نشریه پژوهش های اقلیم شناسی
پیاپی 46 (تابستان 1400)

Changes in climate conditions and the frequency and intensity of extreme climate events like droughts and heatwaves have pronounced impacts on forest health and diversities around the world. Among the climate extremes and hazards, drought has the most influential impacts in forests and can adversely alter their density and spatial extent around the globe, particularly in mid-latitudes of both hemispheres. By investigating the impacts of droughts and diseases on forest trees, Loustau et al., (2006) stated that although most pathogens can resist water deficiency in drought periods in general droughts have no negative impact on forest diseases. By simulating historical long-lasting droughts in moderate climate forests, Borken et al., (2006) reported that a reduction in severe summer droughts significantly increases the CO2 conservation in forest soil. Hogg et al., (2008) investigated the impacts of regional droughts on the productivity, biomass and dieback of the Aspen forest of western Canada and concluded that the forest dieback and decline have a good correlation with annual relative humidity index which is related to short term droughts.In recent decades, oak forest dieback becomes one of the most important environmental challenges in western Iran. Climate change, pests, physiographic and anthropogenic factors were introduced as the main causes of Zagros forests dieback in the preliminary studies. The present study investigates the oak forest dieback in Lorestan province, Iran, concerning drought occurrences and their characteristics.The data used in this study include 1) field surveys using GPS, 2) MODIS satellite data for the period 2000-2017, and 3) monthly precipitation records of meteorological stations for the period 1980 - 2017. Using GPS, the coordinates of the areas encountered canopy level dieback were recorded by the authors through several field surveys. The monthly precipitation records of 16 meteorological stations well distributed over the study area were acquired from the meteorological organization of Iran. The 30 years of 1980 – 2017 was chosen as it has complete data records in all considered stations and meets the minimum record length required for SPI computation in the arid and semi-arid climates. For all considered stations, the SPI time series were computed for 3-, 6-, 9-, 12-, and 24- month time scales from which drought characteristics (i.e., drought frequency, duration, severity, and magnitude) were subsequently computed. The MODIS satellite images with a 16-day interval, totally accounting for 411 images during the eighteen years of 2000-2017 time period were also retrieved from its website and processed by ENVI software for computing NDVI index as the representative of forest health and freshness. The NDVI time series were then divided into three categories based on the density of the forest coverage, namely forest with low, medium, and maximum densities. The mean annual time series of NDVI were then correlated with the SPI time series of each time scale ended at each calendar month. The maps of the long-term mean of drought characteristics were also drawn to spatially analyze drought characteristics over the study area and assess their linkage with oak trees canopy level dieback hot spots over the region.The field study and the literature review showed that the dieback has occurred in Lorestan forests with different intensity and spatial extent, being not related to a specific land elevation, geographic location, and mountain slope and direction. The canopy level dieback of the oak trees was also found as a more common feature than the forest decline in the study area. Investigating the freshness of the forests represented by the Normalized Difference Vegetation Index (NDVI) time series derived from MODIS data showed that the first widespread forest dieback occurred in 2004 and then more intensified in 2008. The results show that the mean annual NDVI as a signal of forests trees health and freshness have the highest correlation with the SPI time series ended in all spring and summer months, particularly at 9- and 12- month time scales that showed the highest correlations with the mean annual NDVI time series. This relationship is relatively similar in most of the studied stations, more specifically in those located in or near the forest dieback hotspots that showed the highest correlation coefficients being significant at 5% significance level. The computed SPI time series also reveals that droughts are more frequent, long-lasting, and severe in the southwest, central, and northeast areas of Lorestan province where more hotspots of oak trees dieback were observed. Investigating the relationship between drought events and the spatial and temporal variations of NDVI time series indicates that a significant reduction in precipitation amount, as represented by SPI, is the main cause of oak trees canopy level dieback in the Lorestan forest, explaining 20% to 70% of the variation of the dieback phenomenon depending on the location over the province. The more widespread, severe and long-lasting droughts in the province were observed in 2004, 2005, and 2008 that coincide well with the years identified with the more pronounced oak trees canopy level dieback in the Lorestan province, as reported by literature and the local habitants.Based on the results achieved in this study, it can be concluded that the oak trees canopy level dieback occurred in many parts of the Lorestan oak forests rather than forest decline. It was also found that drought occurrences explain 20% to 70% of the variation of this phenomenon depending on geographical locations s and SPI time scales considered. Investigating the relationship between drought events and spatial and temporal variations of the NDVI showed that a significant reduction in precipitation amount, as represented by SPI, is one of the main causes of oak trees canopy level dieback in the Lorestan forest.

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

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

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

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

Climate change and global warming have affected extreme precipitation and temperature events at the local and regional scales in most parts of the globe. As a result, changes in the frequency and intensity of precipitation events occur in most parts of the world. Because of its direct effect on the water resources of the Earth, today it is necessary to detailed study on the behavior of these events. Therefore, the main objective of the present study is investigation of the homogeneity of rainfall data, determining the changes in extreme precipitation events in Khorasan South province and also calculation of the trends and statistical trends significancy of each of these indicators. The results of this study necessitate more management and planning for optimal use of available water resources. Today, with more than four decades of industrial rule over human societies, climate change, or global warming, has become a serious challenge to the planet's environment. The main reason is the intensification of human industrial activities. Increasing temperatures, melting polar ice, rising free water levels and irregularities in climate phenomena are the most important consequences of climate change. Due to the impact of climate change on a local and regional scale, support for climate change adaptation strategies and mitigating the adverse effects of this phenomenon has been considered today.

For this study, we used the long-term daily precipitation data in 6 active synoptic stations (Birjand, Nehbandan, Qaen, Boshruyeh, Ferdows and Tabas) in South Khorasan province between 1989-2018. Determination of the homogeneity/non homogeneity, finding the change points and adjusting the rainfall data time series were performed by using "RHtests-dlyPrcp" package, determination of trends observed in the extreme precipitation indices was done by using "RClimDex1.1" package and significancy test of the indices also was performed by Mann-Kendall nonparametric test and using the "trend" package in R software. Then, 11 extreme precipitation indicators were calculated for selected stations and trends in precipitation events were determined. Finally, to investigate the impact of climate change, the significances of the trends in the indicators was measured using the Mann-Kendall statistical test. These indicators were approved by the World Meteorological Organization(WMO). Overall, extreme precipitation indices are classified in two categories. A number of indicators are based on rainfall intensity per unit "mm or mm/days"(Contains 6 index: PRCPTOT, SDII, R99p/R95p, RX1day/RX5day) and others are based on duration of precipitation or number days of precipitation that are based per unit "days"(Contains 5 index: CWD, CDD, R1mm/R10mm/R20mm). To determine the significant trends in each of the 11 extreme precipitation indicators for each station, Mann Kendall confidence level was considered 95%. The test statistic more than +1.96 and less than -1.96 indicated a significant trend.

The results showed that in most of the indices there were a decreasing trend. This trends were statistically significant in RX1day and RX5day(in Birjand and Nehbandan), R30mm(Ferdows and Nehbandan), R10mm (Birjand, Nehbandan and Boshruyeh) and PRCPTOT (for all stations). Despite decreases for R20mm, SDII and R95p (except for some indices), the behavior of these indices were not significant in any stations and for other indices a significant decreasing trend was observed only in one station. Overall, by calculating trends in rainfall events at stations of South Khorasan province, there were a significant decrease in total annual precipitation across the entire province, and days with precipitation greater than 10 mm, 1-day and 5-day maximum precipitation in the eastern half of the province that is affected by climate change. Therefore, it requires more management and planning for the optimal use of available water resources.  

Global warming has caused disparities in the spatial distribution of rainfall and the changing behavior of rainfall events in south Khorasan stations over the last 30 years. The major changes in the indices show a decreasing trend. This decreasing trend is significant in some indicators. Most reductions are seen in the indicators RX1day, RX5day (Birjand and Nehbandan), R30mm (Ferdows and Nehbandan), R10mm (Birjand, Nehbandan and Boshruyeh) and PRCPTOT (for all stations). The south of the province is experiencing a significant decline in most of the indicators and is mostly affected by climate change, which requires more planning for efficient use of current water resources. The rest of the indices were either not significant (SDII, R99p and R20mm) or only significant at one station. So for the province, only a fraction of the changes in of extreme Precipitation Events are due to climate change.

With the growth of urban population, due to the increase in air pollution and also reaching the desired per capita green space, the need for urban green space development becomes clearer than before. However, the scarcity of extractable water resources raises concerns in this area. Water resources management is the only appropriate and principled solution to compensate for a large part of the water shortage required by green space. Calculating and estimating the water demand of urban green space can be a great help in planning for the optimal use of water resources. In this study, the evapotranspiration of urban green space plants in area one of Tehran Municipality with a net area of ​​1535.4 hectares was estimated using three methods WUCOLS, IPOS and PF. The study area includes 52 different plant species. To calculate the reference evapotranspiration and the amount of effective rainfall, climatic data of the North Tehran Meteorological Station for a period of 30 years (1365-1396) were used. The results showed that the highest amount of calculated water requirement is related to the PF method at the rate of 786.72 mm per year and the lowest is related to the IPOS method at the rate of 378.08 mm per year. Also, the results of this study indicate that the WUCOLS method with a total amount of calculated water requirement of 771.33 mm per year, due to having more and more complete parameters and more appropriate relationship with all objectives in urban green space, a method It is more suitable for estimating the water demand of urban green space.With the growth of urban population, due to the increase in air pollution and also reaching the desired per capita green space, the need for urban green space development becomes clearer than before. However, the scarcity of extractable water resources raises concerns in this area. Water resources management is the only appropriate and principled solution to compensate for a large part of the water shortage required by green space. Calculating and estimating the water demand of urban green space can be a great help in planning for the optimal use of water resources. In this study, the evapotranspiration of urban green space plants in area one of Tehran Municipality with a net area of ​​1535.4 hectares was estimated using three methods WUCOLS, IPOS and PF. The study area includes 52 different plant species. To calculate the reference evapotranspiration and the amount of effective rainfall, climatic data of the North Tehran Meteorological Station for a period of 30 years (1365-1396) were used. The results showed that the highest amount of calculated water requirement is related to the PF method at the rate of 786.72 mm per year and the lowest is related to the IPOS method at the rate of 378.08 mm per year. Also, the results of this study indicate that the WUCOLS method with a total amount of calculated water requirement of 771.33 mm per year, due to having more and more complete parameters and more appropriate relationship with all objectives in urban green space, a method It is more suitable for estimating the water demand of urban green space.With the growth of urban population, due to the increase in air pollution and also reaching the desired per capita green space, the need for urban green space development becomes clearer than before. However, the scarcity of extractable water resources raises concerns in this area. Water resources management is the only appropriate and principled solution to compensate for a large part of the water shortage required by green space. Calculating and estimating the water demand of urban green space can be a great help in planning for the optimal use of water resources. In this study, the evapotranspiration of urban green space plants in area one of Tehran Municipality with a net area of ​​1535.4 hectares was estimated using three methods WUCOLS, IPOS and PF. The study area includes 52 different plant species. To calculate the reference evapotranspiration and the amount of effective rainfall, climatic data of the North Tehran Meteorological Station for a period of 30 years (1365-1396) were used. The results showed that the highest amount of calculated water requirement is related to the PF method at the rate of 786.72 mm per year and the lowest is related to the IPOS method at the rate of 378.08 mm per year. Also, the results of this study indicate that the WUCOLS method with a total amount of calculated water requirement of 771.33 mm per year, due to having more and more complete parameters and more appropriate relationship with all objectives in urban green space, a method It is more suitable for estimating the water demand of urban green space.

Climate change and global warming are some of the issues and concerns of human beings today that have important effects on rain, evaporation, runoff, and finally water supply and causes the severity and weakness of these parameters, increasing the occurrence of severe weather events and lack of available water, which causes irreparable damage. Evapotranspiration is an important component in the hydrological cycle that is affected by various factors such as air temperature, relative humidity, wind speed and number of sunshine hours, and these factors are also affected by climate change. Due to the occurrence of climate change in the country in recent decades, it is important to study the changes in the trend of climatic parameters and their role in evapotranspiration in order to apply management methods to reduce evaporation in water resources. The Mann-Kendall trend test is an often-used method to examine changes in the data time series, but this test only expresses changes in the center of the data series, so Quantile and Bayesian multiple regression methods are used to study the trend of changes in different parts of the data time series and also to investigate the role of various parameters on a specific parameter. Therefore, the purpose of the present research is to study and compare the trend of changes in evaporation and climatic parameters affecting it and determining the role of these factors on evaporation using Quantile and Bayesian multiple regression methods at Hashemabad Gorgan station located in Golestan province.

In the first step, the meteorological data time series of evaporation, and the factors affecting it including average temperature, relative humidity, sunshine hour and wind speed were prepared for Hashemabad Gorgan synoptic station with a statistical period of more than 30 years (1984-2018) and the seasonal data series of these data were formed. The non-parametric Mann-Kendall test was performed to investigate the trend of changes in evapotranspiration and the factors affecting it and then Quantile and Bayesian regression was used to investigate the changes in various quantiles of data series and also to determine the role of changes in different values of each of these meteorological factors on evaporation.

investigation of the trend in the evaporation data series and the factors affecting it based on the Man-Kendall test shows that the aforementioned trend test shows a decreasing trend in evaporation only for winter, while the lowest changes in trend in different quantiles are in this season, and in Summer the increasing trend in evaporation has the highest slope in the range of 0.66-1.14% for lower and upper quantiles, respectively. In spring, the increasing slope of 0.75 in the upper quantiles gradually changes to a decreasing slope of -0.72. In autumn, the lower quantiles have a higher slope up to -0.66 and in winter, the quantiles have the lowest slope between -0.14 to -0.08. The results of investigating the factors affecting evaporation also show that changes in temperature have a greater share in the changes of daily evaporation and the bigger the quantile, the increasing slope increases. The relationship between relative humidity and evaporation follows a decreasing slope and ranks second after temperature. Finally, it can be concluded that in Hashemabad station of Gorgan, the Mann-Kendall trend test could not detect significant changes that have occurred in the process of the evaporation trend, but these changes have been revealed the best by the Quantile regression method. In summer, which is the driest and hottest season of the year, the trend of increase in evaporation is more intense, and due to summer cultivation in this region, water consumption in agriculture has increased in recent years and with this trend will increase further in the future.

Given the fact that climate change may not have occurred only in the average value of a data series, but extreme events might have occurred in some parts of the series so it is necessary to study different parts of the data series using methods such as Quantile and Bayesian multiple regression and the results of this research emphasizes this matter. Also, due to the necessity of studying evapotranspiration in the application of management methods for water resources, useful and practical results can be brought out by studying the changes in different ranges of evapotranspiration, especially it’s extreme and high values as well as the effects of changes in different ranges of climatic parameters on evaporation.

Due to the growing trend of climate change in recent years and the occurrence of accident-causing events such as glaciation, storms, hail, drought, etc., the need for more analysis and forecasting of this type of climate-causing hazards is felt.Since Golestan province is one of the agricultural hubs and there are many forests and pastures in it, managers, farmers, and ranchers must anticipate the occurrence of droughts to reduce possible losses during accidents and disasters. Therefore, in this research study, by selecting different stations and distributing the appropriate location in the selection of stations from the data of synoptic stations and rain gauges, evaporators using common annual data 1979-2008 AD and 56-57-85-86 to analyze and predict drought paid.

The research place of Golestan province with geographical coordinates is 37.2898 ° N, 55.1376 ° E. In this research, in the first stage, 6 stations from meteorological stations of Golestan province (Gorgan, Gonbad, Bandar-e-Turkmen, Aq Qala, Kalaleh, Aq Togha) were selected with 36-year annual data. Precipitation data lacked independence and homogeneity of data. Thyer (2000) notes in his research that it takes at least 120 years to simulate the annual rainfall of an area using the Markov chain. Thyer et al. (2006)To continue from Hashemabad Semioptic Station of Gorgan and Gonbad with statistical years (1979-2008) 30 years old and Evaporation and Rain Metering stations of Maravatpeh, Tangarah, Tamar, Til Abad, Araz Kuseh, Tarshkoli, Incheh Borun, and Ghaffarhaji with statistical years (2005-2006 to 1977-1978) 30 years selected and quarterly data collected with the calculation of 4 seasons and 30 years of data reaches a total of 120 cases.

In these stations, in the whole studied period, there were 1200, 566 wet seasons, and 634 dry seasons, which indicates the increase of droughts.According to the probability transfer matrix of the first order of the studied stations, the highest wetting limit is related to Hashemabad Gorgan station with a stability of 64% and the lowest limit is related to Tilabad station with a stability of 39%.probability matrices such as hashem abad gorgan in winter are expected to have p00 means that the probability occrunce of a dry month After a dry month, 56% and the probability of occurrence of p11 means a probability of occurrence of a wet month after a wet month is 53%. P10 means a 47% probability of occurrence of a wet month after a dry month and p01 means a 46% probability of occurrence of a dry mouth after a wet month which is the lowest probability of occurrence.

1- According to the 30 years studied, the dry season occurred 634 times and the wet season 566 times, indicating an increase in drought periods and that its durability has also increased.2- There has been a long period of drought in Gorgan station since 2005. There was only one wet season in winter 2006, i.e. during the last 14 seasons, it was only one wet season. In this period, the most severe drought with SPI 3- index (extremely dry) is unprecedented in the studied stations. Has occurred.3- In Gonbad station, like Gorgan station, a drought trend has been observed since 2005. During the last 14 seasons, only 4 seasons have been wet and the highest level of drought occurred in this period has reached close to SPI 2- (extremely dry).Results of transfer probability matrices1- In all studied stations, P00 (probability of occurrence of a dry season after a dry season) is above 50% except (Til Abad), the highest of which is related to Hashem Abad station in Gorgan with a probability of 66%. This shows. The duration of droughts in the province is long.2- In Maraveh Tappeh, Tangarah, Tamar, Tilabad, Arazkuseh, Tarshkoli, Incheh Borun, Ghaffarhaji, Gorgan, and Gonbad P01 stations (probability of occurrence of a dry season after a wet season) 42, 50, 47, 51, 44, 47, 41, 48, 34, 52, percent, most of which are related to Gonbad station and the least of which is related to Hashemabad station in Gorgan.3- The percentage of drought in Gonbad station is higher than other stations. In Maraveh Tappeh, Tangarah, Tamar, Til Abad, Arazkuseh, Tarshkoli, Incheh Borun, Ghaffarhaji, Gorgan, and Gonbad stations, the probability of P10 occurrence (ie the probability of occurrence of a wet season after a dry season) is 55-51, 60-54.5, respectively. 55-54,61-5,52-47, 55-54, 52-45, 53-52, 51-36, 54-51, the highest percentage is related to Tilabad station with 61% and the lowest is related to Gorgan station with 36%.4- The highest percentage of P11 (probability of occurrence of a wet season after a wet season) is related to Hashemabad station with 64% and the lowest is in Tilabad station with 39%

Because winter has the wettest season and the highest frequency of wet season, but in some years dry season has occurred continuously in most stations in this season, for example in Gorgan station, the most severe continuous drought occurred in winter 2006 with an index of -98-98 It has been found that it is unprecedented during the study period. If winter is the wettest season and the highest frequency of the wet season in the whole province, it seems that this type of change is due to climate change, which needs further investigation.According to the studies and the results of drought analysis in Golestan province, it shows that the length of dry periods has increased, which is in full accordance with the findings of Daneshmand and Mahmoudi (2017). And that the duration of droughts has increased since 2000 and the highest intensity of droughts has occurred in the years 2000-2008 and since 1979-80, so that since 2005 in Gorgan, Gonbad, and Ghaffar Haji stations is more intense and long.Since the minimum drought period is more than one year and the maximum is more than 5 years, the droughts in the province are increasing and changing, and this can pose many risks to the agricultural sector and water resources.

The land surface temperature is the highest layer of the earth's surface and depends on the level of surface emission, vegetation and the types of ground cover. Earth's surface temperature provides important information about the physical characteristics of the Earth's surface from local and global scales, and plays an important role in many applications. From Earth's surface temperature to study water resources management, agriculture, resource management, drought, environmental geochemical processing, meteorological research, global changes in land surface temperature, weather forecasting, hydrology, ecology, plant status survey, urban climate, studies Environmental and geophysical variables such as evaporation-transpiration and soil moisture are used. In general, temperature measurements at ground level are performed by meteorological stations, including synoptic and climatological. It should be noted that meteorological stations are only able to measure the temperature at specific points that have already been installed there. What is considered to be a major flaw in ground temperature monitoring is the lack of sufficient meteorological stations to know the temperature values in stations without stations, which have been partially remedied today by remote sensing technology. Earth's surface temperature is one of the most important components in global studies, which is used as one of the important factors in controlling the biological, chemical and physical processes of the earth.

Moghan plain is located in the northwest of Iran and is subject to Ardabil province and is located in the northern part of the province. ParsAbad Moghan city is a relatively large plain with an area of 143494 hectares, which occupies about 14% of Ardabil area and is the northernmost city of the province. The data used in this study included the Landsat 8 satellite image, which used its OLI sensor to extract land use maps and its TIRS gauge used to extract the Earth's surface temperature for 2018, as well as the ETM + Landsat imager to prepare land use maps. Using visible and infrared bands and surface temperature using thermal bands for 2002. The city's meteorological data were also used to check the temperature recorded by the stations. The ENVI 5.3 software was used for atmospheric and radiometric corrections, and the ARC GIS 10.5 software was used to extract the relevant maps. In order to classify land use, object-oriented classification method was used in eCognition Developer64 software. In object-oriented classification, spectral information is integrated with spatial information, and pixels are segmented based on the shape, texture, and gray tone of the image at a specific scale, and image classification is based on these components.

The largest area in 2002 belongs to the rangeland class with an area of 58,138 hectares. The second area belongs to the dryland agricultural class, which has the largest area with 52369 hectares. The smallest area belongs to the use of water with 543 hectares. For 2018, rainfed agriculture had the highest area with 41906 and then pasture with 30943 had the highest area. Looking at the uses of 2018, the results show a significant difference that the use of soil has increased from 11143 in 2002 to 30943 in 2018, as well as the use of irrigated agriculture and residential areas and forests. However, the use of irrigated areas has decreased significantly from 543 hectares to 262 hectares, and the use of rainfed and rangeland agriculture has also decreased compared to 2002. The water temperature during 2018 was almost constant and did not differ significantly, and the lowest temperature in both years is 31 degrees. Due to the fact that water has a high heat capacity, water has a lower surface temperature to the soil has the highest temperature in both years with 40.80 for 2002 and 42.92 for 2018. Aquaculture in 2003 was 33.12. C, which in 2018 increased to 34.41. C. The rangeland use has had a high temperature in both years of study and has increased from 38.22 in 2002 to 39.26 in 2018.

In this research, in the first step, in order to classify and then examine the changes that occurred in a certain period of time in the city of ParsAbad, action was taken. For this purpose, in the first stage of this research, in order to classify and record changes in a 16-year period, object-oriented images were classified in eCognition software and in ArcGIS10.5 software, extraction maps were extracted. Was. The classification accuracy in 2000 has a total accuracy of 0.90 and a coefficient of 0.87. While the classification in 2018 with an overall accuracy of 92% and a Cape coefficient of 0.90 has provided a relatively higher accuracy. After classification, an attempt was made to examine the changes that occurred in the region over a 16-year period, and a map of land use changes was drawn up for the area under study. Land surface temperature is one of the main parameters in the study of cities. Because it is almost the same as the air temperature in the lower layers of the city, which is the energy balance of the surface and determines the climate between the buildings and affects the life and comfort of the urban residents. Soil use has the highest temperature in both years with 40.80 for 2002 and 42.92 for 2018. Also noteworthy about residential areas is that residential use has increased from 34/51 in 2002 to 40/09 in 2018, which indicates that in 2018, with the expansion of the city compared to 16 years ago, the heat concentration will also increase. Increased. This use is due to the presence of man-made and heat-absorbing factors such as asphalt, concrete, the existence of various machinery and factories, as well as the creation of tall buildings that prevent heat from escaping around and prevent wind from moving into the city.

Climate change has upset some natural balances, including; Radiation is the result of rising greenhouse gases and global warming, manifested by changes in the long-term average temperature and precipitation in drought forms, rising floods, rising sea levels, and rising ocean surface temperatures And new designs called "Climate Design" were developed against the damage caused by these effects to provide the necessary flexibility in Climate change has upset some natural balances, including; Radiation is the result of rising greenhouse gases and global warming, manifested by changes in the long-term average temperature and precipitation in drought forms, rising floods, rising sea levels, and rising ocean surface temperatures Equivalent to climate crises, which have been called "climate resilience" by thinkers, and is an important component in climate change and the ability to prepare the system in the face of these effects and return to its original state Climate Resilience in Climate Design refers to the use of renewable energy and resilient materials and ecosystems, which revolve around smart climate construction, resilience and resilience of cities to adapt to the effects of current and future climate change .

Data collection in this study is based on synoptic information in the period (1985-2019), which is based on the thermal analysis of the construction site using the 2011 Ecotect software. The criterion for selecting the coastal city of Noor for research is the presentation of climate resilience design in the building to better control energy in the building by passive methods and thermal comfort. The results of the findings are presented in the form of tables and graphs and analyzed.Noor city with a location between 36 degrees and 2 minutes to 36 degrees and 34 minutes north latitude and 51 degrees and 20 minutes to 52 degrees and 18 minutes east longitude with a height of -19 meters above sea level.(figure1) Figure (1) Map of the geographical location of Noor

According to the research findings and available data, software tables and output with new findings in the research area, the study of climatic elements shows that during the statistical period (1364-1398) the total annual radiation is 1884 hours, the average annual temperature 16.5 degrees Celsius, the average relative humidity is 81 percent, the average wind speed is 1.4 meters per second and the number of frosts is 5 days. Examining the results of thermal analysis in the research area shows a structural relationship between building and thermal mass according to the rate of rotation of the building to the south and southwest, which increases the thermal function of the building indoors. The slope of regression is 0.93, which is the numerical value of the region's climatic resilience in climate change, it has the power to return to its original state. For ventilation in the building, the direction of the window in the building is very important. In the research area, the rate of adaptation of ventilation and temperature for changing the consumed air was 2.21 watts per square meter per hour, which is done using windows and heat exchangers. The radiation factor is 500 watts per square meter. The daily radiation density is 79% of the building, which is 2.5% of the direct radiation range on the building. The most suitable daily light is from the south, southeast and east, and the most unfavorable direction is west, which is due to the intensity of the radiation at sunset with the decrease in the daily height of the radiation. For sustainable climate design with a climate resilience approach, six inactive radiant design techniques have been proposed in the comfort zone; Thermal mass, direct and indirect evaporative cooling, inactive radiant heating, night ventilation and natural ventilation. Establishment of buildings in the southwest, northeast, east and southeast has led to climate resilience and a sustainable climate design in the region, which can be designed with residential spaces equipped with intelligent facade system, facade and solar roof using photovoltaic systems with a slope angle of 46 to 51 degrees south and southwest, 71 percent of the building's thermal energy is provided.

Researchers use climate resilience as a tool for better decision-making in natural hazards, empowerment of infrastructure, innovation in the process of urban governance in dealing with climate change. This study has analyzed and evaluated the residential area in comparison with the research work of Fernandez et al. (2019) who dealt with the climatic resilience of the city. Compared to the study of Louis and Wang (2019) in Weidung, the equivalent has been researched with them, with the difference that in addition to Ecotect, they used climate consulting software, which is lacking in the present study. Manafluian et al. (2019) studied human and physical factors in measuring climatic resilience in Tabriz, but this research has entered the natural field. Modiri et al. (2012) on the best location of the building based on radiation in Gorgan believed that the south and southwest directions have the best radiation, which in the present study, in addition to the south and southwest, east and southeast directions also have the best radiation. And climatic resilience in these respects is necessary for climatic comfort.Pir Mohammadi and Rafiei (2015) also stated that the purpose of climate design is to reduce energy loss. In the present study, the climatic resilience of the building leads to a reduction of energy loss and a sustainable climate design in buildings within the research area.

It's been a while that, global warming has been involving the scientific and political circles of the world. Human worries about the effects of climate change have put countries on the agenda of international treaties, including reducing carbon emissions and so on. Since the implementation of commitments in countries requires public participation alongside the actions of governments, the present study has examined the sociological analysis of the relationship between climate change and social capital from the perspective of relevant experts. According to O Niell & Hulme (2009), today individual commitment to the detrimental effects of climate change can provide the impetus for the necessary changes in behavior to provide the required weight to adopt coping policies. But in many cases the detrimental effects of climate change are of little importance to citizens, one of the reasons being the imminent concealment of a spatial threat. The main purpose of this study is to answer the question: What is the relationship between climate change and social capital? The research method used in this study was qualitative and thematic analysis. Semi-structured interviews were conducted with 15 professors and experts in sociology, geography and agriculture and water resources. The four main themes of the interviews were extracted from the necessity of cognition, awareness, social trust, social participation, and legitimacy, all of which are key components of social capital. According to interviews with professors and experts, it is clear that the need to be aware of the most important factors in dealing with crises such as climate change is what helps us to achieve this. There is awareness that needs to be addressed through professionals and practitioners, and then there is the discussion of education that should be institutionalized through childhood and through school education and that NGOs can play an effective role in this regard. Another role that can be effective in awareness is the role of the media, especially cyberspace, which can be influenced by the widespread use of it. Another important factor mentioned in the interviews is the lack of social trust in our society. Many of the experts interviewed believed that the reason for such a weakness was due to the way officials handled it because it failed to give people confidence not only in crises such as climate change but also in more trivial matters such as water projects. And the fair distribution of water and so on in society. In addition to their own responsibilities, people and NGOs can be effective in building that trust. This group can increase resilience by thinking about social benefits and training social skills and increasing them in response to natural crises and resource depletion. A third factor that contributes to events such as climate change is the social participation of individuals, which many experts believe is a necessary part of their trust and that officials and public officials are involved in making decisions about local communities. In other words, the role of the authorities in planning to attract people is considered important. On the other hand, the participation of the people and the NGOs in crises such as floods and other issues such as the earthquake war, which is more visible to the public, is clearly evident. In general, involving people in decision-making increases people's sense of responsibility. The fourth topic of the investigation was legalization; which experts say requires compliance by law officials themselves. Gaining people's trust is somehow the result of law enforcement by the upper echelons of society, and the proper conduct of law enforcement and lawmakers leads to law enforcement by the people. In fact, these themes are intertwined and interconnected. These four themes can be linked: informing individuals and cultures about the effects and consequences of climate change phenomena in a long-term way by institutions such as education, the formal media and non-media. Officially, NGOs and professionals with the two target populations of the public and the authorities, will increase the sense of responsibility among the public and authorities. By doing responsible actions, the law will be respected and law enforcement will take its place. It is in this state that social trust and its effects can be seen to increase the participation of people in society. As a result, climate change is a potential threat to water, food, health, and social capital., Is achieved through planning and upgrading the level of knowledge and awareness of individuals, increasing social participation and promoting social capital.

In the vast country, Iran, which has been widely used in the latitude and diverse altitudes, we see the effects of climate change. One of the most fundamental factors in the structure of the planet is climate, and undoubtedly nature, man and all the preventive life of the widespread influence of the climate. Knowledge of climatic zones and influential elements in each region based on climatic indicators and elements has long been the focus of many scientists. Perspectives are less common in literature and climatological texts; This is while environmental planning and analytical analysis is a systematic attempt to look to the long-term future in the field of climatology; One of the most important challenges today and in the future is the issue of rising temperatures. In general, the study of scientific studies and reports shows that the climate and temperature pattern is changing and this issue needs to be studied and paid more attention to the importance of water resources and agriculture in the study area and tried to study the climatic conditions of the province Sistan and Baluchestan is covered.

The study area in the present study is the southeastern part of Iran, Sistan and Baluchestan province. In this study, meteorological data from synoptic stations include daily precipitation, minimum temperature, maximum temperature and sundial for the period 1987-1920. The mentioned data have been obtained from the Statistics and Information Center of the Meteorological Organization of the country. -LARS WG is a generator of meteorological data. The LARS - WG model was designed by a scientist from the Rotamstead Center for Agricultural Studies in the United Kingdom. Using data monitored to study the climate behavior of stations in the statistical period, as well as daily network data of future total circulation models, Modeled future courses daily. The core of this model is the use of the Markov chain, which has been used repeatedly. Performance of LARS - WG model Using error measurement indices and ensuring the suitability of the model, future period data were generated using general turnover model data. In this study, statistical tests were used to evaluate the performance accuracy of the LARS-WG model using NSE, MSE and R2 criteria. In this study, the maximum temperature in the base period and future periods based on two scenarios, RCP2.6 (commitment of countries to reduce greenhouse gases) and RCP8.5 (if not adhering to reducing greenhouse gases) was followed by Using maximum daily temperature data of six synoptic stations in the southeastern part of Iran based on the threshold of the 95th percentile, among the available data, heat waves greater than or equal to three days were identified for each station. Since air temperature determines potential evapotranspiration, the ionp relationship is based on the average total annual rainfall relative to the average evapotranspiration.

To compare the simulated and observational monthly averages, the distribution chart related to the mean of each of the variables in the whole period under study in the southeastern part of Iran was drawn and the correlation coefficient of each was calculated. The distribution diagram of minimum temperature, maximum temperature, precipitation related to the southeastern part of Iran is shown in Figure (3). The observed and generated distribution diagrams show the minimum temperature, maximum temperature, precipitation and sundial of the southeastern zone in the period 1987-2019. As can be seen in the above figures, the results show high correlation coefficients. In general, in the southeastern part of Iran, the correlation coefficients between modeling and observational values in the period under review are significant at least at the level of 1%. Becomes. The least changes are related to the coastal station and the most changes are related to the land stations. Changes in the mean annual temperature difference of the southeastern part of the country during the statistical period with a long-term average of 30 years were investigated; In this case, temperature data show a positive trend in the region and in general, temperature changes in the southeastern part of Iran are evident and these changes can be named as an indicator of climate change.

The HadCM2 model shows that the average annual temperature is 22 degrees Celsius much lower than the observed average, with a difference of -2, and has good accuracy for predicting future climate change. The seasonal average temperature increases in six stations and the amount of rainfall in the stations increases towards winter and spring; Most of the heat waves belong to Zabol station and as we go from north to south, the number of these waves has decreased. The spatial displacement of climatic zones in three consecutive periods indicates an increase in climatic drought coefficient and the expansion of climatic territory. Finally, the results show the trend of increasing temperature and decreasing rainfall in the coming decades in the southeastern regions of Iran.