مسعود جلالی

To achieve the research objectives, two different databases with a common time period of 23 years (2000-2022) were used in this study: first, the 16-day composite MODIS NDVI (MOD13A3) products of the Terra satellite and second, the Standardized Precipitation-Evaporation-Transpiration Index (SPEI) database on a 12-month time scale. First, to obtain the type of drought, the SPEI index was classified into 7 thresholds. Then, according to the thresholds, a map of all 6 main watersheds of Iran was extracted, and to classify the vegetation type, 10 thresholds were extracted for the NDVI index, and the relevant maps of the watersheds were categorized into 5 vegetation types in the form of a map for each year. Then, to examine the relationship between the two SPEI and NDVI indices, Then, using the Pearson correlation test, the relationship between the two indices was evaluated in the average of the gridded data pixel by pixel, and the age slope estimator was used to estimate the rate of change. The results showed that the slope of the negative trend of the SPEI index, 264 months, is increasing in the range of most watersheds, so that the negative trend of this index is more severe in the southwestern regions (Persian Gulf basin and Oman Sea) and in the northern regions of the country (north of the central basin and the center of the Caspian Sea basin) and is statistically significant at a confidence level of 90%, so that the rate of decrease of its index reached -0.9 per decade. For the NDVI index, both positive trends (in the southern and southwestern regions) and negative trends (in the northern regions) prevail throughout Iran, and for basins with a significant trend, the slope of the change trend is (0.01 per decade).

Clouds, as one of the most complex and influential climate variables of climate system, are effective in temporal and spatial distribution of many climatic variables. On the other hand, since clouds have many spatiotemporal changes, therefore, investigating their behavior is very important. Therefore, the aim of the current research is to investigate and analyze the annual cloudiness cycles in Iran and reveal the obvious and hidden behaviors of its time series. For this purpose, daily cloudiness data obtained from the National Meteorological Organization during a period of 31 years for 30 stations were used. Then, the trend of the data studied by Sen Slope Estimator's nonparametric test at the 95% confidence level. The results of data trend analysis and their significance value indicate significant downward changes in 16 stations and significant upward changes in 3 stations and no significant trend was observed in other stations. In order to analyze the harmonics and extracting significant cycles, Spectral Analysis Method was used and the diagrams of periodogram at the 95% confidence level were drawn. The results show that stations including a significant cycle have the highest frequency and are mostly in the south, center, east and northeast of Iran and multi-cycle stations with less frequency are in the north, northwest and southwest regions of the country. Also, by calculating the variance contribution of each cycle, the largest variance contribution for the 14th harmonic and the highest return periods for cycles of 2-5 years with a probability of occurrence of 32% and cycles of more than 10 years with a probability of occurrence of 6% were obtained.

Drought is one of the phenomena of environmental hazards that occurs in most parts of the world but its manifestation is more in arid and semi-arid regions and also occurs over a long period of time and alternately affects human societies through negative effects. It causes problems for water and agriculture, followed by the economy. One method of assessing drought status is the use of Palmer Drought Severity Indicators (scPDSI). In this study, the scPDSI index has been used to study drought and wet season during the period 1979 to 2018. In this research, data with spatial resolution of 0.5 * 0.5 has been used. The results showed that the cities of Bojnourd, Maneh and Samolghan, Gorgan, Shahroud, Tehran, Qazvin, Arak, Hamedan, Kashan, Bandar Lengeh, Fasa, Bandar Abbas, and west of Khorramabad have experienced severe to moderate droughts; These droughts have covered Iran with 22.06% in spring and 20.12% in summer. In general, the results indicate that droughts occurred from low latitudes to 33.75 ° latitude.

In order to use solar energy optimally, the first step is to identify the amount of solar radiation. It is useful to use satellite data to identify the amount of solar radiation in any situation. Therefore, the aim of the current study is to investigate the time-space amount of net short wavelength solar radiation in Iran. Then, in order to check the time of the data on a monthly and seasonal scale, their graphs were drawn, and linear and polynomial regression were used to determine trends. In order to carry out this research, monthly radiation energy data in nc format was prepared from the FLDAS satellite model for the years 1982 to 2021. The result of the long-term linear trend shows that Iran has a stable trend to some extent, but its non-linear trend shows several alternating upward and downward periods. Also, for the spatial analysis of the radiation spread in Iran, zoning was done in the Arc Gis environment. The results showed that the maximum amount of radiant energy in June is 296 watts per square meter and the lowest amount is 101 watts per square meter in December. The highest coefficient of change occurred in January (6.69%) and the lowest in September (1.47%). Therefore, Iran has the same

 Clouds can be considered as one of the most complex and influential variables of the atmosphere system in forming of the climate structure of the earth. When the condensation process takes place at a higher altitude than the earth's surface, it creates clouds. Cloudiness represents the percentage of the atmosphere that is covered by clouds. Clouds, as one of the most complex variables of the climate system, besides changing the energy balance, are also effective in the spatial and temporal distribution of many climate variables. Clouds have a lot of temporal and spatial variability and can affect the climate through many complex relationships and affect the water cycle. The investigation of clouds holds great significance as they serve as the bridge between synoptic systems and the Earth's surface climatic conditions. Any alteration in cloud-related parameters can trigger a domino effect, influencing various other climatic variables. It's worth noting that Iran exhibits a lower average cloud cover of 26%, notably less than the global average of 50%. This places Iran in the category of countries with relatively minimal cloud cover.Hence, possessing insights into the atmospheric cloud cover conditions in Iran becomes imperative for early detection and management of hydroclimatic crises, particularly in the context of water scarcity and drought-related challenges.

In the current research, the cloud data of 93 synoptic meteorological stations of Iran have been used in the daily time period during the statistical period of 1991-2021. The amount of cloudiness is an estimate of the nearest octa (eighth) and values 0 and 8 are completely clear and completely cloudy, respectively. In the present study, Kolmogorov-Smirnov, Anderson-Darling and Lilliefors test were used to determine the normality of the data at the 95% confidence level for annual, monthly and seasonal scales.In the subsequent phase, we employed both parametric and nonparametric methods to discern trends within the cloudiness time series. The parametric approach involved a linear regression test based on the least squared error method, while the nonparametric method employed the Mann-Kendall test. These tests allowed us to identify data trends, accounting for both normal and non-normal distributions of cloudiness. Furthermore, we explored the interplay between cloud cover and spatial factors, namely latitude and longitude, employing Pearson's correlation coefficient. This analysis shed light on the relationships between these variables. Conclusively, we created a spatial distribution map depicting the extent of cloudiness across various stations. This mapping allowed us to dissect the temporal-spatial distribution of cloudiness, comprehend alterations in cloud cover, and investigate the contributing factors behind these changes.
 

The results of Normality Tests according to the Kolmogorov-Smirnov test showed that all the stations did not have a normal distribution however, during the other two tests, except Arak, Kashan, Sarakhs, Takab, Kahnuj, Ramhormoz and Ramsar, other stations had normal distribution. The tests to determine the trend based on the parametric linear regression test based on the least squares error method showed a decreasing trend in 44 stations and an increasing trend in 3 stations of Ardabil, Qom and Sarab. According to the non-parametric Mann-Kendall test, among the stations without normal distribution, Kahnuj, Ramhormoz and Sarakhs stations have a decreasing trend, and no special trend was observed in other stations. The relationship between the two factors of latitude and longitude with the cloudiness variable using the Pearson correlation coefficient indicates a negative relationship (-0.42) between the cloudiness variable and the longitude factor as the amount of cloudiness in Iran's atmosphere decreases with the increase of latitude. Hwoever, the relationship between cloudiness variable and latitude, a positive relationship (0.75) was obtained as the amount of cloudiness increases with the increase of latitude. The survey of the annual cloudiness map of the stations shows the highest amount of cloudiness is in the South, Southwest and East of Caspian Sea. The lowest amount of annual rainfall was in South and Southeast of Iran. The statistical analysis of annual cloudiness data in Iran showed that the amount of cloudiness in Iran is 27.5%. Examining the normal distribution of monthly and seasonal values indicates the non-normality of the data with the Kolmogorov-Smirnov test, but based on the Lilliefors and Anderson-Darling tests, the winter and spring seasons and the months of December, January, February, April and May had a normal distribution and the autumn and summer seasons and the months of June, July, August, September and October did not have normal distribution. Seasonal and monthly trend with linear regression method shows a decreasing trend in winter and spring seasons and cold months of the year. According to the Mann-Kendall method, there was a decreasing trend in the fall season and no significant trend was observed in the summer season.

The purpose of this research was to investigate the temporal and spatial changes of cloudiness in Iran. The results showed a decreasing trend in 47 stations and an increasing trend in only 3 stations and no significant trend was observed in other stations. Also, in monthly and seasonal scales results indicated a decreasing trend in all stations in the cold months of the year and winter, spring and autumn seasons. Examining the relationship between the spatial factors of longitude and latitude with the cloudiness variable using Pearson's correlation coefficient also indicates a negative correlation with longitude and a positive correlation with latitude, and this indicates a large spatial difference in the amount of cloudiness in the country. In general, it can be said that spatial factors (longitude and latitude) were internal factors in the spatial changes of clouds and climatic systems such as Siberian high pressure, sub-tropical high pressure, westerlies system and moisture from the seas of Oman, India and the Persian Gulf and sometimes the Red Sea as external factors were in the temporal changes of clouds. So, cloudiness was a variable that was directly related to other climate variables. Thus, cloud cover was a variable that was directly related to other climatic variables, and its decrease or increase causes the values of elements such as temperature, precipitation, and humidity to change. Therefore, studying this important climate variable and investigating its changes is very important and especially in the discussions of droughts and water crises, it has a special place.

Despite the fact that the snow masses in the snow-bearing mountains provide vital water resources for ecosystems and society, but they are sensitive to climate warming. With the occurrence of climate change in recent years, the amount of snow storage in the snow-bearing areas has decreased significantly. Snow plays an essential role in providing the world's water resources, climate and biogeochemical processes on the earth's surface. he global importance of snowfall is undeniable. Snowfall causes the earth's surface to cool. On the other hand, water from melting snow supplies the amount of fresh water needed by one sixth of the world's population. Snow also attracts tourists and strengthens the tourism industry. Recreational activities, including the skiing industry, attract billions of dollars of income during the year. The reduction of water resources resulting from snow melting has affected the amount of agricultural and garden production, as well as the volume of environmental water in the rivers. In the current research, the amount and trend of changes in the snow mass in the snow catchment areas of the Alborz and Zagros mountain ranges during a period of 42 years were studied. Zoning maps of water equivalent to snowmelt were produced using MERRA2 satellite model data and in the geographic information system environment. The results showed that the highest amount of water equivalent to snowmelt in January (14.15 liters per square meter) is observed in the central Alborz region to the northwest of Iran (Alborz) and the Zardkoh Bakhtiari region .

The expansion of the pole toward the tropical belt is thought to be due to climate change caused by human activities, in particular the increase in greenhouse gases and land use change. The variability of the tropical belt width to higher latitudes indicates the expansion of the subtropical arid region, which indicates an increase in the frequency of drought in each hemisphere. In order to change the width of the tropical belt of the Northern Hemisphere in the middle offerings, indices of  precipitation minus evaporation, wind vector orbital component, stream function, tropopause surface temperature, OLR, and SLP have been used. Findings showed that the expansion of tropical belt latitude with stream function to higher latitudes with 1° to 3° latitude and the effect of Hadley circulation subsidence has increased the amplitude of evaporation minus precipitation has shown that the fraction of precipitation minus evaporation 1° to 3° latitude geographically increased. The subtropical jet has increased the movement of the upper branches of troposphere from the Hadley circulation by 2° to 4° latitude, which can have a negative effect on transient humidification systems as well as on the amount of precipitation. The extension of the pole towards the tropical belt, which is a consequence of climate change and hazards, will lead to the displacement of the pole towards the tropical side of the river, thus providing dry tropical belts to the pole; Also, the long-wave radiation of the earth's output has increased by 1° to 2° latitude and has caused an increase in heat in the upper troposphere, which has increased the dryness and slightly reduced the clouds in the upper troposphere and also caused the tropical belt to expand to higher latitudes. Has been. In general, the research findings showed that most tropical belt indicators have been increasing since 1979.

Snow is considered as one of the climatic elements of water supply for life. Therefore, this study was conducted aimed to investigate the trend of changes in snowmelt in Iran and its impact on changes in the Mediterranean wave of westerly winds. For this purpose, we provided snowmelt and geo-potential height data of 500, 600, and 700 hPa atmospheric levels from the European Center for Medium-Range Weather Forecasts (ECMWF) version ERA5 with a spatial resolution of 0.25 * 0.25 ° for 1979-2019 January, February, March, April, November, and December. First, the trend and slope of monthly snowmelt changes in Iran were evaluated using non-parametric Mann-Kendall statistical tests and Sen.’s slope estimator. Then, using the percentile method, 25% and 75% percentiles of monthly snowmelt values in Iran were determined. The relationship between the changes in the Mediterranean wave of the westerly winds and the months with snowmelt values lower and higher than 25% and 75% percentiles was measured. Finally, the Middle East Synoptic Index (MESI) and decade expansion were used to analyze the impact of the monthly decreasing trends of snowmelt of the Mediterranean wave changes of the western winds in Iran. The results showed that in January, February, March, April, and December, the mean monthly snowmelt in Iran has a decreasing trend. In addition, a relationship was between the Mediterranean wave heights of the westerly winds in January, February, March, November, and December with the mean snowmelt of lower and higher than 25% and 75% percentiles, respectively. Also, the results showed changes in the height of the Mediterranean wave of westerly winds. It seems that these changes are among the factors affecting the decreasing trend of snowmelt in Iran, which is especially evident in the third and fourth decades (since 1999 onwards) in January, February, March, November, and December.

The results of the study showed that the correlation headley cell and subtropical jet on the atmosphere Iran at the level 200 hPa has a positive correlation with a value of 0.4-0.7 to 35 ° latitude and also regression analysis showed that in latitudes between 15 35 degrees north of the subtropical jet 1(m/s) is higher than normal, although in 2017 up to latitudes 30 degrees north showed an increase of 2(m/s), which had a negative effect on rainfall.

The relationship between Hadley cell and olr in the southern, southwestern and southeastern regions of Iran with a value of 0.4 and the Zagros and northwestern heights of Iran with a value of 0.7 and regression with a value of (w/m2) 0.01 more than normal.

It acts as a tangible source of heat in the middle Wordspehr and the heat is added directly to the middle Wordspehr and causes heating of the upper half of the Wordspehr.

Regression 2 to 1 is shown. Low relative humidity along with the dried air mass is located below the descending branches of the headley cell, which has ruled the drought conditions (-0/7) showed that it creates conditions for lack of rainfall and drought.

Proper land use requires knowledge of environmental power, and then knowledge about environmental capacity in management and economic planning, along with their protection, will bring economic growth and development. Therefore, there is a close and undeniable connection between the environmental capacity of an area and its function. The assessment of environmental capacity is based on the indicators appropriate to the type of zoning and mathematical rules. It aims to adjust the land use according to the region's characteristics to promote economic goals and preserve the environment.Climatic and natural conditions are essential factors in the production and determination of plant species, and land use depends on the quality of these factors. Parameters such as temperature, precipitation, and humidity are crucial for the growth and development of different trees, including the walnut tree. The walnut tree is deciduous, large and wide from the broad-leaved group belonging to the Juglandaceae family and the Juglans genus with 21 species. The quantitative and qualitative characteristics of the walnut tree, such as wood, bark, leaves, and kernels, make it possible to use it in various industries such as soap making, paper making, wood and furniture industry, oil wells, oil extraction, pharmaceuticals, medicine, and dyeing, nutrition, purification of heavy metals from water and cleaning of soft metals, bulking of adhesives, with commercial and economic purposes. Therefore, the planting of this type of plant in susceptible rural areas, according to the 20-year vision document, in which special attention is paid to non-oil exports, including agricultural products, its export improves foreign exchange earnings and the economic growth of the villages. Therefore, considering the forestry value (wood value) and the edible seeds, the creation of uniform orchards of walnut trees requires the assessment of the capability of the regions according to the environmental components. 

The research method is based on the objectives of applied research and is descriptive-analytical. In this research, the desired data was collected from the organizations and scientific centers of the Ardabil province from 2007 to 2020. Then, after collecting and sorting, digitization was done, and finally, the layers were combined with the fuzzy coefficient operator model. Furthermore, the final map was obtained in 4 categories: desirable, suitable, relatively suitable and unsuitable in the GIS environment.

Even though the high sensitivity of the walnut tree to maximum wind speed and temperature thresholds (during the growth period and at the time of fruit ripening), the temperature is not considered a limiting factor for the planting of walnut trees in the province villages. The study of the average relative humidity of the air indicates that except for the villages of Pars-Abad and Bileh-Swar, Ardabil, the rest of the places are favorable and ideal for the growth of walnut trees. The investigation of the rainfall situation in Ardabil Province showed that the experts should supervise the planting of walnut due to the inappropriate amount of rainfall in Sarein, Nemin, Pars-Abad, and Ardabil.Gardening at heights above and below sea level, such as Sablan, Talesh, Ghoshe-dagh, Bezghosh, Ag-dagh and Jalga Maghan mountains in Ardabil province, is a limiting factor in the planting of walnut trees. When planting at altitudes lower than 1500 meters above sea level, it is better to use species such as Chandler and Howard. For altitudes higher than 1500 meters above sea level, it is better to use Fernor species. The slope is not a limiting factor for the planting of walnut in the villages of this province, except in parts of Meshkinshahr, Ardabil, Khalkhal and Kausar. The final zoning map indicated that the areas with almost mild winters and dry summers, annual rainfall, relative humidity and moderate to good wind speed had a high potential for planting walnut orchards. According to the final map, of 17,824.6 square kilometers of ​​Ardabil province, 7,773 square kilometers are favorable areas (43.60 percent), 4,681.6 square kilometers are suitable (26.28 percent), 4,809.3 square kilometers are relatively suitable (26.98 percent), and 560.7 square kilometers are unsuitable (3.14 percent). Regarding geographic location, the ideal and favorable lands for walnut planting include the northern, central and eastern parts of the province, which includes 43% of the province.

Hail is a natural disaster for all people, especially farmers. Usually in the insurance industry to calculate the risk of hail damage in each area, the frequency of rainfall (in terms of days) and the average damage are used, which is statistically significant. Hail is one of the phenomena connected with thunderstorms that occur in unstable atmospheres with high humidity and in the presence of strong winds and with mechanisms that increase instability, and these conditions are affected by Local topography and climatology of air masses. Therefore, in order to obtain an overview of the spatial and temporal distribution of hail damage on agricultural products in East Azerbaijan province and to investigate the differences between different parts of the region in terms of this type of rainfall It is better to identify and introduce the cause of possible differences between different areas and the conditions under which this rainfall occurred by achieving zoning of vulnerable areas in terms of hail damage. Thus, by considering and emphasizing the strategy of natural risk management program, which is considered as a potential and a very serious role in aggravating and increasing the damage caused by natural disasters in the region, it is possible to predict and deal with hail and lead To control the injuries caused by this phenomenon.

East Azerbaijan is located in northwestern Iran between 36˚47' N and 39˚ 40' N latitudes and between 45˚ 3' E and 48˚ 50' E longitudes. East Azerbaijan with an area of 45261.4 square kilometers is located in the northwestern corner of the Iranian plateau, which has agricultural lands of about 1320 thousand hectares, which includes 7.47 percent of the country's agricultural lands. In this study, to investigate and analyze the losses of the agricultural sector due to hail, the statistics of losses of the Agricultural Insurance Fund for the statistical period (2010-2019) were used. Due to the fact that in many cases when the hail phenomenon occurs, its very small area and the limited number of synoptic stations, the occurrence of this phenomenon can not be seen and recorded. So the area to be recorded includes only a small number of these events. Therefore, in order to assess the damage caused by hail in the study area, the days when hail caused damage were extracted and examined from the statistics of damage caused by the Agricultural Products Insurance Fund. Then, spatial statistics, hot spot index and ARC GIS software were used to identify areas vulnerable to hail.
discussion and

According to Table (3), we see that the damage caused by this phenomenon on horticultural products in East Azerbaijan province is an average of 123.5 hectares per year, with Bonab city having an average annual level of 568.1 hectares and Ahar with 491.2 hectares and Tark with 476.2 hectares are in the next ranks. But in terms of damage to crops, it was determined that Qara Aghaj with an annual average of 1143.9 hectares has the highest level of damage and Hashtrood with 826.6 hectares and Ahar with 369.1 hectares are in the next ranks.In terms of the level of damage to the total crop and horticultural products during the study period, it was found that in the province, on average, about 262 hectares of the province's area under cultivation are damaged annually due to this phenomenon. The highest level of damage is related to Qara Aghaj section with an annual average of 1159.7 hectares, which includes 14.7% of the total hail damage in the study area, and Hashtrood and Ahar with 1057.9 (13.4%) and 860.3 hectares (10.9%, respectively). ) Are in the next ranks. In order to identify areas vulnerable to hail, spatial statistics and spatial autocorrelation techniques were used, and in order to ensure areas with high and low value clusters, the * Gi index (Getis - Ard GE) was used. The results showed that in agriculture, the values of positive spatial correlation are concentrated in parts of the south of the province, which is the most vulnerable area in the study area, the central parts of Charavimaq and Shadian, and in the garden sector, the values of positive spatial correlation in Parts of the northwest and southwest of the province are concentrated, and among these, the most vulnerable area in the study area is the central and Yamchi Marand districts.

The results of this study showed that the highest frequency of damaging hail occurred in May and the lowest frequency occurred in August. The results also showed that about 71% of the harmful hail in the study area occurred in the warm seasons, which coincides with the plant growing season in this area. In the period under review, the rainfall of harmful hail in East Azerbaijan province was on average between 09:00 and 15:00 (G.M.T) more than other hours, and in this 10-year period, the maximum rainfall occurred at 12:00.In the study of hot spots based on Gi* index, it was found that in agriculture and horticulture, high value amounts (positive spatial autocorrelation) are concentrated in parts of the south and northwest of the province, respectively. Examination of the total damage of agriculture and horticulture showed that high values (positive spatial correlation) are concentrated in parts of the south of the province, and the most vulnerable areas in the study are the central parts of Charavimaq, Shadian and Nazar Kahrizi. On the other hand, a region with less vulnerability in parts of the west of the province, especially the central parts of Osku, Khosrowshahr, Mamqan, Gogan and the suburbs of Azarshahr, corresponds to areas with a spatial distribution pattern with the highest significant negative spatial self-correlation and 99 Percentages (strong-cold-cold cluster) are concentrated. By examining vulnerable areas, we can point to the high area under cultivation in these areas, as well as the impact of local factors such as topography and altitude and external factors, including the entry of hail systems from the west and southwest of the province in its occurrence and intensification.

Hail is a natural disaster for all people, especially farmers. The Hail damage depends on the frequency and intensity of rainfall. Usually in the insurance industry to calculate the risk of hail damage in each area, the frequency of rainfall (in terms of days) and the average damage, which is statistically significant are used. Hail is one of the phenomena connected with thunderstorms that occur in unstable atmospheres with high humidity and in the presence of strong winds and with mechanisms that increase instability, and these conditions are affected by local topography and climatology of air masses. Therefore, according to the natural risk management strategy, which is a potential and very serious role in reducing the damage caused by natural disasters in the region, hail can be predicted and dealt with and led to control of the resulting damage. Therefore, in order to investigate the spatial and temporal distribution of hail damage on agricultural products of East Azerbaijan province, the zoning of vulnerable areas in terms of hail damage, the cause of possible differences in different areas and the conditions in which this rainfall is present, were examined.

East Azerbaijan is located in northwestern Iran between 36˚47' N and 39˚ 40' N latitudes and between 45˚ 3' E and 48˚ 50' E longitudes. East Azerbaijan with an area of ​​45261.4 square kilometers is located in the northwestern of the Iranian plateau. In this study, to investigate and analyze the losses of the agricultural sector due to hail, the data of the agricultural Insurance fund for the were useded from 2010-2019. In many cases the hail phenomenon occurs in small area where there are limited number of synoptic stations so the occurrence of this phenomenon cannot be seen and recorded. Therefore, in order to assess the damage caused by hail in the study area, the day's whit hail damages were extracted and examined from the data of the Agricultural Products Insurance Fund. Then, spatial statistics, hot spot index and ARC GIS software were used to identify areas vulnerable to hail.

The results showed that the damage caused by this phenomenon on Agricultural crops in East Azerbaijan province is an average of 123.5 hectares per year, Bonab with annual average 568.1 hectares and Ahar with 491.2 hectares and Tark with 476.2 hectares are in the next ranks. But in terms of damage to crops, it was determined that Qara Aghaj with an annual average of 1143.9 hectares has the highest level of damage and Hashtrood with 826.6 hectares and Ahar with 369.1 hectares are in the next ranks.In terms of the level of damage to the total crop and horticultural products during the study period, it was found that in the province, on average, about 262 hectares of the province's area under cultivation are damaged annually due to this phenomenon. The highest level of damage is related to Qara Aghaj region with an annual average of 1159.7 hectares, which includes 14.7% of the total hail damages in the study area, and Hashtrood and Ahar with 1057.9 (13.4%) and 860.3 hectares (10.9%, respectively). Are in the next ranks. The spatial statistics and spatial autocorrelation techniques were used identify areas vulnerable to hail, and the Gi* index was used to ensure areas with high and low value clusters. The results showed that in agriculture, the values ​​of positive spatial correlation are concentrated in parts of the south of the province, which is the most vulnerable area, the central parts of Charavimaq and Shadian, In the garden sector, the values ​​of positive spatial correlation are concentrated the northwest and southwest of the province, and among most vulnerable area in the study are in the central and Yamchi Marand districts.

The results of this study showed that the highest frequency of damaging hail occurred in May and the lowest frequency occurred in August. The results also showed that about 71% of the harmful hail in the study area occurred in the warm seasons, which coincides with the plant growing season in this area. In the period under review, the rainfall of harmful hail in East Azerbaijan province was on average between 09:00 and 15:00 (G.M.T) more than other hours, and in this 10-year period, the maximum rainfall occurred at 12:00.In the study of hot spots based on Gi* index, it was found that in agriculture, high values ​​(positive spatial autocorrelation) are concentrated in parts of the south and northwest of the province, respectively. Examination of the total damage of agriculture and horticulture showed that high values ​​(positive spatial correlation) are concentrated in parts of the south of the province, and the most vulnerable areas in the study are ​​the central parts of Charavimaq, Shadian and Nazar Kahrizi. On the other hand, a region with less vulnerability in parts of the west of the province, especially the central parts of Osku, Khosrowshahr, Mamqan, Gogan and the suburbs of Azarshahr, corresponds to areas with a spatial distribution pattern with the highest significant negative spatial self-correlation and 99 Percentages (strong-cold-cold cluster) are concentrated. By examining vulnerable areas, we can point to the high area under cultivation in these areas, as well as the impact of local factors such as topography, altitude and external factors, such as the entry of hail storms from the west and southwest of the province in its occurrence and intensification. The results of this study show the efficiency of spatial statistics techniques in identifying vulnerable areas and proper segregation based on the principles of spatial statistics and can be used as a model in other agricultural and economic sectors of the country. It is also recommended to study this index and combine the information obtained from spatial statistics with climatic information, studying the long-term impact of phenomena on changes in the pattern of hot spots and developing other spatial indicators in future studies.

Since the planet Earth acts like a black body like the planet, and always in a quasi-conditioned state, as much energy as it receives from the sun, it loses energy through long-wave radiation from the earth. The solar radiation absorbed on the ground is converted to heat; however, due to the reflection of the earth, the earth is not hot and hot. The energy reflection process by the earth is called earth reflection or long infrared wavelength, which is indicated by watts per square meter (w / m2). The low OLR values are related to the cloud at high latitudes, so that high values of the long-wave radiation of the Earth's output mean smooth skies and low values of the clouds. This indicator is also used to estimate rainfall in the tropical region. OLR calculations and estimates are a key component of the MJO, MNO, Negative and Positive Phases (ENSO), North Atlantic Oscillation (NAO), and also to study the assessment of weather indicators.

In the present study, in order to calculate the long-wave IR radiation, the OLR data from 1975-2015 were daily from NCEP / NCAR databases of the National Oceanic and Oceanographic Organization of the United States with a spatial resolution of 2.5 * 2.5 degrees longitude and 4-hour time resolution (hours, 00:00, 06:00, 12:00 and 18:00) were extracted and analyzed. In order to calculate the long-wave radiation of Iran, in the region of Iran's Earth's atmosphere (from 25 to 40 degrees north and from 42.5 to 65 degrees east), using Grads and MiniTab programming facilities, weighted earth integral Watts per square meter. First, the general characteristics of the long wave were studied. In this study, linear regression (VIA) regression methods were used to analyze the trend. In this procedure, the amount of variability of the long wave of earthquake is estimated over time. In the present study, in order to better understand the data and make a more accurate decision about the level of statistical confidence, the method of analysis of the Moran model was used; also, the Moran Model and GeoDa software were used to calculate and map the corresponding graphs. In order to calculate the Moran index or index, first the z and P-value points are calculated, and in the next step, the index is evaluated and significant.

The results of this study showed that the mean long wave length of Iran is 263/3 W / m2. The highest mean longitude of the Earth's longitude is due to latitudes below 30 degrees north, especially in the southern and southeastern parts of the country. Nevertheless, it was observed that more than half of the country's average surface longitude was greater than the average. The lowest mean radiation of the long wave of earth exits was seen as a belt from the northeast to the northwest of the country, but its minimum core is in the northwest and northeast. The lowest daily spatial variation coefficient of Iran's high-tide wave is seen in the southeast and southern coast of the country and in parts of the central and eastern parts of the country. Therefore, the geographic latitudes are higher than the mean long wave of the earth and the coefficient of spatial variation increases. Spatial Distribution The temporal and spatial variations of the temporal and spatial variations of the long wave of Iran's annual output in most areas of Iran have been increasing. The most extreme slope is the increasing trend (on average, between 0.8121 and 0.696296 watts per square meter) in the southern part of the southern belt of the Persian Gulf and the Oman Sea. In order to better understand the result of the temporal and spatial changes of the long-wave IR radiation to 4 periods of 10 years (1975-2015), during the first period, the total area of the country had an insignificant increase trend . Of course, in the second period, in contrast to the first period, most of the country's area had a decreasing trend, so that the areas that had a growing trend in the first period had a decreasing trend in the second period. Also, in the third period, again, in the second period, the majority of the country's area was incrementally and statistically insignificant. Of course, in the fourth period, the long-wave radiation of the Earth's surface throughout the southeastern region of Iran has been increasing and statistically insignificant, which includes 14.3% of the country's total area; but in general, during the fourth period, 96% of the country's area has a decreasing trend, of which 50.32% is statistically significant, and 43.53% are statistically non-significant. This suggests that in all four 10-year periods, I have had a photographic process at the outlet of the tidal wave in Iran. The results of the spatial distribution of the local Moran index showed that the long wave of Iranian outbound radiation in the south-east, south, and in the east and west of the region, consisted of a high cluster pattern with 47/60 percent of the country's land area. The cluster pattern regions of the north are drawn from the northeast to the northwest and include the northeastern, north and northwest regions of the country as well as the northern heights of the Zagros Mountains of the country. The spatial self-correlation model has a similar positive correlation with the pattern of spatial autocorrelation, with the difference that the spatial spatial dependence pattern of the second period is decreasing, while the positive spatial self-dependency model from the third period to the next It will slow down. Nevertheless, it can be said that throughout the course of the model, the spatial self-sufficiency pattern negatively affects the recent periods of decline and also the positive spatial self-correlation pattern with 0.75 percent ascendance.

In this study, the European Centre for Medium-Range Weather Forecasts (ECMWF) Version (ERA5) reanalysis forecast data with 0/25 * 0/25 spatial resolution and 40 years interval (1979-2018) from Vwind and Uwind using MATLAB, GrADS From programming in software in level 400-100hpa. Findings showed that the average vertical structure of jet stream subtropical northern hemisphere in summer is located in the northernmost latitude; And is observed from latitudes of 41 to 45 degrees north. In winter, it has shifted to the southernmost latitudes, and the subtropical core is more intense in winter than in other seasons. The seconds are observed at latitudes between 20 to 30 degrees north. This study polewaard that the jet stream of the northern hemisphere had two periods of increase during the years 1979 to 1997 in the amount of 1 to 2 degrees latitude also from 1999 to 2017 in the amount of 2 to 3 degrees latitude.

Changes in OLR can be considered as a critical indicator of climate change and hazard; studies have shown that since 1985, long-range radiation has increased the output of the Earth and is a cause of increased heat in the troposphere. This has led to an increase in drought and a slight decrease in the cloud in the upper terposphere, as well as an increase in Hadleychr('39')s rotation toward higher latitudes. On the other hand, clouds play an important role in the long-wave changes of the Earthchr('39')s output and are adequately evaluated at the global energy scale at all spatial and temporal scales.

Data and methods :

In the present study, in order to calculate the variability and the pattern of seasonal spatial dependence of the long-range radiation output of Iran, OLR data from 1974 to 1976 were daily updated from the NCEP / NCAR databases of the National Oceanic and Oceanographic Organization of the United States of America. To calculate Iranchr('39')s long-range output radiation, in the Iranian atmosphere (from 25 to 40 degrees north and 42.5 to 65 degrees east), using Grads and GIS software. First, the general characteristics of the earthchr('39')s long wave were investigated. To obtain an overview of the spatial status of the seasonal changes of the long-wave and its variability over the country, the average maps and coefficients of the long-wave variations of the earthchr('39')s output were plotted in the spring, summer, fall, and winter seasons. In this study, the slope of linear regression methods using mini tab software was used for trend analysis. Hotspot analysis uses Getis-Ord Gi statistics for all the data.

Explaining the results:

The results of this study showed that the mean of long wave in Iran is 262.3 W/m2. The highest mean long-range radiation output in spring, autumn, and winter is related to latitudes below 30 degrees north, especially in the south and south-east of Iran, with the highest mean in autumn and winter with wavelengths. High output 282-274 W/m2 as well as spring with mean W/m2 295-291 below latitude 27.5° C, which is in Sistan and Baluchestan provinces, south and southeast of  Fars. Hormozgan has also been observed; the lowest OLR average in these seasons is observed above latitude 30 ° N in the northwestern provinces with the lowest mean in the season Yew and winter with mean long wavelength output 213-225 W/m2 and also observed in spring with mean 226-235 W/m2 at latitude 37.5 ° C and latitude 44 ° N in Maku and Chaldaran Is. In summer, the highest OLR averages of 316-307 W/m2 are observed in east of Iran with centralization of Zabol, Kavir plain and Tabas desert as well as west of Iran in Kermanshah, Khuzestan and Ilam provinces, with central length The latitude is 47.50 degrees north and latitude 32/32 east in Ilam province in the city of Musian, due to desertification, saltwater and sand, as well as the absence of high clouds, indicating an increase in the frequency of earthquakes and It is a drought that will lead to shortage of rainfall and increased rainfall in these areas; the lowest average long-range radiation output in summer with W/m2 235-226 extends as a narrow strip from southeast to Chabahar and extends to the middle Zagros highlands in Chaharmahal Bakhtiari province and northwest areas in Maku, Chaldaran, Khoi, Jolfa, Marand, Varzegan, Kalibar, Parsabad, Ahar and Grammy cities. It has also been observed in the northern coastal provinces of Iran including Mazandaran, Gilan, Astara, Talesh, Namin. According to the trend of long-wave radiation output of Iran increased by 0.16 W/m2 and decreased by 0.37 W / m2 with increasing latitude. Seasonal trends indicate that 100 percent of the country has a significant increase in winter and no significant fall in autumn. 21.24% in summer and 18.35% in spring have no significant decreasing trend, which in south-east includes Sistan and Baluchestan, Kerman, Fars and Hormozgan provinces and 78.76% in summer and 81.65% in summer. Spring has a significant non-significant upward trend. The spatial dependence of the hot spots on Iranchr('39')s long-wave radiation at 90, 95 and 99% confidence levels is 45.49% in spring, 37.57 in autumn, and 44.55% in winter. The high wave radiation of summer is 42.2%, which is observed in north of Sistan and Baluchestan province with central Zabul and in east of Lot and Tabas desert and in west of Ilam province with central of Musian. But in spring, autumn and winter in the south and southeast of the country including Sistan and Baluchestan, Hormozgan, Kerman, South Fars, Bushehr provinces and in central Iran including Lot Plains, Desert and Salt Lake and Tabas sandy desert. It is also observed in western Iran in Ilam province, so that these areas correspond to the tropical belt at latitude 30 degrees north. This is due to its location in the subtropical region, the low latitude of Iran, especially south and southeast to central Iran including Lut Plain, Desert and Tabas Desert due to its proximity to the equator, the angle of sunlight is higher and perpendicular. Spun. The spatial dependence of cold spots on long-wave radiation at 90, 95 and 99% confidence levels in spring is 33.44%, autumn is 41.41% and in winter is 44.55%. Cold spots of long-wave radiation are 25.5% in the summer, located at latitudes above 35 ° N in the subtropical belt and include northeast areas in North Khorasan Province in the cities of Bojnourd, Esfarain, Jajarm, Mane and Semlaghan, Safi Abad and northern coastal areas in Golestan, Mazandaran, Guilan, and northwestern provinces of Iran including Ardabil, East and West Azerbaijan, Qazvin and Zanjan North Tfaat Kvh Hay Zagros includes the provinces of Kurdistan, Hamedan, Markazi, Qom, Kermanshah North East part. Minimum OLR cold spot with average output longwave radiation of 213 W/m2 220 northwest of Khoy, Maku, Chaldaran, Jolfa and Marand can be an indicative role for determining convective activity and dynamic / frontal precipitation.

In this research, coding the rainfalls, prepares daily 45 stations with the statistical period of 20 years to zero and one codes to realize the daily dry periods in west and north west of the country and then, by establishing the main condition of occurrence of code one for 30 stations, we extracted the dry 4 to 10-day frequencies. And the results gained of considering the atmospheric weathering, shows that the most clear rotational pattern in sea level is related to Siberia-Europe high-pressure panels and sometimes both of them that increase the rotation on the region and also, the local high-pressure reinforcement and there is a high altitude in atmospheric middle level which is derived from sample patterns and is placed on the studied region and these sample patterns are from omega, bi-polar and rex models that they are on Russia and Scandinavian countries with some changes. The 500 level TAVA and omega shows well that in most regions, the air course, has decreasing case and so, we can result that placement of a high altitude in atmospheric middle and upper level on the high-pressures of the earth, causes the weather stability and lack of rainfall and as a result, the stability and durability of these conditions for several days, is related to sample patterns.

the European Mid-Term Prediction Analysis version (ERA5) data with horizontal spatial resolution of 0.25 * 0.25 degrees and using From air temperature maps, wind vector orbital component, zero level wind vector orbital component at 1000 hPa, wind vector meridian component, wind speed component, meridional performance current function, long wave output of ground output wave for 40 years (1979-1979) and was done using Gardes and MATLAB software. The results showed that the Hadley cell is confined to the lower margin of the subtropics and is due to the density difference resulting from the thermal gradient between the equator and the pole. Due to the rotation of the earth and the Coriolis deviation, heat transfer Low geography is observed in the tropics and its descent is about 30 degrees north and 35 degrees south, and the wind component orbital component winds rise from the west to the east near the earth's surface and from the east to the west at the high level. The meridional wind, the air that ascends, moves in a meridional direction towards the poles, then subsides and reverses in its direction and moves towards the equator, causing the formation of a Hadley rotation. To be. In the Northern Hemisphere, the desert regions of North Africa, the Middle East, Iran, and the southwestern United States are mostly in the Hadley cell dynamic branch, with a relative humidity of 22% Also in the southern hemisphere, the regions of Australia and South Africa with 32% relative humidity.

In this study, the data of (ECMWF) version (ERA5) with spatial resolution of 0.25 * 0.25 degrees and a period of 40 years (1979-1989) of the meridional performance flow function Seasonal changes in the external edge of the Hadley cell in the Northern Hemisphere have been investigated using MATLAB. Findings showed that the outer edge of Hadley cell in winter from 35 to 38 degrees south, in spring from 29 to 32 degrees south, in autumn from 30 to 35.5 degrees South and can be seen in summer from 28 to 29 degrees south; Also, with increasing each year, the outer edge of the Hadley cell in winter, autumn, spring and summer increases by -0.039, -0.048, -0.014 and -0.012 degrees on average. In general, the results show that the expansion of the outer edge of the Hadley cell has increased by 2 to 3.5 degrees latitude in winter and autumn, and shows that it is very prominent compared to the summer and spring seasons. Shows the expansion of the Hadley cell rotation towards higher latitudes.

Human health is influenced by weather variables in all circumstances, including atmospheric pressure, humidity and temperature around them. Based on climate hazard and climate changes, different parts of human life and economic and social strategies such as health, hydrological pollutants And agriculture had a profound effect, including the discussion of the effects of thermal stress on human health over the last few decades, and has become a major issue in the world's scientific circles. Heat and cold stresses, the exposure of humans to extreme heat and cold, are part of the extreme events, often encountered by people during daily activities or in the workplace, and affecting human physical activities. It is important that, if the body is not cooled through transpiration or cooling mechanism, severe deaths are inflicted on human health; therefore, the person has to reduce his activity in order to reduce the adverse effects of heat stress. Hence, many researchers consider the thermal stress component more important than other components in assessing human health.
In this study, using the physiological equivalent thermometer of PET thermal stress assessment and zoning of human thermal physiological stresses in Iran, with the length of the common statistical period from 1959 to 2011, and for the arsenal of thermal physiological stresses of Iran Forty stations have been used as representatives of Iranian cities. To calculate the physiological equivalent thermal temperature, all the effective meteorological elements in the human energy bill are measured at an appropriate height of climate biology, such as 1/5 meters above the Earth's surface. Data on climatic elements are provided by the Meteorological Organization of Iran. In the absence of data for some courses, linear regression method was used to reconstruct these missing data. After calculating the indices, the frequencies were also monitored and finally, using the GIS technique, the Kriging method of the study area was based on the frequency of occurrence of the indicators. Therefore, in order to achieve the results and objectives of the present study, software such as SPSS for data normalization as well as missing data was analyzed and analyzed using Ray Man's model based on meteorological elements to calculate the equivalent thermal physiological temperature of humans. Also, using the GIS software and Ordinary Kriging method, the best interpolation method was used to zon the human cysiological stresses.
Today, in the planning of human health and comfort, the study of the physiological thermal stress plays an important role. In this regard, weather conditions can be used in the long-term planning of climate and in the short term planning of atmospheric conditions. In the present study, using the thermophysical Thermal Equivalent Thermal Index (PET), the climate climatic Atlas of Iran was prepared on a monthly basis. Calculated values for 40 stations in the country with a total statistical period of 52 years (1959-2011) were prepared. The results of this study showed that the spatial distribution of the physiological equivalent thermal temperature index in the country follows the altitudes, roughness and latitude. Accordingly, the low values of the indicator, which relate to the stresses of the cold, are consistent with the high and mountainous regions as well as the high latitudes, and vice versa, the thermal stresses occur in low and low elevations, as well as low latitudes, which of course, severe heat stresses occurred in the summer. Because throughout this season, the entire country of Iran is dominated by high tidal altitudes at high and low levels of ground pressure (1000 hp) with its warm and dry air, causing extreme heat and The term effects of heat waves on humans, heat loss, thermal contraction of the muscles and skin dryness, infectious or skin diseases, inflammation, sunburn, dizziness, fatigue, and mortality due to an increase in allergies can be mentioned. Significant differences in the environmental conditions of the mountainous masses of Kerman, Yazd and Sistan and Baluchestan provinces with their surrounding areas or low and low northern areas, and especially the Moghan Plain and Sarakhs plain, located in the upper latitudes of the country The issue is that the role of elevation in spatial distribution of the country's climate is much more colorful than factors such as latitude and longitude. The results of the analysis of the monthly thermal physiological stress maps showed that in terms of the area without tension, the march of the month with 47/8% of the area (778424/2km2) is in the first place and has the most favorable environmental conditions, The moon with 43/5 percent of the area (709275/2km2) is in the second position and also in March with 22.6 (359128/9km2) in the third, August and the last month. The highest thermal stresses (29 <PET) occur in August. In this month, 99/9 percent of the country has a thermal stress. The months of July with 90/4% are in the second, June and September respectively with 90% and 70% in the following ranks; Azar and Bahman, respectively, with 69 and 65/1% in the second and third places respectively have. The study of spatial variation coefficient of thermal physiological equivalent temperature index in different months showed that July with a change coefficient of 13/12% had the least spatial variation in the country, and in the month of January, the amount of these changes even reaches 55/55%. Also, based on clustering in Iran, there are twenty three distinct subfield thermal physiological stresses. The geographical dispersion of the territory of these tensile areas shows that the difference in Iran's thermal stress is mainly due to latitude and elevation. This difference becomes more apparent when we ignore the slight differences in these thermal stress areas and categorize them in larger groups. In this case, seven major physical physiological stresses are observed in Iran. The main thermal physiological stress regions differ in terms of seasonal stresses, while the subsoil physiological stress regions reflect differences in the received stress ratios on a monthly scale.

In recent years, groundwater level has been descending due to climate change as well as method and use of them, especially in arid and semi - arid regions. According to the United Nations studies, Iran is considered one of the countries facing a shortage of water. In terms of climatic conditions, much of the country is but arid and semiarid regions. Water Table level control using observation wells are the main source of information to investigate the hydrological changes in these areas. Due to the recent drought and water shortages on a wide area of the country, the importance and sensitivity of groundwater management is increasing. Predicting the Water Table level using mathematical and statistical models can contribute significantly to proper planning and decisions to provide long - term water supply. In this study, the level of underground water using the gradient network and the transfer function of Tangent has been tried. Because of recent decades, neural network model studies show the high capability of this model in exploring the relationship between data and the recognition of patterns. Coppola and al (2003) investigated the possibility of predicting the level of 12 observation wells in different climatic situations, using artificial neural networks, in an area near the Temba Bay of Florida. Their results showed that, in modeling of the waters of the limestone and karstic areas, neural networks performed appropriate performance. diacplous et al. (2005)conducted an investigation to predict 18 months of groundwater level to predict an underground water level in the Mesrar Valley in Crete, Greece. The results indicate that the lonenberg algorithm is the most appropriate model.

The recent multi - year drought in the province of hormozgan has resulted in the aggravation of drought conditions and the imposition of many problems on water resources in particular in the underground reservoirs in particular. Sarkhoon Plain plain is one of the areas close to the provincial capital of hormozgan. In this paper, prediction of the spatial model of the Water Table plain of Sarkhoon Plain plain using artificial neural network method and Hyperbolic rule is used to investigate the fault level of this model. in this study, the data of ten observation wells during the 25 - year period of 1990 - 1387 to 1392 - 1392 of the regional water organization of hormozgan province have been used. Artificial neural networks are one of the computational methods that utilize the learning process using called Nero, by adjusting the weights, using the input - output samples that are available. This model is subsequently used to estimate the output value for the new data. The weight of the hidden layer and the output layer are changed so that the error rate is min. This error is represented as follows.
(1) E = 1 / 2 [(y - O) ^ 2]The following algorithm is illustrated in order to train the neural network.η > 0 and E > 0After implementation of neural network algorithms with different neurons in matlab software, the results of predicting the water height of Sarkhoon Plain with Hyperbolic transformation functions were obtained to determine the best spatial model of different levels of groundwater depth, the soil water models were used. in order to choose the best extrapolation method in this study, eight methods were used and finally the model that had the lowest fault was considered as optimal model.

In this study, neural network model was implemented with different neurons to predict the level of groundwater level. After reviewing the evaluation criteria, the neural network model was selected as the top model with 40 neurons in the latent layer and with its extension to observation wells a spatial prediction model was obtained from groundwater level. The very low error and the high correlation of this model, from the results of the test data, shows its efficiency in predicting the level of groundwater level. Using this algorithm for data of ten wells, water height was predicted for twelve months of 1400 year. The results of this research have proved the superiority of neural networks to numerical models, This spatial model can be used to control the rate of water harvesting in different locations for sustainable water resources management, to determine the structure of input parameters of the neural network, the effects of drought periods and the effects of parameters such as rainfall, temperature and evapotranspiration in predicting groundwater levels.

In this study, neural network model was implemented with different neurons to predict the level of groundwater level. After reviewing the evaluation criteria, the neural network model was selected as the top model with 40 neurons in the latent layer and with its extension to observation wells, a spatial prediction model was obtained from groundwater level. The results of diacplous et al. (2005) showed the superiority of lonenberg neural network over other models that have sufficient layers of latent layers, while it seems that the use of multiple latent layers with multiple neurons in different models leads to error reduction and the choice of superior model selection. Toarimino, Chua
  and Sethi (2012) emphasize the short - term forecasts of groundwater fluctuations. They have used the parameters of precipitation, evaporation - evapotranspiration and water level in the neural network model. Despite the higher parameters, the absolute mean of their superior model error has been higher than the average model error of the present research. It is probably due to the low intensity of the hidden layer neurons as well as their short time ranges. The results of the study indicate that the use of a neural network algorithm with the number of static neurons cannot be a measure of the performance evaluation of a model. This spatial model can be used to control the rate of water Picked up in different locations for sustainable water resources management, to determine the structure of input parameters of the neural network, the effects of drought periods and the effects of parameters such as rainfall, temperature and evatranspiration in predicting groundwater levels.

They have investigated the long-term change of the Hadley cell rotation as an expression of the climate hazards associated with the global warming trend over the past half century. By placing most of the arid regions around the earth beneath the substrate branches of the Hadley cells, it indicates the expansion of the subtropical arid zone that results in a drier subtropical climate. Ultimately, this may lead to more desertification than existing boundaries, and the consequences for those areas whose climate is affected by these features are important to manage. In this study, the European Mid-Term Forecast (ECMWF) Version (ERA5) reanalysis forecast data with 0/25 * 0/25 spatial resolution and 40 years interval (1979-2018) from the output long wave radiation data Ground, sea level pressure, evaporation and precipitation, zero-level orbital wind, tropical jet, jet velocity curve, tropopause gap, and meridional flow function using MATLAB software to investigate Hadley cell rotation polarization in the southern hemisphere Been paid. Most of the Hadley cell rotation criteria have been increasing since 1979. Hadley cell latitude with sea level pressure criteria in summer, winter, autumn and spring 1 to 3 degrees latitude, evaporation minus 1 to 3 degrees latitude, zero orbital level 1 to 2 degrees latitude, tropical jet 1 Up to 3 degrees latitude, jet speed curves 1 to 3 degrees latitude The findings showed that with increasing each year, the width of the Hadley cell with the meridional flow function function increased by -0/032 ° C on average. Overall, this study shows that Hadley cell rotation in the southern hemisphere increased by 1 to 3/5 degrees latitude, and since 1999, the intensity of the increasing trend of Hadley cell rotation in the southern hemisphere has been more pronounced. The highest increase in the latitude of Hadley's cell rotation during 1999, 2001, and 2011 extended to a latitude of -33/5 ° C, showing evidence of the expansion of the Hadley cell's rotation toward the pole, increasing drought and water hazards. And it has the air ahead.

The aim of this study was to analyze the mechanism is precipitation Comprehensive Iran. For this purpose the daily precipitation data of 483 synoptic and climatology stations arranged. In this study, a comprehensive annual rainfall is said to have a minimum rainfall and above, 50% sequence coverage and have at least two days. Winter surround Iran on the condition of rainy days were extracted and examined. Then, to review and analyze the mechanism of atmospheric precipitation comprehensive synoptic and dynamic parameters such as moisture flux, vortices, ground level pressure, Geopotential, meridional and zonal wind component for the levels of 1000, 850, 700 and 500 HP studied and analyzed was. The results of this study showed that the widespread mechanism of dynamic and synoptic Winter country most affected by the composition of the atmosphere patterns such as the Mediterranean low pressure - low pressure core Persian Gulf, Iran, Central High East Europe closed low pressure, low pressure Urals - the Middle East, high pressure, low pressure Saudi Arabia - High pressure belt Europe and Siberia - Iran's low-pressure center. However most of the winter precipitation of moisture flux feed barley middle-Level interaction, particularly levels of 850 and 700 HP respectively. It was while change 500 hPa atmospheric dynamical mechanism is an important role in Iran's winter inclusive.

A large amount of water in the seas and oceans on the earth is concentrated and a large body of water, water, gases, aerosol particles and momentum exchanges with the atmosphere (big et al 2003:275). So, how patterns of atmospheric circulation, especially with the increasingly moisture flux patterns are consistent with pressure (ghaemi 1994:272). Various forms of water transfer in addition to the dependence on atmospheric general circulation in different time periods. In general, two types of moisture flux vertical and horizontal in the atmosphere are always combined with each other and only possible and under certain conditions the amount of them may increase flux horizontally by advection of air to carry moisture from the Evaporative to other parts of flux and vertical evaporative to transfer moisture from the surface into the atmosphere takes place in the vertical direction (Lindesay and. Dabreton 1993: 13). Transfer of water vapor in the atmosphere conditions are directly related to atmospheric circulation and changes in atmospheric circulation over time, the amount and the flow of moisture as well as altered. It pays to check the moisture flux convergence fact that wind is causing how much water vapor at different levels of the atmosphere(Masoudian and Mohammadi 2010: 47-70). In this study in order to investigate explores the convergence of moisture flux and atmospheric water precipitation in the spring rainfall, the researchers used two types of databases:Environmental data: environmental data is collected in two parts. Data is obtained in two parts, in the first part of 1460 seeking observations from daily rainfall synoptic and climatic stations and humidity and climate station 483 from 1340 to 1383 Esfezari database is used. The division of the distance is 15.15 km spatial resolution data is in the Lambert cone-shaped image are written. It has the cell density is 7187 cells throughout Iran. In order to increase the temporal resolution of the database daily precipitation observations from 1383 to the end of 1390 using the same method and the same spatial resolution, interpolation is added to the data base.
Then the database is used to determine the rainy day of three conditions:1 day which has at least 3 types of coverage in distance is a 2 mm and above have experienced at least two days to continue.
3 cover at least 50 percent of place.
2. The weather data: in this section to determine the flux convergence humidity and water precipitation rain sweeping spring of data, sea level pressure, water temperature, wind component zonal and meridional moisture, especially in heights of the database (NCEP / NCAR) dependent on the United States of America at the National Oceanic and atmospheric levels of 850, 700 and 1000 hPa is extracted. In search of moisture flux and the participation levels of water to provide humidity, precipitation in the spring of Iran or in other words in the convergence of moisture flux toward Iran fluctuations and changes observed is such that these variations in the levels of the sea, 850 700 hp with an intensity that has faced. In between the Arabian Sea, Persian Gulf, Red Sea, at 850 and 700 hPa as pronounced in flux, humidity, precipitation in the spring of and the Caspian Sea, in addition to providing moisture coastal areas in sea level of moisture sources Home rains of spring Northwest.
In this regard, the Mediterranean when the low pressure Sudan is activated by South Stream and East Mediterranean to the northern Red Sea moves and in accordance with flowing toward the south and southwest of Iran is shifted while the humidity of the Black Sea, because of systems and the presence of northern and northeastern Iran East side to side pass. Minimal role in flux rainfall events in the spring of Iran, especially in the south-eastern region studied the Indian subcontinent, and any time that the transfer of moisture from the Indian subcontinent and the Arabian Sea synchronized as can moisture precipitation in the southeast of the country meet. Thus it can be seen that between the Red Sea and Gulf of changes lower levels in the atmosphere, there is no coordination with the Arabian Sea and Oman. At the same time, the autocorrelation Space moisture in the country has shown that moisture values prized high autocorrelation high ledges in the spring in the coastal strip of the Caspian Sea, Persian Gulf and parts of the North West there; so that the least amount of change autocorrelation Space This study aimed to study the convergence of moisture flux and atmospheric water precipitation and identify sources of moisture in the spring precipitation has been Iran. For this purpose, the daily precipitation data of 483 synoptic, climatological and rain in a 50-year period (1961- 2010) is used. After extraction rainy days sweeping through cluster analysis patterns flux convergence humidity and water precipitation atmosphere of spring precipitation has been identified and then proceed to derive maps of sea level pressure, 850 and 700 hp with flux convergence humidity and water precipitation barley the study area is. pressure East, Turkey, Saudi pressure, moisture flux convergence of high pressure low pressure Siberian- Saudi Arabia, Sudan and moisture flux convergence of Siberian high pressure - Turkmenistan low pressure, low pressure Sudan. Most of the moisture content and moisture flux convergence of the Arabian Sea, Persian Gulf, Caspian Sea and the Red Sea and the Mediterranean and Black upper atmosphere at levels lower atmosphere.