Climate Change and Climate Disaster

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 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 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 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 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 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 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 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 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.