Reliable precipitation data are fundamental for climate and hydrological research, especially in regions with sparse ground-based observations. This study evaluates and compares the accuracy of two satellite-based precipitation products-CMORPH and GPCP-across daily, monthly, and annual scales over Iran. Daily, monthly, and annual precipitation estimates from CMORPH and GPCP were validated against observations from 128 meteorological stations distributed throughout the country. The assessment employed two statistical indices-correlation coefficient (CC) and root mean square error (RMSE)-alongside three categorical indices: probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). At the daily scale, CMORPH outperformed GPCP in terms of CC, RMSE, POD, and CSI, while GPCP exhibited a lower FAR. At the monthly scale, correlations between satellite-derived and station-based precipitation were stronger than those at the daily scale; CMORPH achieved the highest correlation (CC = 0.84), whereas GPCP yielded a lower RMSE, with a mean value of 26.2 mm. At the annual scale, GPCP demonstrated better performance in CC, while CMORPH showed superior accuracy in RMSE. CMORPH consistently underestimated precipitation, whereas GPCP tended to overestimate rainfall across Iran. Although both datasets provided reliable precipitation estimates at the national scale, CMORPH demonstrated higher overall accuracy and efficiency. Its superior performance across most indices makes CMORPH the more suitable dataset for precipitation monitoring in Iran, despite its tendency to underestimate rainfall relative to ground observations.

The Alborz Mountain range, serving as the strategic water tower of the Iranian Plateau, is experiencing the accelerating impacts of climate change. Given the critical role of snow reserves in this region for water security, understanding the mechanisms of snow degradation in response to warming is essential. Aiming to investigate the divergent responses of snow cover and snow depth to extreme temperature indices, this study analyzes a 23-year time series (2001–2023) of ERA5-Land data and MODIS imagery across 11 elevation bands. To this end, trends and correlations among the Warm Spell Duration Index (WSDI), the Percentage of Warm Days (TX90p), the Normalized Difference Snow Index (NDSI), and Average Snow Depth (ASD) were assessed using the Modified Mann–Kendall (MMK) test, Generalized Linear Modeling (GLM), and Spearman’s rank correlation. The findings reveal elevational heterogeneity in the snow regime of the Alborz. Notably, the decline in spatial snow cover (NDSI) is primarily concentrated in the mid-elevation transition zone (2000 to 3000 m), whereas the reduction in snow depth (ASD) is a widespread phenomenon, observed even at high altitudes above 4000 m. A key innovation of this research is demonstrating the dominant role of heat frequency over heat duration; GLM results indicate that the TX90p index (frequency of warm days) has a much stronger negative correlation with the degradation of snow resources than WSDI. These results confirm the transition of the Alborz hydrological system toward instability, the upward shift in the snowline in the transition zone, and the invisible thinning of the snowpack at higher elevations.

Teleconnection patterns, as major large-scale climate signals, can influence dust sources, transport pathways, and the intensity of dusty days (DD). Understanding these relationships helps improve the identification of dust origins across different time intervals. The main objective of this study is to examine the influence of teleconnection patterns on the temporal and spatial frequency of dusty days in Iran. Using data from 44 synoptic stations (1968–2023), twelve teleconnection indices- including Arctic Oscillation (AO), North Atlantic Oscillation (NAO), East Atlantic/Western Russia pattern (EAWR), Pacific Decadal Oscillation (PDO), Mediterranean Oscillation (MO), etc.- were analyzed using correlation analysis, multiple regression, Path Analysis (PA), and Transfer Entropy Analysis (TEA). The results indicate that ENSO (Nino 1 + 2, Multivariate ENSO Index (MEI)), EAWR, and Mediterranean Oscillation Index (MOI) exert the strongest influences on dust activity, particularly in the southern and western regions during spring and summer. Northern Hemisphere indices such as AO and NAO generally show inverse relationships with DD frequency, whereas Southern Hemisphere signals tend to exhibit positive associations. The combined use of PA and TEA highlights both linear and nonlinear pathways of information transfer between climate indices and dust variability. Although teleconnections explain only 10–15

Global warming increases evaporation and atmospheric water vapor, leading to more extreme events in both spatial and temporal domains. This study conducts a non-stationary extreme value analysis of the annual daily maximum at 36 meteorological stations over Iran from 1960 to 2021. We applied stationary and non-stationary Generalized Extreme Value (GEV) models within a Bayesian framework to estimate return levels for rainfall extremes, along with 90% confidence intervals. Our findings indicate that non-stationary models are not prominently evident based on AIC at most stations; however, non-stationary Generalized Extreme Value (GEV) models outperform stationary models based on RMSE and NSE evaluation criteria that sufficiently capture variations in extremes. Furthermore, most observed changes in extreme events exhibit a non-stationary pattern. Non-stationary analysis indicates that the frequency and severity of rainfall extremes have shown both increasing and decreasing trends, characterized by inconsistent spatial patterns.

In this study, the frequency of merging events between the polar-front jet stream and the subtropical jet stream, along with their impact on precipitation patterns in western Iran, was analyzed over a ten-year statistical period (2010–2019). Utilizing coding in GrADS, 300 hPa jet stream maps were produced at six-hour intervals. Throughout the study period, the axes of these two jet streams merged on several occasions. An examination of the frequency of merging indicated that, prior to 2015, the frequency of merging in December exhibited an increasing trend. However, this trend diminished in 2016 and 2017, only to experience a resurgence in 2018 and 2019. It is noteworthy that not all instances of jet stream merging resulted in significant precipitation events (e.g., December 2011, 2014, and 2017). For instance, in light of the substantial rainfall of 110 mm recorded at the Dehloran station, the period from December 12 to 15, 2010, was selected for detailed analysis to elucidate the atmospheric mechanisms responsible for the rainfall. From December 12 to 15, 2010, a decline in air temperature over Europe and Southwest Asia prompted a considerable meridional displacement of the polar-front jet stream, resulting in its merger with the subtropical jet stream. On December 12, 2010, as the polar-front jet stream underwent meridional movement and extended into tropical regions, its velocity core merged with that of the subtropical jet stream over the northern Arabian Peninsula, the Red Sea, and northeastern Africa. The convergence of these two jet streams led to a vertical expansion of the jet stream into lower atmospheric levels. At the mid-levels of the atmosphere, minimal meridional movement was observed. As a result, the Sudan low-pressure system migrated to higher latitudes, merging with the Mediterranean low-pressure system.

Abstract. The unprecedented increase in methane concentration, as the second most important greenhouse gas after carbon dioxide, poses a serious challenge to climate change mitigation policies, while accurate and comprehensive monitoring remains insufficient in many countries, including Iran. This study investigates the spatial and temporal patterns of column-averaged methane in Iran using satellite-based observations from Tropospheric Monitoring Instrument on the Sentinel-5P satellite during 2019–2024 and compares them with data from the Emissions Database for Global Atmospheric Research database. On average, XCH₄ concentrations across Iran increased from 1872.6 ± 11.9 ppb in 2019 to 1918.6 ± 11.2 ppb in 2024, representing a +46.1 ± 16.4 ppb rise over six years. All uncertainty estimates represent standard deviations, with a mean value of 12.3 ppb. Statistical and spatial analyses, including Global Moran’s I (0.914–0.982, p < 0.01), Local Moran’s I, and the Getis-Ord Gi* hotspot analysis, confirmed that methane concentrations in Iran exhibit a significant clustering pattern. Hotspots were mainly observed in Class 1: Northern Agro-Hotspots (Gilan, Mazandaran, and Golestan), Class 2: Central Urban-Dense Hotspots, and Class 3: Southern Industrial-Fossil Hotspots, whereas Class 4: Low-Emission Provinces and Class 5: Very-Low-Emission Provinces exhibited lower concentrations with sparse hotspots, located mostly in western and eastern Iran. The highest seasonal averages were recorded in summer (1914.3 ± 13.1 ppb) and autumn (1910.5 ± 13.5 ppb). Comparison with EDGAR data indicates that several major emission sources are underestimated, and spatial overlaps with the observed hotspots did not exceed 5 % in any month. Satellite observations reveal discrepancies in hotspot locations and emission magnitudes, emphasizing that relying solely on modeled inventories may misrepresent methane emissions.

High-resolution data can help us better understand the patterns and temporal variations related to drought. This research examines drought trends in Iran utilizing the self-calibrated Palmer drought severity index (scPDSI) and high-resolution TerraClimate data (4 km resolution) from 1958 to 2022. Based on the scPDSI index, a total of 558 drought occurrences were identified. Drought migration distance showed a decreasing trend (− 42.135 km/year), indicating that droughts are becoming more stationary, intensifying local impacts. Conversely, drought duration and affected area increased (0.0767 month/year and 41,055 km2/year, respectively), suggesting longer-lasting and more widespread droughts. On the interdecadal scale, the drought magnitude demonstrated a cyclical pattern of increase–decrease-increase from 1958 to 2022. For the most severe drought event, from February 2021 to December 2022, the starting and ending places were in the east, northwest, and then in the middle of the country, respectively. The movement or migration direction was more clockwise, roughly along with the direction of east to northwest and then east. This analysis shows that the distribution pattern of drought throughout the year has changed according to different seasons and months, and the spring and winter seasons are more severe. In recent decades, the most severe drought clusters—based on scPDSI—have been primarily concentrated in the west, northwest, and the central Alborz. However, previous studies using other indices (e.g., SPEI) have also highlighted southeastern and central Iran as highly vulnerable to extreme droughts. Observations indicate that moderate to severe droughts have significantly increased, such that since 1999, the scPDSI index has frequently dropped below threshold − 2 in most years, indicating the persistence of moderate, severe, and extreme droughts across the country.

Despite global warming, cold waves (CWs) remain one of the most severe, frequent, and damaging climatological hazards in most regions of the world. In this research, the most intense and widespread CW in Iran during the statistical period of 1836–2015 has been identified and analyzed. To identify and analyze the synoptic patterns of CWs, the following data were used: Minimum Daily Temperature (MDT) at the 2-meter land surface, Sea Level Pressure (SLP), Geopotential Height (GH) between the 1000 and 500 hPa levels, atmospheric thickness maps (500 to 1000 hPa), and temperature data from the lower and middle levels of the atmosphere. These data were obtained from the daily reanalysis dataset of the gridded NOAA-CIRES-DOE 20th Century Reanalysis V3. The criteria for selecting severe CWs include a temperature threshold of -20 °C or below, a wide spatial extent (regional or covering at least half of Iran), and a duration of at least two days. Based on the determined intensity and extent index, the most severe and widespread extreme CW in Iran, which occurred in January 1925, was selected for synoptic analysis. The synoptic analysis of the selected wave revealed that the extreme CW was caused by the combined influence of the Siberian high-pressure system and a migrating western high-pressure system with a pressure of 1030 hPa. The main cold core featured a high-pressure system of 1035 hPa associated with the migrating western system at the surface level. At upper atmospheric levels (1000 to 500 hPa), a blocking pattern over the North Atlantic Ocean played a significant role. The arrangement of these systems directed very cold northerly air currents toward Iran. At the 1000 to 850 hPa levels, wind flow divergence and temperature gradients caused the cold air to settle. Meanwhile, at the 700 and 500 hPa levels, blocking and the descent of cold air from the polar region and North Scandinavia, combined with a deep trough over Iran, were the primary factors contributing to the cooling and the occurrence of the extreme CW in January 1925.

Pollen study is considered one of the most climate proxies distributed worldwide since the beginning of the last century. Some areas and regions still lack such proxy studies, the main objective behind this review is to investigate and draw a picture of the past climate and vegetation pattern in northeastern Iraq, where the area obtains only a few small in size natural Lakes, Fellaw Lake is the largest mountain natural Lake in the area considered within the study. In addition, there are tries to present the paleoclimate of the study area depending mostly on the bulk of research conducted near the area due to the nonexistence of pollen studies implemented on Fellaw Lake yet. Accordingly, and after matching the modern and past vegetation patterns of some adjacent lakes to the area such as Zaribar, Merabad Van Lake, and Akgol Lake, the area likely obtains to some extent a similar past climate trend and events and vegetation components, regardless of the factor of variation in latitude and topographic effects which in turn affect the precipitation amount that could lead possibly to variate of vegetation patterns in these conditions. Ultimately, the study area is located in a very climate-sensitive area, where it’s situated among the following regions; Levantine from the west, Mesopotamia from the south, Anatolia from the north, and itself located in the eastern edge of the Irano-Turanian region. This in turn could consider the area to be a refuge for other regions in case of climate deterioration and fluctuations in the late Quaternary.

In this study, for statistical studies to determine days whit temperature above 50°c, the reanalyzed data of the nineteenth, twentieth and twenty-first centuries for the West Asia region (12 to 42.5 degrees north latitude and 36 to 63.5 degrees east longitude) have been used. Also, for synoptic analysis of extreme temperatures, HGT, AIR, UWND, VWND and SLP data were used. To conduct this research, first, extreme temperature data above 50° during the last 185 years were extracted for the study area in the hot season (June, July, August and September). After identifying days whit above 50° c, HGT data at the level of 500 hp were extracted and WARD clustering was applied. Finally, after identifying the clusters, the days whit the highest temperature that occurred in each cluster were selected for synoptic analysis. It can be said that all altitude patterns of geopotential meters (HGT) at the level of 500 hp show that the main cause of occurrence and distribution of temperatures above 50°c in West Asia are high-altitude (high-pressure) subtropical West Asia, which due to the location of its high-pressure core on the Zagros and sometimes the Arabian Peninsula, it has been referred to as the Zagros or Saudi high-pressure in terms of interest and taste. What is certain, however, is the high-pressure independent identity of the subtropical Azores, which has been mentioned in numerous articles and is known to be the main cause of the heat in the West Asian region, especially Iran.

Among the world's most essential natural environmental resources are wetlands. In Iraq, the Mesopotamia marshes are considered as among the most significant swamplands worldwide. They are situated in the massive flood plains of the rivers Tigris and Euphrates in the lower basin of Mesopotamia. In this paper, there will be a thoughtful study of the effect of climate and microclimate change on these Marshes. The main sources of data and scientific knowledge will be gathered and summarized from almost all previous research conducted in the area. Most of the papers involved in this summarized study are those related to remote sensing, since remote sensing tends to be the most effective approach as it is less costly and consumes less time. Most of the reviewed papers that have studied the marshland circumstances of the area showed a deterioration in the level of the area's water bodies due to climate change. However, there are other factors that influence and degrade these marshlands other than the effects of climate change. These extra factors are represented by the political and military actions conducted by the previous Iraq regime during the middle of the 1980s. According to most of the most research implemented in the area, the water system in Iraq is experiencing significant challenges, thus increasing concerns about the Mesopotamian marshes that have been sustaining the region for thousands of years and which may possibly vanish soon.

The present study quantifies for the first time the statistical relationship between aerosol properties with Cloud microphysical Properties (CPs), and consequently effect on precipitation over Iran. The daily means of Aerosol Optical Depth (AOD), Angstrom Exponent (AE), and CP including Cloud Fraction (CF), Cloud Top Temperature (CTT), Cloud Top Pressure (CTP), Cloud Optical Thickness (COT), and Cloud Effective Radius (CER) were obtained from the MODerate resolution Imaging Spectroradiometer (MODIS). The precipitation was retrieved from Tropical Rainfall Measuring Mission (TRMM) during 2003-2019 for 156 1 x 1 geographical degree grid-points over Iran. The different types of aerosols including the dust and fine aerosols were separated using the AOD and AE values for each season. We identified grid points, which had statistically significant correlation (at the 5% level) between aerosol modes and at least one of CPs, the precipitation and one of CPs, and between the precipitation and aerosols modes, at the same time. With this approach, we identified 10 points showing a statistically significant relationship between AOD, CPs, and precipitation, stimulatingly. For instance, at a point in the southwest of Iran, the correlation coefficient between the AOD with precipitation (r = 0.54), AOD with CTP (r = -0.51), and precipitation with CTP (r = -0.61) were statistically significant simultaneously. Based on statistical calculations, the relationship between precipitation and AOD (for 10 points) is often positive, which indicates the positive effect of aerosols on precipitation. However, in two points, the relationship between precipitation and AOD is negative, and subsequently significant. In addition, a negative correlation coefficient is also observed between CTT and CTP with AOD, as well as a positive relationship between AOD and COT for both fine (black carbon) and coarse mode (desert dust) of aerosols over Iran. Due to the lack of ground station data in Iran, this study can serve as a starting point to better understanding the complex, and uncertain response to cloud, radiation and precipitation to aerosol over arid region of Iran.

The aim of this study is to investigate long-term spatial changes (LTSC) of monthly maximum temperature (MMT) using NOAA-CIRES-DOE Twentieth Century Reanalysis data and different Kriging methods (KM). In this study, MMT data for 2 m above the ground during the 1836–2019 period were applied, and for spatial analysis, various KMs (ordinary, simple, and general) were used. Also, to determine the pattern of MMT distribution, the global and local Moran’s Spatial Autocorrelation Method (MSAM) was used. The results showed that the simple Kriging method with Gaussian semivariogram model has the lowest error among all methods and best explains the pattern of spatial distribution of MMT in Iran. Therefore, this method was used to map the interpolations. Interpolation maps show that the MMT distribution of Iran is a spatial function of geographical features. In the northwest of Iran and Caspian coast, it is less, and in the lowlands and plains of the south and southwest, it is more. The results of MSAM also indicate that the MMT of Iran has a cluster pattern. In the southern regions of the pattern, it is high cluster, and in the northwestern regions of the pattern, there is low cluster. According to the results, a decreasing trend of MMT and cold spots has always been observed in the northwestern regions of Iran, and an increasing trend and hot spots of MMT are observable in the southern regions. This is contrary to the results of studies conducted in Iran, which with data of up to 60 years show that the pattern of MMT distribution in all regions of Iran is increasing.

One of the characteristics of arid and semi-arid regions is low rainfall and lack of uniform distribution throughout the year, which has a direct effect on water resources in these regions. In this research, daily precipitation and flow rate data of 39 meteorological stations and 9 hydrometric stations in the period 1994–2015 have been used. To evaluate seasonal and annual changes, the average data was calculated, and also MK and SQMK tests were used to detect the type of trend and mutations of changes. Sen slope, correlation, and Pettitt tests were used to determine the slope of changes, type of relationship, and also to determine the breaking point in the data time series, respectively. The results show that in all seasons, Tashk, Bakhtegan, and Maharloo sub-basins had the highest average rainfall; however, flow rate and precipitation changing curve in this region has decreased. The time-changing curve in precipitation is decreasing in winter and spring and increasing in summer and autumn. Thus, the spatial study of the udic moisture regime shows an increase in systems' activity that affects the region in the hot (summer) and cold (autumn) seasons. The trend of leap changes in winter and summer (autumn) in 7 sub-basins with 95% confidence level has been decreasing (increasing) which has decreased (increased) the river water flow in these areas. The highest percentage of decreasing and increasing changes in precipitation is in region 9 with values of − 6.66 and 2.55. The trend of leap changes in annual precipitation and flow rate in 5 sub-basins with a 95% confidence level has been reduced. The decrease in rainfall in areas 8 and 9 have had a direct effect on flow rate and has caused a significant decrease. The correlation between rainfall and flow is positive in all sub-basins and the highest coefficient of determination is in regions 3 and 9 with 40%.

The human body can withstand high temperatures to some extent, but exposure to temperatures exceeding human heat tolerance leads to sickness and, at very high temperatures, to death. In this study, using the analyzed data on the maximum temperature at 2 m above the surface in a 73-year period from 1948 to 2020, the seasonal, annual, decadal and centennial frequency of lethal temperatures above 50 °C (TU50c) in the Northern Hemisphere (NH) was analyzed. The aim of this research was to extract the frequency and trend in TU50c in the NH. In this study, regression analysis, trend component analysis and wavelet analysis were used. Examination of the frequency of TU50c occurrence in the NH showed that the trend of annual changes in the frequency of TU50c in the NH is upward and significant. Inter-decadal changes indicate that in the fifth decade (1980–1989) and sixth decade (1990–1999), there was an unprecedented increase in the frequency of TU50c. Inter-century changes also show that the incidence of TU50c has increased gradually from the twentieth to the twenty-first century. The highest incidence of twentieth-century TU50c extreme temperatures occurred between 1986 and 1988. Spatially, the region with the highest frequency and strongest TU50c is in Africa, especially Sudan, West Asia (between Iraq, southwestern Iran, Kuwait and Saudi Arabia) and India in the Indian subcontinent. These temperatures are not uncommon in the United States, but TU50c has not been reported in Europe and East Asia. The results of statistical analysis show that the frequency of occurrence of TU50c in the NH is related to the annual frequency of sunspots and also, to a much lesser extent, to the concentration of carbon dioxide.

Droughts are one of the most catastrophic environmental hazards that have historically led to the destruction of many ancient civilizations in the cradle of civilization in the West Asian region. The purpose of this study is to analyze the long-term temporal and spatial variability of extreme long-term drought intensities of 18 to 48 months in the West Asian region in the statistical period of 118 years (1901–2018). In this study, using standardized precipitation evapotranspiration index (SPEI) and accurate gridded data, the critical grid points (CGPs) caused by extensive and severe droughts in West Asia in the 118-year long-term period (1901–2018) was analyzed. The results of the cumulative standardized precipitation evapotranspiration index (CSPEI) showed that in the long-term timescales of SPEI-18, SPEI-24, SPEI-36, and SPEI-48 months, the most affected areas of severe drought or the drought CGPs of West Asia were located in Yemen, Southern Iran, and western Saudi Arabia. The Southern and Western regions of Turkey, Northwestern Turkmenistan, Western Pakistan, and Afghanistan, as well as Western Oman and Azerbaijan, have also been less impacted by severe and widespread droughts in West Asia. Moreover, Armenia was found to experience fewer severe droughts than other study areas. The trend of temporal changes in the CGPs derived from the severity and extent of droughts indicates a significant downward trend in the CGPs of droughts in West Asia, which points to the fact that severe and widespread droughts will continue in the future and are likely to intensify. In other words, in the future, investigators will see more widespread and more severe droughts in the West Asian region, especially in Yemen, Iran, Saudi Arabia, and Iraq.

Dust aerosols can sometimes extend thousands of kilometers continuously in the atmosphere. In this study, we refer to these dust streams, as Atmospheric Dust Corridors (ADCs). This study aims to identify ADCs by an automated algorithm and investigate their temporal and spatial characteristics in the Middle East. In order to do this, the Aerosol Optical Depth (AOD) and Angstrom Exponent (AE) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) (Aqua) were obtained on a daily scale at a resolution of 1*1° between 2003 and 2020. In this study, observations with AOD above 0.3 and AE below 0.75 were considered as dust aerosols. After determining a set of conditions, an algorithm was developed to identify the ADCs automatically. In the first step, the dust masses were identified using the connected components labeling method, and the largest dust mass was selected from each day. Then, a set of conditions were examined such as geometric shape and motion of the dust mass (based on wind data). As a result, we identified 281 ADCs and classified them according to their direction of movement. We found 33% cases of ADCs that flow toward the west, 19% cases that flow toward the east, 36% cases that flow toward the south, and 12% cases that flow toward the north. All the directions had the highest frequency in September, April, and March, whereas February, November and December had the lowest frequency. Spatially, the highest frequency can be seen around 45°E over Saudi Arabia, Iraq, and Syria. Western and southern ADCs are primarily found in the Arabian Peninsula and in Iraq, Syria, southern Iran, southern Afghanistan, and northern Pakistan, while northern and eastern ADCs are primarily found in northern Africa (Sudan and Chad, Niger, and Libya). May is important for western ADCs, September for southern ADCs, and April for eastern and northern ADCs. According to the Mann-Kendal test, no significant trends were observed on a monthly or annual basis during the studied period.

The present research has been performed for the temporal-spatial reconstruction of an extreme cold episode (temperature anomaly − 15 °C) occurring over the northwest part of Iran for a 142-year period (1871–2012). In carrying out the following investigation, the NOAA Twentieth Century (V20) reanalysis data including mid-level and sea-surface-level data were used. In order to achieve the research goals and extract the sea-surface and mid-troposphere patterns, the methods of hierarchical clustering and factor analysis were utilized. The results showed that during the 142-year period, a total of 791 days were identified in which temperature of − 15 °C or lower occurred. For the synoptic analysis, 183 of these days during which the temperature anomaly was widely observed across the study area were used. The results demonstrated that for most of these days, a surface high pressure system over Asia Minor and northwest Iran contributed to extreme low temperature. These high-pressure systems, whether individually or as part of an extended episode of occurrences, affected the study area. Furthermore, the upper air level study demonstrated that the occurrence of atmospheric blocking or high latitude troughs located to the northwest of Iran (or upstream) and extending into the study area were the main causes for these low temperatures.