Climate Change and Climate Disaster

Abstract The desiccation of Lake Urmia, recognized as one of the most significant environmental crises in Iran, has had far-reaching economic, social, environmental, and managerial impacts on the surrounding regions. This study adopts a descriptive–analytical approach to examine the spatial consequences of Lake Urmia’s desiccation and to identify effective restoration strategies. Data were collected through library research and survey methods. The statistical population consisted of 60 experts and executive managers selected using the snowball sampling technique. Data were analyzed using the structural cross-impact analysis approach in MicMac software and the interactive cross-impact analysis approach in Scenario Wizard software. The findings indicate that the depletion of water and soil resources, declines in production, income, and investment opportunities, rising unemployment, stagnation in the housing market, the emergence of ethnic tensions resulting from population displacement, particularly the settlement of Kurdish migrant groups in the Azerbaijan region, widening socio-political divisions, spatial and physical management challenges, declining tourism, and weakened regional and national cohesion and development are among the most significant consequences of Lake Urmia’s desiccation. Furthermore, improving laws and regulations, halting dam construction, implementing watershed management projects, stabilizing dust source areas, reforming cropping patterns, and enhancing public awareness were identified as the most effective strategies for restoring the lake.

Abstract The Helmand River is the main water source for northern Sistan and Baluchestan, Iran. The failure to respect Iran’s water rights has intensified regional water crises, caused environmental degradation, and evolved into a significant transboundary conflict. To assess Afghanistan’s claims of drought and water shortage, this study analyzed the spatiotemporal dynamics of surface water and vegetation using Remote Sensing (RS) and Geographic Information Systems (GIS). Landsat imagery covering the area from Kajaki Dam to the Hamoun‑e‑Sistan wetlands was examined across five time intervals. The analysis focused on two key events—the commissioning of Kamal Khan Dam (26 March 2021) and the rise of the Taliban government (23 August 2021)—followed by a three‑year monitoring period up to 2024. Surface water and vegetation were mapped using NDWI and SAVI indices processed in ArcGIS and ENVI. The results show an overall increase in Afghanistan’s water bodies and vegetation, indicating that current authorities have disregarded the bilateral water treaty by diverting surplus flows from Kamal Khan Dam toward the Godzareh depression. Consequently, Iran faces serious threats, including intensified desertification, border depopulation, and environmental insecurity, requiring urgent national and international policy action.

Abstract The geographical location of Ardabil Province in northwestern Iran has resulted in a highly irregular precipitation system in both spatial and temporal dimensions. The concurrent influence of local and external factors on its climate subjects the Sabalan basin to diverse meteorological phenomena. Consequently, the present study aimed to identify days characterized by heavy and widespread precipitation coinciding with peak discharge levels. To achieve this, daily data from 45 synoptic and rain-gauge stations (affiliated with the Ministry of Energy), alongside discharge data from the Doust-Beiglou hydrometric station, were utilized. Heavy precipitation days were identified using the 95th percentile criterion. Widespread precipitation days were subsequently selected based on a positive anomaly of the 75th percentile of the area affected by heavy rainfall. Following the identification of these events, atmospheric patterns were classified using upper-air data through Cluster Analysis and Lund’s Correlation Method. The results indicate that the Mediterranean cyclone, the Siberian High, atmospheric cut-off lows, and the activity of the Polar Vortex play significant roles in the occurrence of heavy and widespread precipitation within the Sabalan drainage basin.

Abstract Water security poses a growing policy challenge, critically shaped by hydro-political relations—ranging from cooperation to conflict—among political-spatial units. This applied study investigates future scenarios of such relations affecting water security in Iran’s Tang Shool basin. Using a descriptive-analytical method, the research draws on library sources and field questionnaires, with data processed via Micmac and Scenario Wizard software. Seven key variables were identified: inter-village water distribution, investment in water transfer infrastructure, basin economic development, sub-national water resource management, external water dependency, enforcement of laws on water shares, and local poverty levels. Scenario analysis based on these variables yields five probable future states for sub-national hydro-political impacts on water security: “Favorable,” “Semi-favorable,” “Static,” “At the Threshold of Crisis,” and “Critical.” The current condition leans toward the critical state. The findings underscore an urgent need to reform the water governance system.

Abstract Variation is an inherent characteristic of the climate. Over time, the change in the frequency distribution of the temperature at a location can reach a point where that location leaves behind its previous climate and accepts a new type of climate. In this case, the evolution of the temperature frequency distribution can be a suitable indicator of climate change. In hot and arid climatic regions such as Iran, where water resources are already very scarce, the evolution of the temperature frequency distribution can have significant consequences for water and energy demands. A detailed understanding of the changes that have occurred in the frequency of different temperature intervals across various points of Iran over time has been the goal of this research. To achieve this goal, daily maximum temperature reanalysis data (ERA5) for 44 years were evaluated using Singular Value Decomposition (SVD). This investigation showed that over the warmer parts of Iran, the frequency of temperatures below 20°C, and over the colder parts, the frequency of temperatures below 10°C, have decreased. In contrast to this decrease, over the warmer parts of Iran, the frequency of temperatures above 40°C, and over the colder parts, the frequency of temperatures above 30 degrees Celsius, have increased.

Abstract This study examines the spatiotemporal distribution and trends of the dust phenomenon in Lorestan Province over a 20-year period (2000–2020). By integrating ground-based data from synoptic stations with MODIS satellite imagery and utilizing the Google Earth Engine (GEE) platform alongside Geographic Information Systems (GIS), the Aerosol Optical Depth (AOD) index was analyzed as a key indicator of suspended particulate concentration and dust intensity. Statistical methods, including the Mann–Kendall test and Sen’s slope estimator, were applied to detect temporal trends. The results indicate a substantial increase in dust events, from 33 days per year in 2000 to 110 days per year in 2020, with the most pronounced rise occurring in the third decade (2011–2020). The annual mean AOD also increased from 0.15 to 0.45, reflecting a marked growth in particulate concentration, particularly during the spring season. A strong correlation (>80%) was observed between ground-based and satellite data, with close temporal alignment in recorded dust events. The GEE platform demonstrated significant advantages due to its high efficiency in processing large datasets and conducting spatiotemporal analyses. Projections suggest that by 2030, the number of dusty days may reach 150 per year, with the mean AOD rising to 0.6. This escalating trend is likely to be further intensified by climate change, recurrent droughts, and the degradation of vegetation cover.

Abstract As a prominent climate change hotspot, Iran exhibits complex and heterogeneous hydroclimatic responses to global warming. This study analyzes the temporal dynamics of temperature and relative humidity using monthly data from five representative synoptic stations (Ahvaz, Bandar-e Anzali, Tabriz, Zahedan, and Yazd) over a 38-year period (1986–2023). To model the time series behavior, a comparative framework incorporating Moving Average (MA), Autoregressive Integrated Moving Average (ARIMA), and Holt-Winters exponential smoothing models was employed. Prior to modeling, the distributional structure of the data was assessed using the Anderson-Darling test and graphical probability analysis. The results revealed a consistent and significant warming trend across all stations, confirming a convergent thermal response at the national scale. In contrast, relative humidity exhibited a profound divergence. The most significant finding was the identification of strong evidence for a climate regime shift at the Tabriz station. Here, a bimodal distribution in relative humidity, uncovered through diagnostic analysis, indicates an abrupt transition to a more stable, arid climatic state. Model evaluation confirmed the definitive superiority of the Holt-Winters approach, owing to its capability to adapt to both trend and seasonal components. These findings underscore the insufficiency of standard linear models for assessing climate change in transitioning regions, highlighting that regional adaptation strategies must be formulated based on an understanding of these non-linear and heterogeneous responses.

Abstract Northwestern Iran, as the country’s most important agricultural hub and the region with the highest frequency of hail occurrence, experiences the greatest level of damage associated with this phenomenon. The present study was conducted with the aim of selecting a probability distribution best fitted to the data on hail days and planning to reduce vulnerability to this phenomenon. Based on goodness-of-fit tests, except for Bernoulli and hypergeometric distributions, other discrete distributions including Poisson, negative binomial, discrete uniform, geometric, and binomial were able to represent the observed frequency pattern with varying degrees of accuracy. The goodness-of-fit test confirmed the significant superiority of the Poisson distribution at a confidence level of 99%. Marivan station, which has the highest frequency of hail in the entire region, shows the greatest probability of hail occurrence. Following the Poisson distribution, the negative binomial model is introduced as the second most efficient fit. These findings provide a valid statistical basis for designing risk management strategies and reducing hail-related damage in Northwest Iran.

Abstract This research was conducted to quantify the influence of changes in biophysical parameters on the regional thermal dynamics in the Bakhtegan-Maharlu watershed during March, across the period from 1991 to 2020. To achieve this objective, Landsat 5th and 8th generation satellite data were processed utilizing the Google Earth Engine platform for the extraction of the specified indices. Subsequently, Pearson correlation analysis and multivariate regression modeling were employed to elucidate the relationship between the biophysical variables and the thermal characteristics. Furthermore, Hot Spot Analysis was implemented to identify and spatially locate high-intensity thermal clusters. Findings revealed a significant and severe decline in the NDWI index across the Bakhtegan and Maharlu lakes, concomitant with a decrease in NDVI in the surrounding areas. These land surface transformations resulted in the expansion of warmer temperature classes (from 30−40^∘C to a new class of 40−50^∘C) in the southern and central parts of the basin, underscoring an increasing trend across all investigated temperature parameters. The spatial analysis indicated that high-intensity thermal clusters were predominantly concentrated in the southern and southeastern regions of the watershed; this spatial convergence was directly correlated with areas exhibiting the highest LST values, reduced water resources, and severe vegetation destruction.

Abstract The aim of the current research is the statistical-synoptic analysis of heavy spring rains in Kermanshah province, in line with proper management to prevent the occurrence of financial damage and loss of life caused by storms and floods, and the optimal use and storage of this type of rain during times of water shortage and drought. To carry out this research, daily data on heavy spring rainfall from nine stations in Kermanshah province, for the period 1951–2013, were obtained from the country's organization. Then, using statistical methods including descriptive statistics (prevalence, percentage) and inferential statistics (clustering), and the synoptic method (circulation to environment), from the NCEP/NCAR website, Omega synoptic maps at levels from 200 to 1000 hPa and composite maps (sea level pressure with vorticity, specific humidity with wind flow at the 700 hPa level, and geopotential height with vorticity at the 500 hPa level) were obtained, and the studied maps were plotted in the GrADS software environment. After identifying and analyzing three patterns of heavy rain, the results of this research showed that due to the integration of the low-pressure systems of the Mediterranean Sea and the Red Sea on one hand and the suitable position of the ridge over Arabia and the Arabian Sea, the influence of the trough on the mentioned water sources, and also the formation of the negative omega core in the upper levels of the troposphere on the other hand, conditions have been created for proper advection and divergence of moisture from the desired water areas toward the study area.

Abstract Rivers, as vital arteries of natural ecosystems, play a central role in maintaining environmental balance. Globally, river drying has become one of the most serious environmental challenges. Studies indicate that rivers located near mountainous areas are among the most vulnerable ecosystems due to their greater sensitivity to climate change. This applied research examines the factors affecting the drying up of the Zayanderud River, focusing on the Zagros mountain ecosystem. Data were collected through library and field methods, and the research problem was analyzed using a systems approach and futures studies tools. The findings show that precipitation systems, water extraction, Zagros topography, water allocation methods, and water resource management are the key factors influencing the river’s drying. Considering different possible states of these key variables, the future of the Zayanderud River appears critical. As this crisis goes beyond a local issue, it should be regarded as a warning of potential ecological collapse in the region, requiring effective cooperation among government, researchers, and society.

Abstract Precise elucidation of the dynamic interactions between large-scale atmospheric circulation patterns and hydro-climatic variability in mountainous and semi-arid regions is a prerequisite for environmental risk management. This study was conducted to investigate the correlation of the North Atlantic Oscillation (NAO), Arctic Oscillation (AO), and Multivariate ENSO Index (MEI) with temperature and precipitation in western and northwestern Iran over the period 1987–2022. Data from 20 synoptic stations were processed using Pearson correlation, Canonical Correlation Analysis (CCA), and Inverse Distance Weighting (IDW) spatial modeling. Pearson results indicated that the highest positive correlation of temperature was with MEI (0.21), while the highest negative correlation of precipitation was with NAO (–0.19). Although linear correlations were weak (mostly <0.20), canonical analysis revealed a significant and non-linear climatic response. The highest canonical correlation coefficients were recorded at Ardabil (0.266), Mahabad (0.232), and Khoy (0.231). Precipitation, with a canonical loading of –0.78, exhibited the highest influence from NAO (particularly at Sarab and Maku), whereas temperature, with a canonical loading of 0.64, was mainly controlled by MEI (notably at Sanandaj). Negative canonical loadings at Sardasht and Jolfa indicated a distinct circulation mechanism. The impact of teleconnections in western Iran is a function of synergy with Zagros topography, creating a spatial gradient from the north (dominated by NAO/AO) to the south (dominated by MEI).

Abstract Rainfall is one of the most challenging atmospheric-climatic parameters that has significant effects on different scales. In the modern world, water, whose main source is precipitation, plays an important role in the life of humanity. In the present research, a synoptic analysis of the maximum rainfall during March - April 2019 was conducted using the daily rainfall data extracted from synoptic data and the daily data of geopotential height, relative humidity, sea level pressure, vertical winds flow, and zonal and meridian winds for the south and southwest of Iran (including Lorestan, Ilam, Kohgiloye and Boyer Ahmad, Chaharmahal Bakhtiari, Khuzestan, Bushehr, and Fars). The results of analyzing the synoptic maps on the rainy days of April indicated the presence and continuation of a deep trough and a blocking pattern at the level of 500 hPa along with the bifurcation of the wind flow at the level of 200 hPa, upward movements and low pressure on the ground surface, advection of relative humidity above 80%, and hot air advection at the levels of 700 and 850 hPa in the study area.

Abstract This study presents an integrated analysis of trends in key hydro-climatic variables, i.e. minimum temperature, maximum temperature, precipitation, and potential evapotranspiration (ET₀), across annual and seasonal timescales, utilizing 30 years (1986-2015) of data from 62 meteorological stations in Iran. Using Sen’s slope estimator, results reveal a consistent warming trend across the country, notably a significant increase in winter temperatures, implying reduced snow-to-rain ratios and earlier snowmelt. At the national scale, the increasing trend in ET₀ ​coupled with decreasing precipitation paints a clear picture of Iran’s climate becoming drier. Spatial analysis identified Western and Northwestern Iran as “Hotspots of Change,” experiencing the most pronounced temperature increases and precipitation decreases, posing threats to regional water and food security. A notable finding was the observed decreasing trend in ET₀​ in some southern stations, attributed to the “Evaporation Paradox,” highlighting the importance of considering factors like wind speed and solar radiation. Collectively, this study provides robust evidence of escalating climatic stress on Iran’s water resources and underscores the necessity for adaptive, regionally-focused management strategies for vulnerable areas.

Abstract Changes in extreme climatic patterns, as the most prominent consequence of global warming, have created serious hydrological and ecological challenges in mountain ecosystems. This study analyzes the trends of extreme climate indices at the Sardasht synoptic station by examining downscaled temporal trends of 10 temperature and precipitation extreme indices (ETCCDI) over a 40-year period (1986–2025). After daily data quality control, the Mann–Kendall test and Sen's slope estimator were applied. The findings reveal a structural transformation in the region's climate regime, as a warming signal is observed across all temperature indices with statistical certainty (95% to 99.9%). The warm spell duration index has increased with a slope of +3.115 days/year, and tropical nights with a rate of +1.081 days/year, indicating intensified heat stress and disruption of nocturnal cooling. Conversely, frost days and ice days have decreased at rates of –1.259 and –1.059 days/year, respectively, confirming the decline of harsh winters and shortening of the cold season. Regarding precipitation, although the annual total shows no significant trend, the increase in the simple daily intensity index (+0.062 mm/day per year) suggests a shift toward short, intense downpours. Overall, the climate of Sardasht is transitioning from a temperate mountain phase toward conditions with compound extreme hazards (flash floods and heatwaves).

Abstract Heavy rains cause large floods that damage many natural resources needed by humans. In this research, the goal is to reveal synoptic patterns of heavy and super heavy rains in Lorestan Province. To this aim, daily precipitation data from Dorood stations and ECMWF climate database were used. Using percentile method, heavy rains at the 95th percentile and super heavy rains at the 99th percentile were determined. By applying the percentile method to the daily rainfall, two samples of super-heavy (March 27, 2007; April 1, 2019) and two samples of heavy rainfalls (February 3, 2006 and January 9, 1999) were extracted. The results showed that more than 90% of the heavy rainfall cases and more than 70% of the monthly rainfall were recorded in 24 hours. The results of the analysis showed a deep trough over the eastern Mediterranean Sea and western Iran in the super-heavy events, which has prepared the conditions for the ascent air mass and entry of low-pressure systems in the western part of the country. However, in this study, the establishment of a low-altitude blocking system cut off at the atmospheric mid - level has provided the conditions for heavy rainfall events in January and February.

Abstract Analysis of climatic changes in semi-arid regions requires the detection of nonlinear behaviors and structural breaks. This study was conducted with the aim of simultaneously detecting uniform trends and regime shifts in temperature and precipitation in Kermanshah Province. Annual mean temperature and precipitation data from 12 synoptic stations were extracted for the period 1989–2018. First, uniform trends were estimated using the Mann–Kendall test and Sen's slope estimator. Then, the Innovative Trend Analysis (ITA) was employed to examine the asymmetry of trends and sub-trends. In a complementary step, the Pettitt and SNHT tests were applied to identify structural breaks. The results showed that annual temperature increased at all stations, with significant structural breaks occurring in the late 1990s and mid-2000s; particularly, Qasr-e Shirin and Sonqor stations showed higher synchrony and significance in temperature breaks. In contrast, precipitation exhibited more scattered and location-dependent behavior, and only in Gilan-e Gharb was a significant break observed in both tests, which was accompanied by a jump in mean precipitation after the break. The before/after analysis showed that temperature increase was evident at most stations after the break points, whereas precipitation changes were heterogeneous in terms of sign and magnitude.

Abstract The wind chill index expresses the degree of real cooling sensation created in the human body, and if this cooling exceeds a threshold it will cause the occurrence of wind chill hazard. The aim of this research is satellite monitoring of wind chill hazard in Iran. In this first step, daily wind speed and air temperature data in the period 1994-2023 for 11,000 days with a spatial resolution of 0.25 by 0.25 degrees of arc were extracted from the ECMWF website. Then, the wind chill index was calculated separately for each day based on the American-Canadian formula. Based on this formula, 3 risk classes were defined for the Wind chill index. The first class was positive values ​​of the Wind chill index, which were without risk. The second class was values ​​between 0 and -9 of the Wind chill index, which were low risk, and the third class was values ​​between -9 and -27 of the Wind chill index, which were named as medium risk. The findings showed that the risk of Wind chill in Iran only occurs in the months of November, December, January, February, and March. This is because in the rest of the year the weather does not cool much and consequently Wind chill will not occur. The findings also showed that due to the prevailing cold conditions at high altitudes, the greatest extent of the risk of Wind chill in the studied region also occurs in the Zagros and Alborz highlands.

Abstract This study investigates the spatio-temporal variations in the frequency of dry days (precipitation < 1 mm) and their longest consecutive spells across Iran during the period 1970–2021, using daily data from 411 synoptic stations. Kriging interpolation was applied for spatial analysis, the Mann–Kendall test for trend detection, and the Alexandersson test (SNHT) for identifying significant breakpoints. Results indicate that the national annual mean frequency of dry days is 328 days, with a minimum of 247 days in the southwestern Caspian region and a maximum of 355 days in western Sistan and Baluchestan. Approximately 62.6% of the country's area experienced frequencies above the spatial mean. A significant increasing trend was observed over 89.12% of the territory, whereas only 10.64% showed a decreasing trend. The longest recorded consecutive dry spell (>600 days) occurred in western Sistan and Baluchestan in December 2016. The Alexandersson test identified 1998 as a significant shift point; thereafter, the mean frequency of dry days increased by approximately 8 days, and the maximum dry spell duration nearly doubled. Anomaly analysis of frequency and duration reveals that these changes predominantly occurred in central, southern, and eastern regions. This pattern aligns with alterations in the general atmospheric circulation over Southwest Asia. The findings warn that Iran is transitioning from seasonal dryness toward more extreme and persistent aridity conditions.

Abstract Dust storms are among the most significant environmental hazards in western Iran, exerting considerable impacts on natural ecosystems, particularly the Zagros oak forests. This study aims to investigate the spatiotemporal variations of dust and analyze its effects on the vegetation condition of oak forests in Ilam Province during the period 2005–2020. For this purpose, Aerosol Optical Depth (AOD) was used as an indicator of dust intensity, while the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) were applied to assess vegetation status and thermal conditions, respectively. MODIS satellite data and Sentinel‑2 imagery were processed within the Google Earth Engine platform. Temporal trends of dust were analyzed using the non‑parametric Kendall’s Tau test, and spatial correlation analysis between AOD and vegetation indices was conducted in the ArcGIS environment.The results indicated that AOD values exhibited interannual variability and increasing trends during certain periods. Spatial correlation between AOD and VCI was negative and statistically significant across large parts of the oak forests, particularly in the southern and southwestern areas of the province, indicating a decline in vegetation condition concurrent with increased dust levels. Moreover, the correlation between AOD and TCI revealed intensified thermal stress under high dust concentrations. The sensitivity map showed that southern areas were most affected, while northern highlands experienced the lowest impact.

Abstract Climate change is a global challenge with wide-ranging consequences for the environment, the economy, and global security. Climate-induced migration at both the domestic and international levels has become a concern, especially as Africa’s vulnerability to droughts, floods, and rising temperatures drives displacement toward European Union (EU) borders. This study examines how such movements affect the EU’s political and security architecture through the Copenhagen School’s securitization framework. It argues that climate change undermines habitats and livelihoods, forcing vulnerable communities to migrate. Externally, these flows have expanded human trafficking networks, increased border pressures, and encouraged stricter asylum policies, turning migration into a security issue. Using a descriptive-analytical method and library-based sources, the research shows that internally, securitization has shifted European priorities and strengthened right-wing parties opposing refugee admission.

Abstract This study evaluates the climate capacity of the southern strip of Iran in 2050. Due to its high climatic sensitivity and the pressures of human activities, this region is considered one of the country’s key areas in confronting climate change, making future climate projections essential. The objective of this research is to identify favorable and unfavorable areas in terms of climate capacity by 2050. For this purpose, the Analytic Hierarchy Process (AHP) method was used. The data used in the study are humidity, wind speed, minimum temperature, maximum temperature, precipitation, longwave radiation, and shortwave radiation from the SSP 245 scenario and the GFDL-ESM4 model on a daily scale. Seven factors were used in the AHP. AHP computations were performed in MATLAB, and spatial maps were generated in R. The results indicate that the northern half of Fars Province and the northeastern part of Khuzestan Province will be the most favorable regions, while Hormozgan Province and the southern half of Sistan and Baluchestan Province will be the least favorable. Among the seven factors, precipitation, temperature, and humidity were identified as the most influential determinants of climatic capacity.

Abstract I
In recent decades, examining precipitation trends at local and basin scales has become increasingly important for water‑resources management and climate‑vulnerability assessment. This study aims to analyze the temporal and spatial patterns of precipitation in the Qezel-Owzan Basin during the period 1994–2023. Monthly and annual precipitation data from ten selected meteorological stations were compiled, quality‑controlled, and interpolated into continuous precipitation surfaces using the IDW method within a GIS environment. To identify long‑term statistical trends, the Mann–Kendall test and Sen’s slope estimator were applied, allowing the detection of significant directional changes. Results indicate that the long‑term mean annual precipitation of the basin is approximately 350 mm. The most pronounced declines were observed in the southern and southeastern sectors of the basin, whereas stations located in the higher northern elevations recorded more moderate variations. Spatial analysis further suggests that declining precipitation patterns are associated with reduced moisture influx from Mediterranean systems, increased frequency of short‑term droughts, and shifts in winter circulation regimes. These findings highlight rising pressure on both surface and groundwater resources and underscore the need for adaptive planning based on future climate scenarios. The outcomes of this research can assist basin managers, agricultural planners, and water‑policy stakeholders in developing strategies to enhance resilience under ongoing climatic changes.

Abstract With the increase in air temperature and global warming, the behavior of atmospheric parameters has undergone significant variations. It is common to use temperature variability to estimate the rate of global warming; however, employing the equivalent potential temperature index provides a more comprehensive and informative understanding. Since this index reflects variations in the atmospheric moisture content and the latent heat resulting from the presence of water vapor in addition to temperature, it serves as a more optimal and suitable tool for analyzing global warming. Accordingly, the objective of this study was to examine the variability of equivalent potential temperature as an indicator of global warming at the Marivan synoptic station, which is located near Lake Zarivar. To achieve this goal, daily data of atmospheric parameters from the Marivan synoptic station for the period from January 1, 1993, to December 31, 2024, were used. The findings of this study showed that due to the role of atmospheric water vapor and the proximity to the water body of Lake Zarivar, the values of equivalent potential temperature at the Marivan synoptic station are higher than air temperature values. Moreover, the rate of increase in equivalent potential temperature is greater than that of air temperature, with an upward trend of 1.3°C per decade, indicating a rise in atmospheric water vapor and evapotranspiration.

Abstract The role of human activities on exacerbating climate changes and human society's exposure to the risks is the main reason to deal with the phenomena as the most priority among the world's problems. These changes are due to dramatically increasing greenhouse gases in the atmosphere during last century. Climate change is mainly known as increasing in global temperature. Melting of polar ice, rising of oceans level, long-term droughts, water resource depletion, storms and flash floods, extreme temperatures, increasing of dust and air pollution. Following repeated warnings by scientists in 1992, "United Nations Convention on Climate Change" was held by United Nations to address this issue. In order to stabilize concentration of greenhouse gases in the atmosphere to a certain level, the convention arranges an annual conference entitled "Conference of the Parties", in one of the member countries. In this study climate change and its risks and the importance of holding this conferences are discussed. Challenges to be faced and the actions to be taken related to this issue were also examined.

Abstract The purpose of this study was to Analysis of Inversion Indicators of Boundary layer in Shiraz. In this regard, radiosond data was provided at 3.5 local time in the 1380-1394 solar. Then, the height of the meteorological station in Shiraz (1491 m above sea level) was determined as the base of the inertia of the boundary layer of the air and the boundary layer was up to the surface of the geopotential of 700 hp (an average of 1.5 km from the lower layer of air above ground) Selected as the study space. The results showed that October and November are the highest and July's low frequency of inversion days. On this basis, the autumn, winter, spring and summer seasons were the most days of inversion, respectively. After determining the inversion days frequency, thickness, gradient, adiabatic and inversion intensity were calculated in each day. The results showed that October and November are the highest and the lowest of the days of inversion in July. On this basis, autumn, winter, spring and summer were respectively the most invasive days, respectively. The highest inversion gradient occurs in September and the lowest in January. The highest lapse rate is in March and the lowest is in July. This feature is in consonant with the fact that cold weather is more intense than warm weather. At the end, of months were classified according to the inversion intensity. The results showed that the strongest inversions in the January and the lowest in the July occur.

Abstract The aim of this study is to investigate synoptic change's monsoon system, South East Iran. Since precipitation is indicative instability and influx moisture, Precipitation's sweeping of the area was considered as a base to expand monsoon into Iran. The data include precipitation in synoptic, rain-gauge stations and NCEP-NCAR data. Grad's software was used for mapping. The results showed that in surface, the establishment of a broad low pressure in the Persian Gulf, Pakistan and expansion tab of Turkey high-pressure for a trough along the Zagros is responsible for the spread of monsoon. In 500 ha in events 1, 2 and 4, create a trough and positioned in the eastern areas in front its and in the third event the sawed-off tabs Russia for Cutoff low on Afghanistan, caused monsoon system penetration into the Iran. The profile of the area Omega is representing negative Omega at this time. Following lines showed the establishment the cyclone over the Indian Ocean in events 1, 2 and 4 and on Afghanistan in event 3 the groundwork for expanding the monsoon system. Events 1, 2 and 4 field of shared water systems that come from India, while the event 3 moisture is provided from Afghanistan that actually the tab moisture that has penetrated through India to Central Asia. Furthermore, monsoon expanded with positive vorticity is at ground level and negative vorticity at 500 hPa level.

Abstract In this study, hourly data of dew point temperature from 162 stations of the country, which had more than 10 years of data, were extracted from the database of Iran's Meteorological Organization during the period from 1951 to 2010. The hourly dew point temperature data includes 8 times and daily mean. Different methods can be used to assess the time series behavior of climate data. In this study, in addition to the linear regression trend test, a frequency analysis method was used to evaluate the dew point temperature behavior over the past few decades. For estimating the trend, the smoothed average of the hourly data was used and for frequency analysis, the daily mean dew point temperature was used.
In frequency analysis, the statistical period was divided into six decades according to the Julian calendar, and then, the frequency and percentage of frequency of the data were calculated. The distribution of the temperature of the dew point of the first decade was compared with subsequent decades.
A review of the decade to decade of dew point temperature in Iran has shown that, in general, its temporal behavior is changing. The percentage of distribution of the dew point temperature has shifted to low temperatures. Analysis of the linear regression test on the smoothed series the hourly dew point temperature showed that 18, 21 and 00 hours had a weakening trend. While at 03, 06, 09, 12, 15 and the average daily, a steep slope has occurred. The average dew point temperature in the solar decades of 30-60 degrees was about 5 degrees Celsius, and in the 1980s the solar fluctuated around 3.8 degrees Celsius. This decrease was accompanied by a sudden drop in the late '60s, which could be a sign of the drying of the moisture content of Iranian atmosphere.

Abstract Climate change in form of the rainfall pattern transformation has disrupted the different dimensions of the countries national security. Meanwhile, increasing the temperature and reducing the rainfall in those of countries where located on the world desert strip, have had the most impacts on environmental security especially their food production and security. The available date in our country shows that groundwater levels have been decreased because of changing the rainfall pattern during two recent decades and increasing the water consumption. In between, increasing the temperature and decreasing the rainfall during two past decades has had the great impact on the central catchment area. This study focuses on the analyzing the effect of climate change on the food security in the jeroft city. This article with its functional nature is based on this mean hypothesis that food security in this part of country is effected by climate change in form of transforming the rainfall pattern especially increasing the temperature and decreasing the rainfall. The methodology of this text is descriptive- analytical. Its data have collected by library method and analyzed by statistical software R. The result of the study showed that climate change has a positive and significant effect on food security in southern Kerman province with a significant level of 99%.

Abstract Rising greenhouse gases and subsequent global warming are among the problems leading to climate change. It directly affects various factors related to human life, so in the present study, the data of the fifth report of CSIRO model under three scenarios RCP8.5, RCP4.5 and RCP2.6 for the next period 2020 2100 as well as two LARS scaling methods WG and Delta method were used to simulate precipitation, minimum and maximum temperatures in East Azerbaijan province. In evaluating the LARS WG model, the error rate of simulation and survey data was evaluated using MSE, RMSE and MAE performance criteria as well as the coefficient of determination and correlation. The results showed that the model is able to predict maximum and minimum temperature parameters with high accuracy, but shows less accuracy in simulating precipitation than other desired variables. Also in Delta Method, the maximum and minimum temperatures are observed for all seasons with an increasing trend, while in the LARS WG model there is a decreasing trend in the next period (2020 2100) for all scenarios. In general, the difference between the operating modes and the LARS WG model for maximum and minimum temperature values in the next period, depending on the type of emission scenario, was obtained between 3.89, 6.33, 7.17 and 2.84. C, respectively. Rainfall has been declining in most seasons under the release scenarios compared to the LARS WG model.

Abstract In this survey, we recognize synoptic patterns which lead to comprehensive and heavy rainfall from March 16th-31st, 2019 in Iran. Therefore, data of earth and the upper atmosphere have been used. The earth data include precipitation amount of stations in the flood zones of Iran. The upper atmosphere data consist of patterns in ECMWF. Three heavy rainfall systems heavy rains in Iran, have been examined. Results shows that the establishment of Cut-off Low plays an important role in heavy rains. In the first system which is stimultaneous with the flash flood of Golestan, a transferring of dynamic low-pressure of system and its cyclonic circulation make rainfall start. The speed of circulation system was reducing, when it established over Caspian Sea and under the influence of pressure Gradiant, humid currents in the low-level of atmosphere have been moved to south and east side of the coast. In this area, heavy rains generally take place in a clod front which transports a large amount of humidity from the sea to Golestan with increasing perssur Gradient between Siberian high and Cut-off Low pressure under the influence of convection currents. A merger between low-pressur of Sudanese and Mediterranean is the main factor for the second and third systems. Heavy rains in the west side of Iran happen, because of an establishing of blocking system in the middle-level and making Cut-off Low which lasts for a few days, with transportation of humidity from various sources.

Abstract Three major challenges, include climate change, water resource reduction and desertification. The preparation of daily or up-to-date maps of salinity and mineral changes can play an important role in the proper utilization of water resources Underground water is the most important source of water supply for agriculture in arid and semi-arid areas.For optimal management of water resources as well as maintaining and improving their quality, Location, volume and pattern data of water quality is needed in each specific geographic area. The aim of this study was to determine the most appropriate interpolation method and spatial analysis to evaluation of the groundwater salinity in Great Plains Yazd - Ardakan which is located in the center Yazd province. In order to study the salinity changes of groundwater in this area, the data of 18 years old (1376 to 1392) were used for salinity of the district water wells. After normalization and correction of incomplete data using + GS software best variogram model was chosen. extrapolated the most appropriate method of Geostatistical methods, kriging methods (ordinary) algorithm due to high value (R2) and low error (RSS) to prepare maps And finally salinity maps, GIS software changes and limitations in drawing groundwater salinity maps. Salinity maps show that ultra-high salinity (above 8 dS / m) in the central, north and northeastern parts of the area due to the construction of multiple wells and a long harvest period, as well as in parts of the south-east is located. The western and southwest margins consist of low salinity (less than 2 dS / m) and the rest of the basin is medium to high (4 to 8 dS / m) salinity.