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To conduct this research, data on monthly synoptic and hydrometric precipitation observations from the National Meteorological Organization and the Ministry of Energy were obtained for a 30-year period (1976-2005). To assess future changes in rainfall, historical data from the period (1976-2005) and simulated climate data from the period (2021-2050) using two models (CM3 and CSIRO-Mk3.6) from the CMIP5 series were used. These simulations were based on four scenarios (RCP2.6, RCP4.5, RCP6, and RCP8.5) with a spatial resolution of 0.5 x 0.5 using the BCSD method. A mean-based (MB) strategy was employed to correct any bias in the model outputs.  The results of the AOGCM models indicated that the CSIRO-Mk3.6 model had a lower error coefficient than the GFDL-CM3 model when simulating precipitation in the Large Karoun case. The average future rainfall (2021-2050) across the entire basin, compared to the average observed rainfall during the statistical period of 1976-2005, exhibited a significant decrease in both the amount and extent of precipitation in both basins for all models and scenarios. In the Great Karoun Basin, heavy rains were consistently concentrated east of the basin across all scenarios and models, with the central foothills experiencing the highest rainfall and the southwest and southeast regions receiving the lowest amounts.  The findings of this study estimate rainfall to range between 83-116 mm, with the highest rainfall expected in the Greater Karoun Basin under the rcp4.5 and rcp2.6 scenarios for both models.

Geotourism, as a sub-branch of nature-oriented tourism, has many potential capacities for the development of the land and the sustainability of natural resources. In this field, Khuzestan province has many scientific, historical and cultural structures that have high capacities to attract tourists. The purpose of this research is to identify the capabilities of some geotourism places in Khuzestan province and to investigate their importance in attracting tourism in the province. This research is descriptive and analytical, and library, documentary and fieldwork methods were used to collect data. After identifying tourism phenomena and landforms in the study area, the features of each geomorphological landform were completed through experts in the Prolong tables. The results showed that the highest average value of tourism in the province is Shadgan Wetland and Shushtar water structures with (0.66) and (0.63) respectively, and the lowest average value of tourism with (0.33) is related to the coasts of the Persian Gulf. be Shushtar water structures and Karun beaches have the highest productivity value (0.84 and 0.78) and Persian Gulf beaches have the lowest productivity of the study area with (0.12). . Therefore, Shadgan lagoon and Shushtar water structures and Karun beaches should be considered more in terms of investment.

Recently, global warming has become one of the most important topics of global concern. There is significant evidence that proves that most of this warming is caused by human activities. The purpose of this research is to calculate and estimate the carbon footprint caused by the consumption of fossil fuels and the green space standard for the control and self-purification of carbon dioxide in Ahvaz metropolis. In this research work, the data of fossil fuel consumption and green space per capita for the years 1396 to 1400 from the 1400 statistics of Ahvaz Metropolitan Municipality were used. To calculate the carbon footprint, the estimation method provided by Iran's Ministry of Oil (MOP) was used. The results showed that the per capita emission of carbon footprint from 2016 to 2018 was (2207717.06), (3293028.42), (2450152.42), (2607968.79) and (2949480.70) tons of carbon dioxide equivalent, respectively. It is that the highest footprint related to the year 2017 with 42.3293028 tons and the lowest footprint related to the year 2016 was 2207717.06 tons of carbon dioxide equivalent. The per capita calculation of the standard of green space also showed that Ahvaz metropolis faced a per capita shortage of green space during the studied years and the standard of green space for this city in the period from 1396 to 1400 was (883086/82), (1317211/37) respectively , (980060/96), (1043187/51) and (1179792/28) hectares and the largest per capita shortage of green space was in 2017.

By examining the trend of air temperature changes, it is possible to search for traces of climatic changes in the area of Iran. Temperature is one of the most important meteorological parameters that is used in many studies. This parameter is of special importance in climate change studies, as the increase in temperature is considered one of the most important human environmental issues. In this research, the purpose of the research is to look at the average temperature changes in the base and future period of Khuzestan province. The evaluation of the model and the reproduction of climatic variables and the perspective of the future climatic conditions are examined, and this question is raised: Is the Sdsm model in Khuzestan province highly accurate?

The area studied in the current research is the synoptic stations of Khuzestan province. In this study, meteorological data including the values of minimum temperature, maximum temperature and average temperature for the studied period have been used. In this research, we used SDSM statistical micro-scale exponential model for temperature prediction and 6 synoptic stations of Khuzestan province, which had 45-year (1961-2005) and 40-year (1966-2005) climatic statistics, were selected. The outputs of the CanESM2 climate model have been used under RCP2.6 and RCP8.5 scenarios. The data of the base period (1961-2005) were used for the first 30 years of data (1961-1990) for calibration and the second 15 years (1991-2005) for the syntactic evaluation of the model performance. Error and accuracy measures are evaluated.

MAE, NRMSE, RMSE, MSE and R2 were calculated based on the average values of the variables in each month. These values were obtained according to the daily temperature produced by the model and the observed values for calibration and validation data. The results showed that according to the NRMSE, the error rate in temperature estimation is acceptable (less than 10%) and is almost the same in all stations. The results showed that according to the high correlation coefficient of 87%, the performance of the model is confirmed. Finally, it indicates that the model has relatively good accuracy in estimating the climatic variable of temperature. In most stations, they overlap the most in the first months of the year, which is the reason for the accuracy of the model in the first months of the year. In the stations of Ahvaz, Bandar Mahshahr, Omidiye Aghajari and Bagh Malek in the first seven months of the year, the highest overlap and accuracy are included, and in the last five months of the year, the average retrospective temperature in these stations is 2.4, 2.4, 2.6 respectively. and 2.7 degrees Celsius shows the difference with the observational data. Dezful, Abadan and Shushtar stations have the highest overlap and accuracy in the first three months of the year and July. In the rest of the months, the average retrospective temperature in these stations is 2.6, 2 and 2 degrees Celsius, respectively, the difference with the data Shows observations. The temperature has increased in all periods and for the RCP2.6 scenario, it increases more than the RCP8.5 scenario. The highest RCP2.6 average temperature increase in Ahvaz is predicted to be 1.9 degrees and the lowest RCP8.5 increase is 0.2 degrees in Dezful and Shushtar stations. The average temperature in the forecast period with RCP2.6 and RCP8.5 scenarios is 26 and 25.7 degrees Celsius respectively, which shows an increase of 0.7 and 0.4 degrees compared to the previous period, and also the highest average temperature in the period Predicted with RCP2.6 and RCP8.5 scenarios and the observation period is approximately 28.2, 27.5 and 27.3 degrees Celsius corresponding to Shushtar station and the lowest average temperature is approximately 22.7, 22.6 and 22.2 degrees Celsius corresponding to Bagh Malek station respectively. In most of the studied stations, the increasing and decreasing trends of the observation and forecast period are similar. Aghajari station shows the most overlap. Shushtar, Abadan and Omidiye Aghajari stations have the highest temperature with an average temperature of 27.3, 26.5 and 26.4 degrees Celsius, respectively, and Bagh Malek station, which is located in the east of the province, has the lowest temperature with 20.9 degrees Celsius.

The most important results obtained from the performance evaluation of the SDSM model using statistical tests and various error measurement indicators showed that this model has been investigated in Khuzestan province and has the appropriate accuracy to simulate climate variables at the level of the studied region. It is absolutely necessary to evaluate the effects of global warming on the occurrence of climatic extremes. An increase in temperature has occurred in all studied stations in the coming period. In two scenarios, RCP2.6 (commitment of countries to reduce greenhouse gases) and RCP8.5 (in case of non-compliance to reduce greenhouse gases) were measured in the studied periods. Meanwhile, during the annual study period, the areas adjacent to the southern coasts of Iran will have the lowest temperature increase, so that the temperature increase in the stations located in the land is more than the stations in the coastal areas. The highest RCP2.6 average temperature increase in Ahvaz is predicted to be 1.9 degrees and the lowest RCP8.5 increase is 0.2 degrees in Dezful and Shushtar stations. In this research, the trends and types of seasonal changes have been investigated. The results obtained from the data analysis show that in all stations, in Khuzestan province in general, the average temperature parameter shows an increasing trend. Research has shown that the maximum temperature trend is an increasing trend in the base period of 1961-2005 and this trend will continue in the future periods. In the future periods, the temperature trend in the last few decades, the increase in the earth's temperature has upset the climate balance of the earth and has caused extensive climate changes in most areas of the earth, which is referred to as climate change. The minimum temperature is increasing, and as a result, it reduces the coldness of the air and moderates it.

Sustainable development is one of the key objectives of the tourism industry in any country, and this industry is influenced by economics, politics, and geography, with its development also impacting each region. Sustainable development in tourist areas accelerates the national development process through policies that preserve resources and the environment in each region. The aim of this research is to examine the role of urban policy in selecting top tourist regions and evaluating the criteria and capabilities of tourist destinations in the city of Mahshahr. The analytic hierarchy Process (AHP) model and a likert scale questionnaire were used in this research. Firstly, the questionnaires were distributed and their data were analyzed. After obtaining the compatibility of the criteria, the weights of each criterion and option were determined and then analyzed. The findings of this study indicate that among the factors of gravity, value, distance, and selected demand for tourism in the study area, the demand criterion has been assigned the highest weight (0.54) and the attraction criterion has been assigned the lowest weight (0.06) in tourism. Furthermore, the final ranking of selected tourist areas in Mahshahr has shown that bandar imam Khomeini and Aram Park Lake, with scores of 0/354 and 0/29 respectively, are ranked first and second in priority, while the historical city of Esk is ranked seventh in a lower position. Therefore, making informed decisions based on tourism criteria has a significant impact on economic activities, and the demand criterion has a more significant impact on regional tourism development.

Education, training, and upbringing are highly complex processes. As a result, multiple factors and elements are involved in its formation. The physical environment is one of the important elements in desirable education. By providing a suitable physical environment, students will engage in learning with better mental and emotional conditions and more tranquility.In this study, the bioclimatic conditions of Ahvaz city were evaluated using climate consultant software Based on the results of these indices, a total of 12 to 15percent of the training period hours were in comfortable bioclimatic conditions. In 45 to 50percent of the study hours, the climatic conditions were warm and undesirable for students, and in 30 to 35percent of the study hours, the air temperature was below the comfort threshold. Therefore, in more than 80to 85percent of the days when students are present at school, the temperature and climatic conditions are not conducive to their learning and comfort. In this 7 to 8month period, the number of hot and cold hours is approximately equal. However, since the undesirability of cold and discomfort conditions is less than that of hot undesirable conditions, and the cost of heating is lower than the cost of cooling, it is recommended to focus the study period on cool to cold months of autumn and winter. Based on the results of the bioclimatic consultant index, from 15 to 20days in the month of Mehr and from mid-Ardibehesht month, the thermal conditions exceed the tolerance threshold of students, and their health may be at risk. It is better to remove this period from the academic calendar. However, in other months of the study period, by considering appropriate strategies in the design and construction of schools, the climatic undesirability of this period can be addressed.

Global warming process is one of the most important climate changes of the current century that researchers have addressed in regional and planetary scales. Global warming and climate change is one of the most important environmental issues in the world. The phenomenon of climate change, especially the increase in the minimum and maximum temperature of the studied area, will be overshadowed. Finding the future climate of each climate zone and examining the system of their changes and examining the consequences of climate change can open the way for planning. In this research, the author tries to show a perspective of the conditions of climate change in the next 50 years in Khuzestan province, emphasizing the element of temperature.

The area studied in the current research is the synoptic stations of Khuzestan province. In this study, meteorological data including the values of minimum temperature, maximum temperature and average temperature for the studied period have been used. In this research, we used SDSM statistical micro-scale exponential model for temperature prediction and 6 synoptic stations of Khuzestan province, which had 45-year (1961-2005) and 40-year (1966-2005) climatic statistics, were selected. The outputs of the CanESM2 climate model have been used under RCP2.6 and RCP8.5 scenarios. The data of the base period (1961-2005) were used for the first 30 years of data (1961-1990) for calibration and the second 15 years (1991-2005) for the syntactic evaluation of the model performance.

According to the degree of correlation between the average temperature data and the predictor variable data, it has the highest correlation with the ncep_temp predictor variable, which is shown in graph (3) of the annual correlation between the ncep_temp predictor and the average temperature data. shows that the annual temperature in Ahvaz station is 96%, Abadan station is 95%, Dezful station is 94%, Shushtar station is 95%, Bagh Malek station is 88%, Bandar Mahshahr station is 94% and Omidiye Aghajari station is 95%. . The average temperature changes in the province is 25.7 with two optimistic and pessimistic scenarios with an increase of 0.4 and 0.7 respectively. Therefore, the trend of the temperature climatic element regarding the studied area and the future period is changing and increasing. In Khuzestan province, with optimistic and pessimistic scenarios, the frequency of heat waves increases by 2 and 1 days respectively. In the past period, in the northern regions of the province, Dezful station, Shushtar and the southeastern regions of Omidiyeh Aghajari province had the highest frequency of heat waves on average, 22, 19 and 18 days per year respectively.

.The most important results of its implementation are as follows: The results obtained from the data analysis show that in all stations, in Khuzestan province in general, the average temperature parameter shows an increasing trend. An increase in temperature has occurred in all studied stations in the coming period. In two scenarios, RCP2.6 (commitment of countries to reduce greenhouse gases) and RCP8.5 (in case of non-compliance to reduce greenhouse gases) were measured in the studied periods. Meanwhile, during the annual study period, the areas adjacent to the southern coasts of Iran will have the lowest temperature increase, so that the temperature increase in the stations located in the land is more than the stations in the coastal areas. The studies of temperature increase in Khuzestan province are aligned and consistent with the studies and researches of researchers such as Abbasnia (2016) and Ansari (2016). Because climate change can have an important effect on maximum and average temperature.The results of evaluating the performance of SDSM model using statistical tests and different error measurement indicators showed that this model is investigated in Khuzestan province and has a suitable accuracy for simulating climatic variables in the studied area.As a result, according to the monthly forecast for future periods, according to the existing scenarios, the results obtained are as follows:_ July is the hottest and January is the coldest month of the year in all studied stations of Khuzestan province during the forecast period.Research has shown that the maximum temperature trend is an increasing trend in the base period of 1961-2005 and this trend will continue in the future periods. Based on this, the consequences of climate change in the southwest of the country (Khuzestan province) have been calculated. it will reduce the coldness of the air and moderate it, and severe frosts will be reduced. The study of hot days zoning shows an increase in the number of hot days in the future climate period, among other results of data analysis in the future period. The number of hot days has increased and it is consistent with Pudina's studies (2014). Investigating the spatial behavior of heat waves in Khuzestan province. The results showed that there are high occurrences of heat waves in the east and northwest of the province. They are significant in terms of location, in Dezful and Shushtar stations located in the north of the province and Omidiye Aghajari located in the south of the province, they decreased by almost 2 days and in the rest of the studied stations, they increased by an average of 4 days, which according to the research of Esmailnejad (2004) approximately It is aligned and in recent years, this consequence has been frequent. In the last few decades, the increase in the earth's temperature has upset the climate balance of the earth and has caused extensive climate changes in most areas of the earth, which is referred to as climate change. The number of dry days in the future will increase in all stations. Currently, finding out about the amount of climate changes and the behavior of climate variables in order to apply the necessary measures against the effects of climate change has been discussed and the focus of attention of many researchers, especially climatologists. Recognizing and evaluating climate changes in the coming decades with the aim of proper environmental planning in order to adapt to future climate conditions and reduce its effects is an effective matter.

Climate change affects all sectors of the economy to some extent, but the agricultural sector may be the most sensitive and vulnerable. This phenomenon can lead to increased migration and heightened conflict risks. Today migration is a challenge for all developing countries. Climate migration and the occurrence of consecutive droughts in the Khuzestan province and the city of Ahvaz are also caused by rising temperatures and lack of precipitation, among other factors The aim of this research is to assess the capabilities for reducing migration in the city of Ahvaz and develop a migration strategy. In this study the SWOT model was used and questionnaires were adjusted based on the Likert spectrum and completed and analyzed with the opinions of experts. Initially in the first stage, internal factors, namely strengths and weaknesses, were identified, and in the next stage, external factors, namely opportunities and threats, were identified and weighted. Among the external factors, threats with a weight of )0.460)and among the internal factors, weaknesses with a weight of )0.440) had the highest weights assigned to them. The results showed that the strategic migration strategy for the city of Ahvaz is close to a minimum-minimum or defensive strategy. The main message of this article emphasizes the use of defensive and reduction strategies.This means that in this area weaknesses should be reduced and threats should be avoided. These weaknesses and threats are the basis for migration and hinder the sustainable development of Ahvaz.
 

Cloudiness is one of the most important climate elements that plays a major role in the rainfall and water balance of any region. In addition, the radiation budget of each region is largely controlled by the cloudiness and cloud characteristics of each region. Knowledge of the temporal and spatial structure of clouds in each region plays an essential role in planning and checking programs based on water and energy resources. The main goal of this research is to analyze the temporal-spatial structure of cloudiness in Khuzestan province using gridded data of ECMWF cloud database version ERA5 in Khuzestan province during the statistical period of 1990-2020. The cloud data for Khuzestan province in NC format was obtained monthly from the Copernicus integrated climate database, which included the height of the base or cloud floor, the percentage of sky cloud cover by the upper, middle and lower clouds of each pixel was 0.25 degrees of arc. . By calling the mentioned data in the ARC-GIS environment and spatial averaging by separating the cold and warm periods of the year, 30-year average maps of the warm and cold periods of the year were produced for the two factors of total cloudiness and cloud base height. On the other hand, the sky cloud percentage values were also calculated through spatial averaging in Khuzestan province for each year (1990-2020). The results showed that, firstly, in both hot and cold periods of the year, the northeastern and mountainous parts of the province had higher cloud cover than the plains and lowlands of the province. In the cold period of the year, the percentage of cloudiness of the sky varied between 25 and 60%, while in the warm period of the year, the percentage of sky cloudiness reached less than 5%. In addition, it was observed that in the province of Khuzestan, the highest share of cloudiness in the cold period of the year is related to the upper clouds (cirrus family including cirrus, cirrustratus and cirrocumulus with a height of more than 4 thousand meters). These clouds have a share of 25% in the cloud coverage of Khuzestan province during the cold period of the year. Meanwhile, middle clouds (alto family clouds including altocumulus and altostratus) have a 16% share in the cloud cover of the sky of Khuzestan province. In terms of the cloudiness time series trend during the period of 1990-2020, despite significant annual changes in the amount of cloudiness of the province's sky, no significant trend was observed in the changes of cloudiness in Khuzestan province during the last three decades.

This research sought to assess the climate comfort conditions for tourism in Hamadan Province.

This applied study, conducted in 2023 in Hamadan Province, utilized climate data gathered from meteorological stations across the region. Key climatic variables, including temperature, relative humidity, wind speed, and atmospheric pressure, were collected from 2004 to 2018. The meteorological stations examined included Hamadan, Tuyserkan, Asadabad, Razan, Famenin, Nahavand, Qahavand, Nojeh, and Malayer. After gathering the data, the Stress Index, the Steadman-Tom Temperature-Humidity Index, and the Climate Potential Index were calculated and analyzed across various time periods, such as different seasons, to determine which periods and areas provided optimal climatic conditions for tourism.

The models revealed consistent patterns, including climatic homogeneity and stability, persistent cold in winter, variations in climate between spring and summer, and unfavorable conditions during winter. All three indices indicated that climate changes in the Hamadan region have been gradual, without extreme fluctuations, leading to uniform conditions within each season. This consistency across the indices suggests that, despite methodological differences, the overall findings regarding climatic and thermal comfort were similar.

Most meteorological stations in Hamadan report unfavorable bioclimatic conditions for tourism in January and February, with March also being suboptimal. The most favorable months for tourism in Hamadan Province are May, June, and September.

Investigating the climatic characteristics of different regions and determining the type of architecture of each region based on statistics and climatic data is an inevitable principle, the important factor in architecture is man and his comfort. This research was carried out with the objective of factors influencing the type of architecture and climatic zone in the city of Ahvaz. The research method is the library and field method. To collect information, library and documentary sources have been used, and for a better understanding of library sources, field research has been conducted in the study area. Cosine law and tcic software were used to analyze the data. The findings showed that the criterion of orientation of the building with a weight of (0.20) is the index of its subgroups, respectively, access with a weight of (0.46), the connection between adjacent buildings with a weight of (0.42) and the slope of the land with a weight of (0.38) are ranked third. has it. It is also a measure of sunlight with a weight of (0.243), whose sub-set indices are, respectively, sunny hours (0.40), radiation angle (0.39), average temperature (0.36), are in the first to third ranks. Ahvaz city has special bioclimatic conditions due to its location in a special geographical location, topographical conditions and atmospheric systems affecting the region. So that the extreme heat causes many problems for the residents of this city.

The most important pillar of a scientific and applied research is the statement of the problem, when a problem can be scientific and practical that creates a challenge in relation to the solution of the problem and clearly defines the purpose of the work, as well as the challenges that have arisen in relation to the problem in question, the researcher uses Simulation models can overcome one of the challenges and work as a source of information for climate researchers to use for future research. In this research, the statement of the present problem is the statement of forecasting the average seasonal temperature. What element is temperature, the answer to these questions and reasons, let's hypothesize against it, after formulating the assumptions, prepare climatic data of temperature of the study area and the neighboring stations of the area, and also specify the study area To start the work, using modeling (simulation) and comparison and accuracy of forecasting, he used two models by comparing and measuring the accuracy of their errors, because Temperature is a physical quantity, some of the sun's radiant energy is absorbed by the earth's surface and becomes thermal energy.This energy is expressed in the form of temperature or degrees. Among the different climatic elements, temperature and precipitation are of special importance to predict this. The important key climatic element, our goal is to examine the seasonal average temperature changes in the seasons and determine the seasonal changes with 95% and 80% accuracy using artificial neural network - Arima time series model, RMSE index, and also the models together Let's compare which predicts temperature changes better. So that researchers can use and test these models in future researches to predict other climate parameters and also the impactful consequences of seasonal temperature changes and climate elements such as relative humidity - evaporation and transpiration - industry - transportation - bridges and other infrastructures. Proper planning and management should be done in this regard. In the 21st century, climate change is considered one of the biggest environmental threats to the world. Changes in Farin's climate are estimated to have more negative effects on human society and the natural environment than changes in the average climate (Mahmood and Babel, 2014: 56). Based on the fourth report of the International Commission on Climate Change, which was published under the title of Climate Change Assessment Reports, the global increase in temperature and the occurrence of climate change have been confirmed by using the measured data of the surface temperature of land and water in the world (IPC Si, 2014: 32). The first effect of climate change on atmospheric elements is especially temperature and precipitation, then due to the relationship between atmospheric elements and terrestrial ecosystems, water resources, vegetation, soil and also human life will be affected by this phenomenon; Therefore, investigating the trend of atmospheric variables such as temperature is of particular importance (Abkar et al., 2013: 14).Temperature Some of the radiant energy of the sun absorbed by the effects of the earth's surface turns into thermal energy. This energy is manifested in the form of temperature or degree. Among the different climatic elements, temperature and precipitation are of particular importance. Although the main cause of temperature is the energy obtained from the absorption of short solar radiation on the earth's surface.Using artificial neural network and Arima time seriesThe purpose of this research is to model forecasting changes in seasonal average temperature in the study area of Al-Shatar city using artificial neural network and Arima time series model and to determine the measurement accuracy of neural network models and Arima time series model in forecasting average temperature changes and also The above simulation models should be used to predict the research of future climate researchers and be realized.The main goals of this research are to model and identify seasonal average temperature changes and the relationship of this key element with other climatic parameters of Al-Shatar city. In terms of seasonal average temperature changes and prioritizing areas with temperature variability.This part of the research has monitored and simulated the regression error of Lorestan stations (Alshatar-Broujerd-Aligodarz-Noorabad-Khorramabad-Poldakhter) in the time period (1998-2018) of the stations of Lorestan province with the temporal-spatial analysis of the RMSE index. The obtained results show that the indicators of the cold period of the year in the current situation in different areas (stations of Lorestan province) have had different trends, but the average temperature of the cold seasons of autumn and winter is an increasing trend, which results in the melting of the glaciers and snowfall. Rain is coming and this process is predicted for the next eleven (11) years. In general, the results obtained in this section have shown that the heat waves in the future will be more intense, sharper and more lasting than the current situation, and the highest temperature fluctuations in the autumn season, which is 81. Using RMSE = .003 and ME = .86, it is the artificial neural network that has the best efficiency and performance in Elshatar city station and predicts the average temperature better than the Arima time series model, therefore the artificial neural network model and Arima time series Both have 95% and 80% measurement accuracy. It is better to use these models and other machines in future research to predict the minimum and maximum temperature and other climatic elements. Because they have the best performance and efficiency in forecasting the elements, forecasting the average seasonal temperature can help to plan and manage, control evaporation and transpiration and other resources of the country and Al-Shatar city. It is summer and the least accuracy is in autumn and winter. Considering that the prevailing rain-producing air masses in Al-Shatar city leave the most seasonal changes in autumn and winter, it can be concluded that the most temperature fluctuations occur in the cold seasons of the year and the least fluctuations in The summer season occurs due to the deactivation of the rain-producing western wind, whose value is 33/. Is

Dust events are one of the most important and challenging environmental and climatic hazards of the whole country and especially of Khuzestan province. The main goal of this research is to reveal the role of changes in vegetation cover and soil moisture in the annual distribution of dust events in Khuzestan province. In this regard, 3 categories of data were used. The data related to station dust codes obtained during the statistical period of 2010-2020 for the synoptic stations of Khuzestan province on an hourly scale. The second set of monthly vegetation data was obtained from the NDVI product (MOD13C3) of the MODIS sensor, and finally, the moisture data of the upper 5 cm layer of the soil was provided from the SMAP sensor on a monthly basis. By analyzing the frequency of dust codes, the monthly frequency of dust events, the concentration and persistence of dust were investigated. By obtaining the spatial average values of the two moisture indices of the upper 5 cm soil layer and the monthly NDVI index, the correlation and relationship between the dust indices and these indices was analyzed. The results showed that based on the average period of 2010-2020, the period of 4 months from May to August is the dust peak period in the province. There are at least 11 days of dust in every month, and the concentration of dust is more than 2800 micrograms per cubic meter in the air, and the duration of the dust event in the province is at least 40 hours. The investigation of the moisture indicators of the upper layer of the soil and vegetation showed that, exactly in the province during the same dust peak period, the soil moisture of the upper layer of the soil reached less than 10% in a large part of the central and southern regions of the province, and at the same time, the vegetation index also In these sectors, it has reached less than 0.18. In addition, in this research, it was observed that the monthly changes in the moisture content of the upper 5 cm layer of the soil with a correlation coefficient of -0.88 have the greatest effect on controlling the dust concentration in Khuzestan province.

The present study aimed to identify and rank the factors affecting the selection of architecture and leveling of educational centers according to climate conditions using the ANP method. Library and field methods were used to collect data. Data collection tools were databases related to climatology in the Ahvaz metropolis. To weigh each factor, the opinions of experts and ANP were used. The factors were also ranked based on the weight of each factor. The results revealed that pollution prevention with a weight of 0.099, sunny hours with a weight of 0.099, and access with a relative weight of 0.096 had the highest weights among the obtained sub-indices. Thus, they were ranked first to third, respectively. Other sub-indicators were placed in other ranks based on the weights obtained.

Extensive and massive agriculture, along with other agricultural activities such as animal husbandry, industrial activities in the southern half of the province, has created and intensified extensive changes in the environmental resources and natural structure of the province. This extensive change can show its effects and consequences in the destruction of forest lands, the transformation of rich pastures into poor pastures and barren lands, severe soil erosion, and finally the creation and development of internal centers of dust. and intensify the severity of dust incidents in the province. Dust events have profound and significant effects on agriculture and soil fertility, health and hygiene, disruption and destruction of industries and power plants, and negative effects on the environment, including the deterioration of forests. Airborne particles, which are mainly driven to the region by dust storms, are one of the important components of the atmospheric system. They can not only change the albedo of the energy balance by acting as cloud particle nuclei, or ice nuclei.

The study location of this research is Khuzestan province, which is one of the most challenging provinces in the country in terms of environmental hazards. This province, with an area of about 6.5 million hectares, occupies about 4% of the country's area. Dust is one of the major and most important challenges of this province. Its destructive effects can be traced in various dimensions, such as the quality of water resources, the quality and performance of agricultural products, industries and energy transmission networks, and the air quality of cities. Three categories of data have been used in this research. The data of the first category is related to the data of widespread dust days in Khuzestan province. These data were obtained from the dust codes of the current air condition (ww parameter of synoptic stations of the province) during the statistical period of 2000, 2020. The second category of data was actually the remote sensing data of MODIS sensor, which included the Aerosol Optical Depth (AOD) product of MODIS sensor (MOD04 product) and Aerosol Exponential Index (AEA). These two indicators are dimensionless but with different directions. In the AOD index, higher numbers represent more aerosols in the atmosphere and in the AEA index, in addition to the presence of dust in the place, it also provides the size of the aerosol particles. Finally, the third category of data is the reanalysis data related to incoming net shortwave radiation (SNSR), which was taken from the reanalysis data of the European ECMWF database version ERA5 with a spatial resolution of 0.5 arc degrees. 

In this research, it was tried to investigate the influence of the dust event in the context of fluctuations and daily changes in the amount of net shortwave radiation received on the earth's surface. The results of the investigation of three cases of widespread dust in the province showed that in these three cases of widespread dust, aerosol particles are generally in the central, southern and western parts of the province (plain and lowland areas of the province) from the type of medium to large particles (index angstrom between 0.5 and 1) and in the eastern and northeastern parts, it was of the type of coarse particles (angstrom index less than 0.5). In the context of the impact of dust events on the amount of shortwave radiation received by the earth's surface, it was seen that in the dust event of July 22, 2010, the Angstrom exponential index indicates the presence of coarse particles in the atmosphere near the earth's surface and the AOD index also indicates the presence of dense dust in the entire area of the province. The received net shortwave radiation (at 12 noon or 09 UTC) was about 194 watts per square meter (about 28 percent) lower than the average for the same month. This drop rate was less in the other two dust waves, whose AOD and Angstrom index values indicated finer and less concentrated dust. In the dust wave of June 19, 2012, the amount of net shortwave radiation received was only 5% (25 W/m2 at 12 noon or 09 UTC) less than the long-term average, and this drop in the dust event of May 12, 2018 was equal to 28 W/m square (about 4% drop compared to the average of the same month).

Knowledge of supernatural microphysical properties and revealing its relationship with the spatial temporal distribution of precipitation can significantly increase the accuracy of precipitation predictions. The main purpose of this study is to reveal the relationship between the Cloud microphysical structure and the distribution of precipitation in Khuzestan province. In this regard, first 3 inclusive rainfall events in Khuzestan province were selected and their 24-hour cumulative rainfall values were obtained. The rainfall event of 17December2006, was selected as a sample of heavy rainfall, 25 March 2019, as a medium rainfall case, and finally 27 October 2018, as a light rainfall case. Microphysical factors of clouds producing these precipitations were obtained from MODIS (MOD06) cloud product. These factors included temperature, pressure, and cloud top height, optical thickness, and cloud fraction. Finally, by generating a matrix with 64000 information codes, and performing spatial correlation analysis at a confidence level of 0.95, the relationship between the Cloud microphysical structure and the spatial values and distribution of selected precipitates was revealed. The results showed that in the case study of heavy and medium rainfall, the spatial average of 24-hour cumulative rainfall in the province was 36 and 12 mm, respectively. A fully developed cloud structure with a cloud ratio of more than 75% and a vertical expansion of 6 to 9 thousand meters, with an optical thickness of 40 to 50, has led to the occurrence of these widespread and significant rainfall in the province. While in the case of light rain, a significant discontinuation was seen in the horizontal expansion of the cloud cover in the province and the cloud cover percentage was less than 10%. In addition, the factors related to the vertical expansion of the cloud were much lower, so that the height of the cloud peak in this rainfall was between 3 to 5 thousand meters. The results of this study showed that in heavy and medium rainfall cases, a significant spatial correlation was observed at a confidence level of 0.95 between MOD06 Cloud microphysical factors and recorded precipitation values, while no significant spatial correlation was observed in light rainfall case.

The role of climate in the study of urban environments is important in terms of its impact on climate change in urban environments. The heat island is one of the hazards that has recently affected the environmental conditions of cities due to urban development.

For this purpose, Landsat ETM satellite images were used during the period 1990-2019. In this regard, LST and NDVI indices, urban coverage and land use were used. Geographical area of research The city of Isfahan has been considered in this study. 

Results and discussion: 

The results showed that the high temperature is mostly in the central core of Isfahan and the surrounding city is covered by the middle temperature class. Most of the low temperature class also includes agricultural use due to high humidity. Parks and green spaces in the city are among the middle temperature classes due to the impact of high and very high temperature areas around them.

In general, it can be said that in the last three periods, the highest area has been related to the average temperature, and this trend will continue in the coming years. Due to the reduction of agricultural land use and the physical expansion of the city, the area of heat islands in the upper range has increased. On the one hand, the reasons for the increase in high temperatures are the increase in population, the increase in industries and the number of cars in the city, the multiplication of traffic volumes, the increase in asphalt levels and urban and interurban roads, and the increase in wasteland due to grazing. He pointed to overcrowding and damage to pastures, as well as clearing of green lands and deforestation.

The aim of this research was to identify and rank the factors influencing the choice of architectural type and zoning based on climate conditions using the best and worst methods. Library and field methods were used to collect data. Data collection tools are databases related to climatology in Ahvaz metropolis. In order to determine the weight of each factor, the opinions of experts and ANP were used, and the factors were ranked according to the weight of each factor. The findings showed that among the obtained weights, pollution prevention with weight (0.099), sunny hours with weight (0.097) and access with relative weight (0.096) have the highest weights among the sub-indexes obtained, which are in the first ranks to They placed third. Other weights were based on the weights obtained in other ranks. Other weights were based on the weights obtained in other ranks.Other weights were based on the weights obtained in other ranks.

The development of the tourism industry and the resulting income has provided the basis for competition between countries. The tourism authorities are making a double effort to attract more international tourists by introducing tourist and geo-tourist places and provide the basis for the distribution of domestic wealth through them. The city of Mahshahr in Khuzestan province is no exception to this and in this context, the structures It has many scientific, ancient and cultural sites that have high potential for tourists. Among the natural attractions of this province, we can mention the wetlands, river banks, bridges and parks, estuaries, etc. as tourist places, which are subject to historical and influential factors They are social, geology and geomorphology. The purpose of this research is to evaluate the criteria and capabilities of tourist places in Mahshahr city. The main problem of the current research is based on a main question, which is the highest value of tourism among the geoclimatic attraction indicators of Mahshahr city? Also, by identifying some geotourism places, investigate their importance in attracting tourism in this city.

This research is of a descriptive-analytical type and to collect data from the method 1. Library, documents and fieldwork were used. 2. In order to determine the exact location of the studied stations, the software (Google Earth) was used. 3. The obtained information was adjusted in the Prolong tables (Prolong method). 4. Experts and tourism professors and students were asked to complete the questionnaire. During the field visits, 4 places in the desired area, including Khormosi (station no. 1), the next station Khor Smiley (station no. 2), the third station of the deserts around Mahshahr (station no. 3), the fourth station of the Salt Lake (station No. 4) was selected.

This part of the research work, first, the tables related to the score criteria in terms of cultural and historical value, appearance and economic beauty along with scientific value and the level of productivity as well as the quality of exploitation were brought and prepared for analysis. After identifying some geotourism capabilities of the studied area, the effective factors in the development of these landforms were analyzed using the Prolong model: First, the tourism criterion of Mahshahr city was evaluated with four criteria of external beauty, scientific, cultural, historical and socio-economic. Each of the criteria was scored and finally the overall value of the area was determined. Also, the average value of productivity was obtained from the sum of the points of the value of quantity and quality of productivity and calculating their average.

The results showed that Namak Lake and Khor Smiley with value (0.525 and 0.531) have the highest average tourism and Mahshahr desert (0.475) has the lowest average tourism. The highest average productivity value is related to Namak Lake with an average of (0.62) and the lowest productivity value with (0.24) is related to Khor Smiley. Also, the salt lake has the highest quality of productivity.

Geomorphosites possess the potential to evolve into tourist destinations. Shadgan Wetland, benefiting from favorable weather conditions during winter and spring, attracts numerous tourists. This research aims to evaluate the tourism capabilities of Shadgan Wetland. The opinions of environmental experts and tourists were analyzed using the SWAT model and a Likert-scale questionnaire. The study involved three stages: identification of internal factors (IF) or strengths and weaknesses, identification of external factors (EFE) or opportunities and threats, and assigning weights to these factors. The results indicate that among the external factors, threats carry the highest weight of 2.52, while weaknesses have the highest weight of 3.39 among the internal factors. The strategic approach for this wetland entails a competitive strategy of maximum-minimum (wo) type, whereby officials should aim to capitalize on opportunities and mitigating or eliminating weaknesses.

 climate change can be considered one of the biggest environmental challenges of the recent era, which indicates unusual changes in the internal climate of the earth's atmosphere and its consequences in different parts of the globe, which is a serious threat to the environment. The purpose of this research is to prepare a vulnerability zoning map of infrastructures in the southern regions of Khuzestan in the conditions of climate change.

 for this purpose, using previous sources and interviews with experts, eleven variables of total annual precipitation, average temperature of hot and cold season, the trend of maximum precipitation of more than 5 mm per day, the number of dust codes, the occurrence of heat waves above the 95th percentile, precipitation changes, displacement of coastline, underground water changes, floods and inundation and temperature changes during 2019 to 2019 were investigated. By using two trend analysis tests, i.e. Sence slope estimator trend analysis test and Mann-Kendall trend analysis test, the trend of the 32-year time series of these elements during the basic statistical period (1985-2017) was investigated.

 The southern parts of the studied region of Khuzestan had an average temperature of more than 38 degrees Celsius per year, while the northern and central parts of the studied region had a temperature of more than 38.5 degrees Celsius per year.The southern part of Khuzestan has an annual rainfall equivalent to more than 273 mm per year, while the southern parts of the studied area have less than 200 mm of rainfall per year and in some cases about 156 mm per year.

 The results show that high and very high risk areas cover 80% of the region.

In Iran, due to the high rate of economic growth and development activities, the annual demand for various energies, including electrical energy, has increased, as a result of which the construction of new power plants has become an undeniable necessity. Considering the evolution of energy in the current century and the need for renewable energies, the use of wind energy and the establishment of wind power plants are increasingly developing. One of the most important issues in the use of wind energy is determining the location of its use, which has a great impact on the efficiency of wind power generation equipment and devices. Determining the right place for the construction of wind power plants requires attention to various criteria and factors. The purpose of this research is to determine the role of climate, geography, economic-social, environmental and geological factors in determining the suitable location for the construction of wind power plants in Khuzestan province. Based on the different roles and effects of these factors, a limitation map and a map of effective factors were prepared. The weights of criteria, sub-criteria and options were determined by Analytical Hierarchy Process (AHP) in EC2000 software environment and GIS software environment was used for spatial modeling and analysis and information integration. The results show that the southern and southwestern regions of Khuzestan province are the best places to build wind power plants.

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

Background and purpose:

Design of buildings based on climate is a method that helps to reduce energy demand of buildings for heating and cooling to use natural energy sources in order to create more comfort and reduce the use of fossil fuels in buildings. The objectives of this strategy include reducing the loss of thermal energy of buildings, reducing the effects of wind on the loss of thermal energy of buildings, providing ventilation of the interior spaces, benefiting from suitable outside climate, benefiting from solar energy for the heating demand of buildings and protecting buildings from sunlight.

Materials and Methods:

 In this study, the design strategy of educational buildings based on climate of Dezful has been developed. For this purpose, the hourly data of the Dezful synoptic station during1986-2019 were used by Climate Consultant and ASHRAE Standard 55. After receiving and standardizing the hourly data of various atmospheric elements, and loading these data into Climate Consultant, the results have been analyzed and the most suitable architectural model for the educational centers of Dezful has been proposed.

Findings and discussion :

Based on the output strategies of Climate Consultant and field visits to the schools of Dezful, the architecture of both the old and new schools, 9 strategies were developed and proposed for the sustainable design of schools in this city based on the factors affecting comfort and the principles such as window shading, high thermal mass, evaporative cooling, forced ventilation by fan and heating in addition to humidity, for the maximum use of the climatic capabilities of Dezful for school activities and avoidance of adverse climate, the most suitable orientation for light-reflecting structures and openings is the south first and second directions close to it for the schools of Dezful. For schools that have already been built and there is no other choice but to use these schools, by planting trees along the walls and undesired openings, the adverse effects of solar radiation can be minimized. The results of the field visits to the city's schools showed that for the design and construction of the new schools, the direction of the south is observed more than the old schools.

 The conflict between architecture and climate leads to an increase in energy use for cooling and heating of buildings; which has negative economic and environmental consequences in addition to mental and psychological health damage for the residents. Therefore, it is necessary to know the climate of each region and determine the standard for spaces according to the climate of each region. As a result, the design of high-performance educational buildings requires the use of accurate and scientific models and software. The study results showed that Climate Consultant 5.5 is highly effective on the design of educational spaces to discover climate design ideas in educational buildings. Therefore, this software should be used for the design of educational spaces in other cities of the province. Given that children and adolescents are more vulnerable to adverse climate in residential and educational spaces compared to adults, and in these spaces, climatic comfort and peace of mind are very important to increase the quality of education. The building design compatible with the climate is very important. To achieve this desired model, the use of walls and openings along the south or directions close to it towards the southeast is the most suitable for the design of educational spaces. 17 strategies were developed and proposed for the design and construction of schools in this city. These strategies can be a document for designers and engineers to achieve the design and construction of schools and educational spaces in Dezful based on its climate.

On April 01th , 2019 Iranian calendar, heady damages was inflicted on Lorestan province due to the arising of the heavy rainfall and consequent destructive flood . Present study was carried out to investigate the synoptic mechanisms associated with the occurrence of this rainfall. At first, the data related to the daily rainfall in different research stations was received from the metrological organizations. Afterwards, data related to atmospheric levels including Sea Level Pressure (SLP), the altitude geopotential of 850 and 500 hectopascal levels, vertical atmosphere speed , wind stream in 1000, 850, and 500 hectopascal, specific humidity of 700 hectopascal level , and the river flow of the 250 hectopascal level during the studied days were prepared and received from National Center of the Environmental Prediction (NCEP) and National Center for Atmospheric Research(NCAR). The created maps were drawn and interpreted in Grads Software.The results of the study indicated that, on April 01th when the flood hit the region, synoptic investigation of the Sea Level Press (SLP) shows a low-pressure system with a central core equals to 1206 hectopascal is located in Northern Europe with its braces covered the north of the Black Sea. Furthermore, the low-pressure system having central core of 1026 hectopascal covered wide regions surrounding Aral lake to North-east of Afghanistan. Accordingly, a low-pressure system having central core of 1008 hectopascal moved to eastern parts compared to previous day and dominated wide regions from Mediterranean through all investigated areas to Central Iran. Given that low pressure system spreads north-east Russia in line with northeast-southwest through Red Sea and East Africa, a high-pressure shave was created which was accompanied by instability and intense ascending of the weather on desired April 01th along with the arising of the rainfall in investigated region. Consequently, with the rise in the altitude and in 850 hectopascal level, low pressure system having central core equaling to 1300 hectopascal dominates North-Russia through lower latitudes. Subsequently, lower altitude closed system corresponding to 1420 geopotential meters resides Eastern Mediterranean and, compared to previous day headed eastwards and spread West and North-west of Iran including investigated region in the north-south direction.Moreover, high altitude system with central core which equals 1520 geopotential meters has spread North Europe up to 48-degree latitudes, which, given to high altitude system located on Afghanistan and Pakistan, a more intense shave arose compared to previous day. Afterwards, at 500 hectopascal level, central core having 5540 geopotential meters places on East-Mediterranean Sea in its Northeast-southwest direction, which resulted in deeper and wider trough so much that central trough spreads west Iran. The placement of its positive vorticity covers wide investigated region and results in ascending motions. The deepening of the cyclone and penetration of trough to the lower latitudes can gives rise to the precipitation of cold weather. Synoptic investigation of vertical atmospheric speed of 1000 hectopascal level revealed that maximum negative omega equals -0/2 pascal / second that is located on the North-west of Caspian Sea in Northeast-Southwest direction, and, on its movement toward Lorestan, it decreases in its intensity and reaches -0/05 pascal/ sec. Given that the second negative omega equaling to -0/15 pascal/sec is placed on Persian Gulf and omega is negative throughout the investigated region, the required conditions are really for the occurrence of instability, ascending of the weather, and rainfall. Subsequently, with the rise of altitude in the atmospheric levels, the maximum negative omega has increased and reached 0/3 pascal/sec. Within 500 hectopascal, the direction of negative omega changed from Red Sea towards investigated region which, accordingly, has been strengthened over Caspian Sea and spread the intended region in North-South direction. Given the increasing altitude of the level of the atmosphere, the maximum omega has risen and reached -0/4 pascal/sec, which accordingly intensified the conditions for atmospheric instability. Synoptic investigation of specific humidity indicated that most of the humidity advection happened from the Southern water reserves to the investigated regions. Maximum humidity core is 24 g/kgs over Red Sea and is decreasing in extent toward Iran, which, subsequently, passed over Persian Gulf and reached 18 g/kgs in Oman Sea and spread intended area in Northwest-Southeast direction.Humidity injection, particularly from southern water reserves, led to arising of the heavy rainfall during the specified day in investigated region. With the rise in the altitude at the level of 700 hectopascal, maximum specific humidity, which equal 10g/kgs, residing in East Africa and got the investigated region having passed over Caspian Sea. So , the sources for the heavy cloud rainfall on Farvardin 12th are Red Sea, Mediterranean Sea, Arab Sea, and Persian Gulf.Key Words: Heavy rainfall, Geopotential, Omega, Synopsis, Lorestan.