transmission networks whose is important that the location features of their construction sites are effective in reducing the risk of investing in solar energy. In this study, using geographic information system and fuzzy valuation method for the criteria and method of weighing (AHP), was considered the potential of the Kavir & desert region and Makran coast for the purpose of obtaining energy from the sun. For this purpose, were used the 14 criteria related to the climatic, infrastructural, and technical and physical conditions of the area. In order to overlap the fuzzy layers were used the usual operators, Gamma, Product and also the Sum Weighted Overlay operator to compare and present the appropriate result. Each of the operators has a different sensitivity to the fuzzy overlap of the layers. For this reason, was considered the Gamma 0.9 operator, due to the high sensitivity for building power plants with high electrical power generation and the Sum Weighted Overlay operator, for the construction of smaller capacity plants. In the overlay map, using the Gamma 0.9 operator, about 2%, and in the overlay map with the weighted operator, about 33% of the study areas were found to be very suitable for the construction of solar power plants.

Drought is one of the most complicated disaster, its adverse effects on dryland agriculture are more pronounced than other sectors.. The aim of this study was to investigate the drought situation in the Simineh river basin watershed at four stations Synoptic Bukane, Mahabad, Miandoab and Saqez conditions for moisture content of wheat dried grapes in the four years 2007-2010 were analyzed and analyzed to determine the drought stress on the yield of wheat from the 22nd to the 43rd week in the light of the growth and development of rain fed wheat in the region The study was conducted weekly using Palmer's Moisture Index (CMI).. CMI results indicate that in the period of grain filling between 20May and 15June, there is a negative moisture drought index (CMI), which indicates the effect of drought on the performance of the wheat field. Drying plant is in good moisture conditions, but the stations of Bookan, Mahabad and The midsection is tense and the amount of moisture in 2010 is negative in all stations and the area is in severe drought.

Climate predictions have been made in global, regional and local simulation, and climatic parameters have changed in terms of trends and models in climatology, futures studies are less visible in literature and climatology literature therefore environmental planning and futures analysis are an attempt to look at the long-term future in the field of climatology. Today, one of the most important challenges of the present and future is the increase in temperature and   is the lack of climatic comfort. The growth of Tehranchr('39')s metropolitan area, improving living standards, expanding urbanization and industry, climate change, and the energy shortage crisis are important. The survey forms were prepared by the climatologists and managers of Tehran and data analysis, futuristic techniques such as scenario for data analysis tool in this study was MICMAC software. have been used. In the research process, the most important key factors and drivers in relation to futures studies were identified in relation to the increase of temperature in the city of Tehran.Mini scenarios and a comprehensive scenario were defined in three cases: Improvement of the Micro-Climatic Conditions of Tehran City + Climatic Comfort of Citizens Lack of  good micro-climate in Tehran + low climatic comfort of citizens The lack of improvement in the micro-climatic situation in Tehran + the lack of climate comfort for citizens and increased energy consumptionAccording to the results of the study, the most important factors in creating a crisis of rising surface temperature can be the lack of attitude to the concept of micro-climate improvement and urban management.

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>

Increasing the concentration of greenhouse gases leads to global warming is a phenomenon called resonance phenomenon that has led to an average annual temperature of 0.74 ° C over the last century the Earth's surface to rise. Global warming is a phenomenon that many adverse effects on human life and affects animals. Find phenomena such as droughts and intensity of rainfall . What reduction - Increased occurrence of dust and Sylabha.nyz days of climate change caused by global warming in the world ultimately was. In this study, to investigate the phenomenon of global warming in the province using the usual methods of time series (moving averages, trend-factor equation Trendline) and Mann-Kendall test, the average annual air temperature changes over the period 2016-1988 to 8 stations synoptic meteorology (Ahvaz, Abadan and Dezful Bustan- omydyeh- Ramhormoz-Mahshahr-MasjedSoleiman)is examined. The results obtained indicate a significant increase in average temperature of the air at all stations in the province so that the selected stations during the study period (except station in Masjed Soleyman, rising at 5% level) show the significant increase in the level of 1% of the stations 0.107 and 0.097, respectively Vramhrmz take degrees Celsius per year, the highest annual rate of increase in temperature have had

The plant community in an area is the most sensitive indicator of climate. A visual comparison of climate and vegetation on a global scale immediately reveals a strong correlation between climatic and vegetation zones and this relationship, of course, are not co-incidental.  The main object of this study is to reveal the spatiotemporal association between climatic factors andvegetation Cover (NDVI) incorporate MODIS and TRMM product in Kohkiloyeh O Boirahmad province of Iran. So that the in this paer we use MOD13Q1  of MODIS product as NDVI layer for study area. MOD11A2 as landsurface temperature and 3B43 TRMM as meanmonthly accumulative rainfall for study area during 2002 to 2012 in 0.25° spatial resolution also were used as climatic factors. We use the correlation and cross-correlation analysis in 0.95 confident level(P_value =0.05) to detection the spatial and temporal association between the NDVI and 2 climatic Factor(LST and rainfall). The results indicated that during winter (December to March) the spatial distribution of NDVI is highly correlated with LST spatial distribution. In these months the pixels which have the high value of NDVI are spatiallyassociated with the pixels which have highest value of LST (6 to 14C°).As can be seen in table 1. Season the spatial correlation among NDVI and LST is so high which is statistical significant in 0.99 confident level  in winter. In transient months such as May, October and November,(temperate months in study region ) the spatial correlation among NDVI and LST is falling to 0.30 to 0.35 which is not statistical significant in 0.95 confident level. Finally in summer season or warm months including Jun to September, we found the minimum spatial association among the NDVI and LST.. In temporal aspect we found that the maximum correlation between NDVI and LST simultaneously appears and not whit lag time. The spatial correlation of NDVI and TRMM monthly accumulative rainfall was statistical significant in spring season (April to Jun) by 1 month lag time in remain months we don’t find any significant correlation between NDVI and rainfall.

The purpose of this study is to identify and detect changes in rainfall extremes as indicators of climate change in  Iran. To conduct this research daily rainfall data of 76 synoptic stations were used from 1986 to 2016. The results show that the trend of the number of days with heavy rainfall was about 7 percent of Iran's negative and 93 percent of it was not observed. The trend of successive dry days in 28% of Iran is a positive trend and 37% there is a negative trend. The wet succession days in most areas of Iran are not trendy. The trend of the total amount of rainy days is about 99% of Iran's negative range. The maximum  negative slope of Iran's annual precipitation was observed at Masjed-e-Soleiman Station with a slope of -8.26  and there is a positive trend in the Bandar-e- Anzali. The trend of very wet days is about 78 percent of Iran is negative and about 14 percent is positive and 8 percent of it is trendless. The trend of very wet days in about 70 percent of Iran is negative. The highest wet days are observed in Khorramabad with a gradient of 1.4 and the highest decreasing trend in Sarpol-e-Zahab with a gradient of 2.78. Also, in 22% of Iran's range, there is no particular trend. The trend of one-day' precipitation in about 47% of Iran's negative and in 47% is without trend and 6% of it is positive. The trend of the maximum amount of 5-day precipitation about 73% of Iran is negative and in 2% it is positive and 25% of it is without a trend. The slope of the decreasing trend in Fasa and Masjed Soleiman stations is -2.4 and -1.9 respectively

The purpose of this study is to establish a proper classification of atmospheric patterns related to hail events and their climatic characteristics in the Zab Basin. Therefore, station data (27-87-96-99 to 100 present weather codes) were used to capture hail from the 3 synoptic stations of the Zab basin over a 24year period (1992-2016). The NCEP / NCAR database data was also analyzed to analyze the circulation patterns of these events. Cluster analysis on sea level pressure data and geopotential height (500 hpa) identified three circulation patterns associated with hail precipitation. Including: 1. Strengthening Sudan's low-pressure system 2. Strengthening European and Siberian high-pressure systems 3. Locating the area east of the Mediterranean Sea. Then, by performing intra-group correlations between each day cluster that was most correlated with other days, it was selected as the day to represent the circulation pattern of that cluster and the basis of the research was analyzed. Keywords: Synoptic analysis, Northern Highlands, Mediterranean Nave, Hail precipitation, Zab Basin. Introduction Hail is considered one of the most important atmospheric hazards as a consequence of a thunderstorm that damages the environment every year . Hailstorms usually occur from the clouds of cumulonimbus and are often thunderstorms and generally accompanied by thunderstorms, especially in spring. In general, hail is the product of intense convection found in a thunderstorm. To analyze and predict the mechanisms of each climatic phenomenon, one needs to have a detailed understanding of the main components of its climatic systems. Compared to other countries in the world, Iran has a high rank in the crisis due to natural disasters due to its environmental diversity. As a result, of the 7 natural disasters in the world, 7 have occurred in Iran. According to the FAO (World Food Organization) report, Iran ranks 10th in the world in terms of potential and disaster potential. Given the varied weather conditions in Iran, hailstorms are common. The occurrence of destructive and severe hailstorms as one of the major natural disasters has been reported in many parts of this vast country, with damages in various aspects of economic, agricultural, transport, infrastructure and so on and so on. Hail damages are sometimes greater than hurricanes and hurricanes. Since hail in the Zab basin annually causes significant damages, especially in agriculture and livestock, the aim of this study was to investigate the synoptic patterns of hail in the Zab basin in order to reduce the damaging effects of this. The climatic phenomenon is on different parts Area of study The Zab Minor catchment in the southwestern province of northwestern and northwest of Kurdistan province consists of Piranshahr, Sardasht and Baneh counties and is about 2 km 2 Material and method In this study, an environmental circulation approach was used to identify the circulation patterns of the days associated with hail in the west of the country. In this study, the code of days associated with the hail of Sardasht, Piranshahr and Baneh synoptic stations (with the longest statistical period between provincial stations) was obtained from the establishment (1992) up to year 2016 from the Meteorological Organization of Iran and then according to the code. The intensity of days associated with the hail event was identified during the study period. To identify large-scale synoptic patterns of day-event hail phenomena, hectopascal altitude and sea-level pressure data from open NCEP / NCAR analysis data on daytime events ranging from 0 ° C to 120 ° C and 0 ° C to 90 ° N They were prepared. Also, to determine the moisture flux of hail event days, Schulz and Benacus moisture flux equation was used. Discussion and Conclusion The purpose of this study is to establish an appropriate classification of atmospheric patterns in relation to hail events and the climatic characteristics that cause them in the Zab Basin. Therefore, station data (27-87-96-99 to 100 present weather codes) were used to capture hail from the 3 synoptic stations of the Zab basin over a 24year period (1992-2016). Using the NCEP / NCAR Center data, it is possible to analyze synoptically and identify the circulation patterns that coincide with these events. Cluster analysis of sea level pressure and geopotential height data revealed three weak, moderate and severe circulation patterns associated with hail precipitation. Finally, in order to identify the most important systems, intra-group correlation was performed between each cluster, and the day that had the highest correlation with other days in one cluster was selected as the representative day of the circulation pattern of the cluster and the basis of this study was analyzed. In the study of the synoptic patterns of hail precipitation according to the obtained results, the model best justified the hail precipitation in the Zab basin. In the first model, which included low hail precipitation, we observed a contrast between warm and humid low-pressure Sudan systems and high-pressure European cold tabs on the study area. In the second pattern at sea level with the formation of a low pressure center on Iraq, this low pressure is reinforced by the development of warm and humid air through the Sudanese system and the formation of a high-pressure belt across the northern Iranian strip, which, with its rotation and rotation, drives cold air. The study area has provided conditions for frontalisation in the area In the third model, Sudan's low sea level is strengthened so that its tongues stretch to the northwest and northwest of Iran, which inject hot and humid air and create convergence conditions over the study area. The Siberian high pressure on the north of Iran is also at its peak, and its tabs and motions cause very cold air to fall over the study area, and in this case the very cold northern and warm southern humid conditions make for the front. The region has created instability and instability Previous research on hail precipitation or only the role of Sudanese high or low pressure northern Sudan in hail precipitation events has shown that hail precipitation in western Iran necessitates confrontation of air masses. The cold north is warm and humid south and the strongest hailstorms occurred when these air masses penetrated the study area at peak times and created conditions for overburden and instability with the help of high-level currents. They cause severe vertical motions in the atmosphere and, as a result, hail..