سید ابوالفضل مسعودیان

Aerosol optical depth (AOD) is a dimensionless quantity that shows the amount of light passing through the atmosphere and expresses the amount of absorption and scattering caused by aerosols in the path of light passage. Knowing AOD is necessary to understand its effects on air quality and provide a strategy of confrontation with it. South Baluchistan basin is affected by dust and high concentrations of aerosol due to its geographical location. Therefore, in this study, the tempo-spatial changes of AOD in this basin have been analyzed. In this research, the data of the AOD product (MOD 04 L2) and, the Deep Blue algorithm of MODIS sensor of Terra satellite during the period of 2002-2019 were used. Principal component analysis (PCA) and cluster analysis were used for data processing. The results showed that the first component alone explains 84% of the variance of the data. The pattern of temporal changes shows that this component exists throughout the year, but it decreases in the cold period and increases in the warm period of the year. Based on the temporal changes of the AOD, the basin can be divided into four temporal periods: winter, spring-autumn, transitional, and summer. The mean AOD reaches 0.69 in the summer pattern. This means that the basin has relatively dusty weather during the summer. Based on spatial distribution, the basin can be divided into three areas: mountainous, piedmont, and plains. The average AOD in the basin is 0.38, which reaches 0.62 in the plain zone. The AOD regime is the same in all three zones, but the plain zone is significantly different from the other two zones in terms of quantity. The high deal of AOD in this basin is related to regional factors that are active in the warm period of the year (Indian monsoon) in addition to local factors.

The complex process of rainfall-runoff relationship in each catchment area is controlled by numerous known and often unknown factors in the time and place dimension. One of these factors is precipitation. Precipitation is the most important atmospheric phenomenon that is directly affect the hydrological cycle, especially in discharge changes. In this study, in order to investigate the relation between rainfall and runoff and investigating their temporal and spatial variation, the daily precipitation data of 160 synoptic and rain gage stations and 12 hydrometric stations with different statistical period were used for 12 sub basins in Karun. Linear and nonlinear correlation equations between the two elements were calculated. In the final stage, cumulative coefficients of precipitation and runoff and its temporal-spatial correlation were calculated. The results showed that nonlinear transformations did not affect the relation between precipitation and runoff and the relation between the two elements is linear. The height, type of precipitation and temperature affected different influences on the correlation between rainfall and runoff. Also it has been shown that the physical properties of the basin, especially tectonic plates, and the impact of human factors, especially dam construction and water transport, have a great impact on the relationship between them.

In this research, three steps were taken to estimate the solar energy balance on the earth's surface. First, the amount of incident radiation on a tilted surface at the top of the atmosphere was calculated. Then, by using MODIS data, the transmittance coefficients of the atmosphere were estimated and the amount of direct radiation, diffuse radiation and global radiation in cloudless sky conditions were estimated. In the next step, based on the cloud transmittance coefficient, the amount of all sky radiation was estimated. Finally, by estimating the actual albedo of the earth's surface, the balance of solar radiation on the earth's surface was evaluated.The average top of atmosphere radiation in Iran is about 365 Watts per square meter. On a tilted surface, Iran receives 356 Watts per square meter of solar radiation. The difference in the angle of radiation on a tilted surface compared to the flat ground due to the slope of the ground and the difference in the duration of the radiation on a tilted surface compared to the flat ground due to the aspect of slope resulted a 2.5 percent reduction in the amount of radiation in Iran.In Iran, on a clear and sunny day about one percent of solar radiation is lost by air molecules not reaching the ground. The phenomenon of Rayleigh scattering also prevents about 9% of radiation from reaching the earth's surface. Therefore, about 10% of solar radiation is reduced due to atmospheric gases. The presence of aerosols, water vapor and ozone also affect the transparency of the atmosphere to solar radiation. The effect of these gases can be expressed by the transmission coefficient namely the aerosols transmittance coefficient which is low in desert areas of the country and on the coasts of Oman Sea and Persian Gulf and for Khuzestan Plain. In these areas, between 20 and 40 percent of the solar radiation is prevented from reaching the earth's surface by the aerosols. On the other hand, in the heights of Zagros and Alborz mountains and in the heights of Khorasan and in the north-west of Iran, aerosols do not play a significant role in reducing solar radiation. In Iran, the average reduction of solar radiation due to the presence of aerosols is about 17%.As expected, water vapor transmission is minimal at high altitudes, and about 10% of solar radiation is prevented from reaching the earth's surface due to atmospheric water vapor. On the shores of the Oman Sea, Caspian Sea, and Persian Gulf, the amount of attenuation due to atmospheric water vapor is about 14%. In Iran, the average reduction of solar radiation due to the presence of water vapor in the atmosphere is about 11%.The average transmittance of direct surface solar radiation in Iran is about 60%. In other words, the atmosphere prevents about 40% of direct sunlight from reaching the earth's surface. In mountainous areas the transmittance coefficient is the maximum and exceeds 70%. In the southern banks and eastern and central regions of Iran, due to the presence of aerosols and water vapor, the figure is less than 60%. The amount of mean direct radiation in Iran is about 213 Watts per square meter. Diffuse radiation is a small part of the total radiation. The average transmittance of diffuse radiation in Iran is about 10%. Aerosols play an important role in scattering solar radiation. The amount of mean diffuse radiation that reaches the earth's surface in Iran is about 35 Watts per square meter.This study shows that the global radiation in Iran is 248 Watts per square meter. The average transmittance coefficient of global radiation is 70% and follows the configuration of topography and distance from the sea. Average cloudiness of Iran is about 26% and the average ratio of actual to possible sunshine hours is about 72%. On the shores of the Caspian Sea, the cloudiness exceeds 60%. The average cloud transmittance coefficient in Iran is about 83%. In Iran, clouds contribute about 17% in the reduction of radiation. On a cloudy day, the mean amount of solar radiation that passes through the atmosphere and reaches the surface of the earth on a tilted surface is 205 Watts per square meter. The average albedo of Iran is about 21%. Nearly 80% of the solar radiation that reaches the earth's surface is absorbed by the surface. The amount of net annual solar radiation on the earth's surface in Iran varies between 80 and 220 Watts per square meter.

In late March 2019, heavy rains occurred in Iran, which led to floods in several provinces of the country. In this paper, the spring floods of 2019 in the western basins of the country (Karkheh and Karun) have been investigated. These floods brought heavy losses to the country. Nation administration tried to dissect this event and know its causes and consequences. This experience showed that flood is an anthropogenic - physical phenomenon and it is naturally complex like all other human phenomena; Complex, in the sense that it is the result of the interaction of many different components. Here, we have examined partly one of the components of this complex phenomenon, that is, the part of precipitation from the climatological point of view. This investigation showed that the intensity of rain in the spring of 2019 did not exceed the historical events, but the amount of rain received by the basins was unprecedented. Therefore, from a climatological point of view, heavy rainfall and the location of the core of rainfall played the most important role in the occurrence of this flood. The amount of rainfall in the Karkheh and Karun basins in 9 days was equivalent to about 70% of the annual rainfall of these two basins. The establishment of the rain core in the eastern steep part of the basin has also contributed to the intensification of floods.

Vegetation plays an essential role in regional and global ecosystem stability. The change in terrestrial net carbon uptake is principally affected by varying vegetation productivity and the Earth’s climate is regulated by vegetation through evapotranspiration, surface albedo, and roughness. The purpose research is monitoring the trend of vegetation changes (NDVI) in Najaf abad County using Time Series Images and Mann-Kendall test (2003-2019). In this study, 16-day data of normalized vegetation difference index (NDVI) of MODIS Aqua in time interval 2003- 2019 temporal resolution of 500 meters have been used. Mann-Kendall test used for assessing trend of the index in Najafabad County. The results showed that in the first period (2003- 2013) the amount trend of vegetation is moderate and increasing. The peak of amount increase in vegetation 2005-2007. From 2013- 2016 year the increasing- decline trend shows itself in the same way, until from 2016- 2019 year, decline intense trend witness and once in amount of vegetation in this area, once land use changes and climate fluctuations and drought can be considered one of the main reasons the declining trend vegetation in Najafabad County. The greatest trend of declining vegetation in the southern and southeastern as occurred in urban areas, this trend can indicate high urban growth and land use change from vegetation to construction in this county. Aa well as, irrigated cultivation in the county has during the study period intense decline faced, this issue leads to change land use from irrigated cultivation to other uses in the area.

Precipitation is one of the most important and variable elements of climate that has a lot of spatiotemporal variability, especially in arid and semi-arid regions. Adequate knowledge of precipitation variations is crucial for agricultural planning and water resource management in any region. For this purpose, in this study, using the daily data of Asfezari precipitation database during the period 1349 to 1394, the characteristics of precipitation and also the precipitation trends in Yazd province were investigated. The average coefficient of variation of the total annual rainfall of the province was 42.2 and varied from 32.9 to 68.4 in different cells. The highest coefficient of variation of precipitation on an annual scale was observed in the central and western regions of the province, which indicates the greater dispersion and risk of precipitation in these regions. The trend of precipitation was examined using nonparametric statistical tests of Mann-Kendall and Sen’s slope estimator. The spatiotemporal distribution of the trend of total annual Precipitation and total annual extreme Precipitation was similar and in both cases the general trend of the province was decreasing. The highest share of extreme Precipitation in total annual Precipitation was observed in the central regions of the province (Yazd-Ardakan plain). Therefore, in rainy years, these areas have favorable conditions for severe floods.

In this research, the daily data of geopotential height of 500 hectopascals (hPa) with a spatial resolution of 1 degree from the ECMWF database for Southwest Asia and rainfall station data from the National Meteorological Organization (1979 to 2018) have been exerted. The technique used the principal component analysis and cluster analysis. With these analyses, nine circulation patterns were identified. The changes in the patterns were tested at the 95% significance level by the non-parametric Mann-Kendall test, and Sen's slope estimator was exerted to estimate the number of changes. The significance test of the trend for the winter patterns in Iran's rainy season revealed the significant trend of increasing the height of the geopotential, which has led to a decrease in the pressure gradient and a decrease in instability, and finally, a weakening of the winter precipitation patterns. Significant positive trends of geopotential height showed the continuation of these conditions for summer patterns (increasing stability, decreasing rotation, and decreasing precipitation). Of the nine known patterns, only one seasonal pattern showed a significant negative trend in the country. This pattern, with a slight increase in rainfall, indicates the formation of unstable conditions, which can lead to moderate-season rains if moisture is available. The findings showed that a rainy winter pattern had been eliminated in the last two decades, and a summer pattern had appeared instead.

Precipitation and temperature are important elements of climate. Changes in these elements can have a significant impact on the changes in other environmental components, including changes in land use. This study aimed to investigate the long-term changes in temperature and precipitation in the Karun basin. Then the probable relationship between these changes and land use changes was investigated. Therefore, the daily temperature and precipitation data from 177 synoptic stations and 230 rain gauge stations were prepared from 1972 to 2014. Daily maps were made up of 4 x 4 km, using the kriging interpolation method. Due to the climatic and spatial diversity of the Karun, the basin was divided into 12 smaller sub-basins. Using google earth engine (GEE) and using the digital data of Landsat 5, 7, and 8 series satellites, TM, and OLI/TIRS sensors, land use maps were extracted by calculating the mean of each use. For the classification of images, the algorithm of the minimum distance from the mean was used for several years (1987 - 1997 - 2007-2018). To monitor the temporal changes in land use, the dynamic model of land use was also used. The results of the research showed that in the high basins of Karun, the variation in the climatic elements played a significant role in land use changes. In the sub-basins of Karon, the decrease in rainfall over time has had a destructive effect on the degradation of forests, pastures, water levels, and water agriculture in the region. So that in recent years, the amount of destruction of forests and pastures has reached its peak and it is mostly dedicated to aquatic cultivation. The drilling of deep and semi-deep wells and the unprincipled exploitation of the underground water have also caused that over time, Karun faces surface and underground water crises and as a result many economic, agricultural, and social crises.Using google earth engine (GEE) and landsat 5,7,8 images, land use maps were produced. For classification of images, the algorithm minimum distance of mean was used for years of 1987 - 1997 - 2007. In order to monitoring changes of land use, land use dynamics model was used. The results showed that in the Karun basin, the variation of climate elements has a significant role in land use changes. In the Karun, precipitation reduction had negative effects on the degradation of forests, pastures, water levels and aquatic agriculture. So, the destruction of forests and pastures has been increased. The Welles and exploiting the groundwater led the Karun into the surface of the surface and underground water crisis. Extended Abstract Introduction The increasing world population, greenhouse gases emission, and land use changes through dam construction, deforestation, desertification, etc., have caused changes in the climate system. These changes can be effective along with positive feedback on the natural ecosystems and the activity of human societies. Precipitation and temperature are important elements of climate. Precipitation and air temperature are important elements of climate. The change of these two elements can have a significant impact on the changes of other environmental components, including changes in land use. In this study, the temperature and precipitation trend in the Karun basin has been investigated. Then, the possible relation among these changes, temperature, and precipitation was evaluated by examining the decade-long changes in land use.MethodologyTo achieve the objectives of the research, two types of data including ground data and satellite data were used. GEE system was used to monitor land use changes on the surface of the earth using Landsat satellite images. Also, Kendall's test was used to identify the trend of climatic elements. To detect the land use changes, the classification algorithm of minimum distance from the mean was used. Using the dynamic model, the changes in the time series of users were evaluated.Results and discussionThe fluctuations and multiple collisions of Mann-Kendall diagrams showed that precipitation has varying behavior. Changes can be seen in mountain basins such as sub-basins 2, 3, and 4. As the height decreases, the amount of fluctuations is significantly reduced. This shows that height has an influential role in the rainfall changes in the region. The results of classification showed that considerable variation has occurred in subbasins land use. Most changes have been related to changes in water levels, arid regions, and forests. The impact of human activity, including afforestation and the development of hydroponics, the conversion of pastures into agricultural lands, increases the risk of floods, fires, soil erosion, and the entry of polluting substances into water sources.ConclusionIn the Karun basin, the decrease in rainfall over time has had a destructive effect on the reduction of forests, pastures, water levels and water agriculture in the region. So that during the last decade, the amount of destruction of forests and pastures has reached its peak and more is devoted to dryland farming. Also, the occurrence of these changes has led to an increase in the extent of arid areas in the region over time and has reached the maximum possible extent in recent years. In the Karun basin, taking into account that the area under cultivation of irrigated crops has increased and the amount of water in the region has decreased over time, it can be expected that the huge amount of water demand for irrigated cultivation and the lack of water will lead to water stress in the future. The increase in cultivation areas has been in line with the destruction of forests to be used in the agricultural sector. Therefore, from year to year, the extent of forests in the Karun region has decreased.Funding There is no funding support.Authors’ Contribution The authors contribute equally to the conceptualization and writing of the article. All authors approved the content of the article submitted for review and agree on all aspects of the work.Conflict of Interest Authors declared no conflict of interest.Acknowledgments We are grateful to all the persons for scientific consulting in this paper.

Surface albedo is a climatic parameter that is a function of surface type. In this study, to investigate the relationship between albedo and Elevation components in Iran from the combined data (Terra / Aqua) of Modis sensor in the period 3/20/2000 to 3/20/2019 (6940 days) on a daily basis and in a spatial resolution of 500 Meters were utilized. Also, Iran's Digital Elevation Model (DEM) data in spatial resolution of 500 meters and with a sinusoidal projection system coordinated with the spatial resolution and projection system of albedo data were downloaded from the NASA website. In the DEM data used, In data used, in addition to the elevation of the points, the slope and aspect information for each pixel is also in decis. Prior to data usage, some preprocessing was performed on digital data. Based on nearly 60 billion pixels, the albedo and DEM showed a linear fragmentary pattern. The results showed that the amount of albedo has 5 different patterns with increasing elevation. The first pattern shows the whiteness behavior at elevation below sea level. In these zones, albedo increases sharply with increasing elevation due to rising land surface temperature(LST). So that the albedo goes from 4% to about 16%. The second pattern shows the uniform behavior of the albedo at an elevation of 0-800 m. The third pattern of albedo decreasing behavior with elevation is revealed in the 1300-800 m belt. One of the reasons for the decrease in albedo in these elevation belts can be the expansion of cities and consequently the decrease in albedo due to the smooth surface of the asphalt of the streets and the paving of the streets. In the fourth pattern, a direct connection of albedo with elevation is observed in the belt of 3500-1300 meters. One of the main reasons for the increase in albedo in this elevation belt is the increase in snow cover in this elevation belt. The fifth pattern also shows a direct link between albedo and elevation above 3500 meters and is a continuation of the fourth pattern, with the difference that this pattern loses some of its order and shows a scattered pattern. The correlation of albedo and slope also showed that due to more sun exposure, the southern aspect of Iran has about 3% more albedo than the northern aspect. The correlation between the albedo and the slope is a straight line. As the albedo decreases to a slope of 30 °, the albedo will increase on slopes above 30 °.

Geographical situation of Iran is a place for interacting many physical and human processes which lead to specific precipitation climatology in the country. The month to month variation of precipitation is one of  the features which the precipitation climatology may reflect due to tempo - spatial characteristics. In fact, monthly distribution of precipitation is one of precipitation normal features building up the climate structure. In order to recognize this fundamental characteristic three following questions have been raised:1) Have the month to month distribution of precipitation changed over recent four decades? 2) How is the pattern of relationship of month to month distribution of precipitation and spatio - topographical variables? 3) Is it possible to find a spatial pattern for decadal changes of precipitation of month to month distribution?

In order to find a responses for the abovementioned questions the distribution of month to month precipitation and its decadal changes was considered by adopting coefficients of variations (CV) for 46 years (1970-2016)  and using the third version of Asfazari dataset. The relationship of precipitation data and spatio-topographical variables calculated based on regression techniques. Moreover, the spatial pattern considered by using cluster analysis.  The CV calculated as follow: here ،،  are ith raw's and jth column's CV, standard deviation, and monthly mean, respectively. CV and its relationships with spatio-topographical variables were calculated in two temporal scale, for whole the under investigation period (1970-2016) and in decadal period for four decades (1977-1986, 1987-1996, 1997-2006, 2007-2016).

The results of current study proved that the month to month different in precipitation amounts have had spatial variations, whilst the temporal trends is not statistically significant. In addition, the minimum, maximum, and consequently, the range of values also the averages have not experienced significantly changes. However, the region experiencing the same values of precipitation illustrated oscillatory behavior. Accordingly, the decadal variations have happened in different areas. Although the there have been statistically significant relationships between monthly CV and spatio - topographical factors, the correlations were low. Based on cluster analysis, we found 5 regions according to CV and its anomalies in compares with normal CV for all under investigation period. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.

Precipitation is known a chiastic and complicated climate element. One of chiastic behaviors which precipitation shows in its different time - scale behavior is its month to month distribution among a given year. In current research the decadal variation of  above-mentioned behavior among recent four decades and the variation of its relationships and the spatio - topographical features , as parts of climate structure of the country, have investigated in details.  Our finding illustrated that the month to month different in precipitation amounts have had tempo - spatial variations, whilst the temporal long - term trends is not statistically significant. Moreover, the values of minimum, maximum, and consequently, the range of month to month CV also the decadal averages have not experienced significantly changes over four under study decades. However, the region experiencing the same values of precipitation depicted oscillatory behavior. consequently, the decadal variations have happened in different areas. Although there have been statistically significant relationships between monthly CV and spatio - topographical variables, the correlations were not considerably high. Based on cluster analysis technique, we found 5 regions according to CV and its anomalies in compares to normal CV for all under study decades. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns. 

The tropopause is a thin layer separating the stratosphere from the troposphere and is often characterized by a large change in the thermal, mass and chemical structure of the atmosphere.Compared to global studies on the tropopause and its various features, studies conducted in Iran are very few and the methods used are often less inclusive or the length of the statistical period is limited. For this reason, and considering the importance of the tropopause and its effect on exchanges between the troposphere and the stratosphere, and also due to the lack of information about it in Iran, accurate knowledge of the height of the tropopause in the country using more reliable data sources is a fundamental necessity. To calculate the tropopause, we used daily temperatures of ECMWF reanalysis datasets from January 1979 until December 2018. Gridded data witha spatial resolution of 0.25*0.25 were used. In vertical levels, we used 10 standard isobaric surfaces from 700 to 50 hPa.

The location of the tropopause thermally and dynamically was defined. According to the WMO (World Meteorological Organization), the tropopause is defined as the lowest level at which the lapse rate decreases to 2°C/km or less, provided that the average lapse rate between this level and all higher levels within 2 km does not exceed 2°C/km.In this study, this index was used to identify the tropopause.In this study, to identify the factors affecting the tropopause, the relationship between the tropopause and spatial variables (latitude and longitude) and altitude was evaluated by general and partial correlations.

The results of this study showed that in the months of cold season, the tropopause pressure level on Iran is followed by latitude, and the tropopause height decreases with increasing latitude, but in the months of the warm season (June, July, and August), the tropopause pressure level is different from the months of the winter season.In these months, the changes in the tropopause pressure levels do not follow the latitude; on the Zagros and Kerman heights, the tropopause height is at its lowest, while the highest tropopause elevation is in these months at higher latitudes than in other months.The temperature of the upper and lower levels of tropopause also showed that the temperature of the lower levels of the tropopause in all seasons was below the temperature of the upper levels of the tropopause and the temperature of the two levels changed with the changes in the levels of tropopause pressure in different months.The study of low and high levels of tropopause showed that during the cold season, the temperature of the two levels around the tropopause, following the tropopause pressure levels, follows the latitude, and with increasing latitude, temperature increases in the two levels around the tropopause.In two studied seasons, the lowest temperature of the two levels of the tropopause is consistent with the highest level of the tropopause, but the highest two-level temperature is only consistent with the lowest tropopause pressure level during the warm season months, and in other months, this observation coordination failed.Investigating the thermal difference between two levels of tropopause showed that the temperature difference between the two levels of the tropopause in the warm season is more significant than that of the cold season, while in the cold season, the temperature difference in most regions of the latitude is obeyed. Slowly, the difference in temperature decreases with increasing latitude.

Examination of the characteristics of the tropopause and its related factors for summer and winter showed that in each season due to local conditions and changes in large-scale factors, the height of the tropopause changes, and therefore the tropopause in each season has completely different characteristics from the other season.Examination of the characteristics of the tropopause and its related factors for summer and winter showed that in each season due to local conditions and changes in large-scale factors, the height of the tropopause changes, and therefore the tropopause in each season has completely different characteristics from the other season.

The expansion of urbanization and the increase of population in metropolises and the growth ofindustrial activities of cities, It has caused changes in urban area climate. One result of these changesis the city's heat islands. The city of Mashhad has also grown rapidly in recent years. This studyinvestigates the heat/cold island of Mashhad metropolis based on the background climate in order toidentify its spatiotemporal behavior. For this purpose The MODIS Terra and Aqua land surfacetemperature (LST) data were obtained and the heat island was examined accordingly. A new wasused to measure the heat island. In this method, Modis land use data was used to determine the urbanand suburban boundaries as well as to determine the land use type of the study area. The backgroundclimate was determined based on Far-side temperature and the representative non urban area wasselected based on the most frequent temperature and the heat island was calculated. Survey ofheat/cold island in the daily period showed that during the day the average temperature of city islower than non urbun temperature and at night is higher. Also the seasonal survey of heat island/couldisland of Mashhad metropolitan shows that daily cold island is the highest during the warm seasonsand lowest in the cold seasons and the seasonal variability of nightly heat island is less than the dailycold island. The core of the daily cold island is located between the Haram and the Shahid FehmidahSquare towards the western area of Mashhad. The day time cold island matches the areas of the citywith high vegetation coverage. The core of the nightly heat island is consistent with the old textureand dense area around the Haram towards the northwest of the city. The heat/cold island intensity isalso directly related to the wind speed. The role of land use in intensifying or reducing the intensity ofthe heat island of Mashhad is well seen. In the development of the city, more attention can be paid tothe use of urban land use in order to moderate the temperature of the city.

Some mechanisms of climate change, particularly changes in precipitation, are the result of changes in local mechanisms, while some others are caused by the interaction of events on larger scales, e.g., regional, synoptic, hemispherical, or planetary scales. However, in all these changes, the reactions of spatial factors like geographical coordinates (latitude and longitude) and topographic features, including altitude, terrain slope, and terrain aspect, on a local scale can be a proper signal of large-scale changes. In particular, numerous studies have shown that spatial variations, as well as temporal variability of precipitation, are in relation with spatial coordinates (longitude and latitude) and topography (altitude, terrain slope, and terrain aspect). Nevertheless, the fact that the temporal variation of precipitation is in relation with the roles of spatial factors has been neglected.Using the Artificial Neural Network (ANN) technique, the present study aimed to provide inferences about the decadal changes in the overt and covert links of spatial factors with the precipitation climatology of Iran. Thus, using the national network data (Asfazari), 3rd version, the spatial distributions of precipitation for the last four decades were compared based on spatial factors. Also, an attempt was made to show the decadal variation of precipitation in Iran in relation to spatial factors, which could serve as an index of climate change as an essential field of research on precipitation. 

Two datasets were employed to conduct this investigation; the 3rd version of Asfazari Precipitation Dataset and the data of a Digital Elevation Model (DEM) related to Iran. The first dataset with the dimensions of 16801×205×167 and a resolution of 10 km was applied to study the temporal and spatial behaviors of precipitation within Iranian borders. The second dataset with a resolution of 10 km belonged to the US Geological Survey produced via ASTER satellite imagery with a global coverage.Based on the two above-mentioned datasets, the following steps and methods were taken and adopted to conduct the current study:1- The average precipitation for the whole period (1969-2015) was calculated and its spatial relationships were examined. To investigate the variability of decadal precipitation, the average precipitation for each decade up to the decade of 2006-2015 was measured. Thus, the first 6 years (1969-1975) did not fit into the study decades to provide a comparison. Accordingly, the spatial characteristics of precipitation in Iran during the four decades of 1976-1985, 1986-1995, 1996-2005, and 2006-2015 were studied.Precipitation is considered as one of the elements, phenomena, and climatic processes, as well as an important indicator, in climate change tracking. One of the notable features of precipitation is its strong and often nonlinear relationship with geographical coordinates (latitude and longitude) and topographic factors (altitude, slope, and slope direction). There are several ways to study this relationship. In this regard, we can refer to regression methods, control methods, ANN methods, etc. In recent years, the use of regression techniques (for example, Singh et al., 1995; Glazin, 1997; Alijani, 1373; Ghayyur and Masoudian, 1375; Mojarad and Moradifar, 1382; Asakereh, 1384; Razi'i and Azizi, 1387) has been in focus.Modeling the time series of climate like precipitation and chaotic spatial relationships of such nonlinear series are difficult and complex task due to atmospheric dynamics and its nonlinear relationships with spatial variables and since temporal change (variability) of precipitation in a continuous and chaotic system reflects a complex and nonlinear atmospheric behavior in the "geographical space". The spatial analysis showed that the relationships between precipitation and spatial factors had undergone a change on the tempo-spatial scale. Accordingly, complex algorithms, such as ANN methods, were more suitable for modeling these chaotic time series in a broad space like Iran.To study the characteristics of precipitation in Iran and compare the spatial relationships of precipitation in the current research, the spatial distribution of precipitation on the decadal scale and the decadal variability of precipitation were first investigated. Based on the selected spatial-topographic factors in all 16203 cells on the map of Iran as the ANN inputs, a model could be extracted to better fit the data. In this paper, the precipitation in Iran was regarded as the target variable to be compared with the model outputs. 

General characteristics of annual rainfallThe spatial average of precipitation was about 250.5 mm. There was a very large spatial difference of precipitation in Iran. The spatial variability of precipitation was estimated based on geographic coordinates and topographic variables by using the ANN technique. Although the model’s error rate (88809.3) was noticeable, the correlation coefficient (0.95) showed that the estimated spatial distribution pattern of precipitation and the spatial distribution of real precipitation were very similar (90%). The absolute values of the model’s coefficients revealed that longitude, latitude, and altitude played the most important roles, respectively. The terrain aspect played the least important role in justifying precipitation. Decadal changes of precipitationThe average precipitation in the country demonstrated a significant decrease from 268.1 to 220.3 mm from the first to the fourth decade. Nonetheless, the second decade had experienced a relatively significant increase and thus disrupted the general downward trend. The average precipitation anomaly was negative in the last two decades as well. This was evidence of the impact of the decreasing trend of precipitation in all regions of the country. Consequently, in the last two decades, 76.1 and 81% of Iran’s territory had received less precipitation than the long-term average precipitation between 1969 and 2015, respectively. The amounts of precipitation in the models fitted to each decade were compatible with the actual precipitation amounts. Therefore, the role of spatial factors in estimating rainfall had an acceptable capability.Decadal changes in the effects of spatial factorsAssessment of latitude coefficients revealed that both the pattern and coefficient values ​​were corresponding to the first, third, and fourth decades. It seemed that the negative values of latitude increased towards the last decade. For the second decade, which was associated with a relative enhancement in rainfall, the coefficients were different from those of the other decades. In this decade, coefficient variability was higher than those of the other decades. The average longitude coefficients of 10 neurons for the four studied decades were 1.76, 29.35, 0.91, and -1.19, respectively. The average altitude coefficients of neurons for these decades were about -2.87, -7.3, 0.1, and 3.75, respectively. Also, the average slope coefficients for the decades were almost similar to those of the altitude pattern (-2.29, 29.91, 0.3, and -0.22, respectively). However, the degrees of influence (coefficient values) and their signs were highly different for these two factors. Finally, the average coefficients for slope for the mentioned decades were about -0.71, 31.18, 0.34, and -2.83, respectively.

 Conclusion

In this investigation, the diversity of spatial factors, such as geographical coordinates and topographic features, were found to have led to the spatial diversity of climatic elements like precipitation.  In association with the temporal changes of precipitation, spatial factors played different roles in the process. Therefore, despite the relative stability of spatial factors, it could be inferred that these factors played different roles in the context of precipitation changes. To track the roles of geographical coordinates and topographic factors, i.e., altitude, terrain slope, and terrain aspect, in precipitation, the Artificial Neural Network (ANN) model was utilized. The research findings could be presented in two categories as follows

Dust and air pollution from dust are of important social and everyday issues in society. According to the Earth Observatory website dust storms are considered natural hazards, which affect ecosystems for short time intervals ranging from a few hours to a few days. Dust outbreaks have a significant impact on climate, human health and ecosystems, and numerous studies have been conducted worldwide with different instrumentation and techniques to investigate of such events. In addition to human health problems, these phenomena impose much damages to industrial and agricultural installation, population centers and communication ways. The recognition of source regions, creation and expansion style of dust storms and their relation with atmospheric circulation patterns are fundamental factors in reduction of their damages this has affected major decision-makings and policies. Dust particles enter the atmosphere under the influence of various factors such as weather conditions, ground surface characteristics such as topography, surface moisture, roughness and rough length and vegetation and soil characteristics (texture, density and composition) and land use (agriculture). Dust particles enter the atmosphere from the soil surface, rocks, volcanic lavas or environmental pollution and can lead to reduced evaporation, lowering the surface temperature and affect the precipitation process. Dust storms are one of the destructive climatic phenomena which are affected by various climatic elements such as pressure, precipitation, wind, temperature and evaporation. Dust storms are more common in arid and semi-arid regions and are far more important. Khorasan Razavi province has an arid and semi-arid climate with several dust storms occurring on its surface every year.

Statistical study of dust storms and tracking and revealing the path of these storms is important. In this study, statistical analysis of dust storms was performed using data from Khorasan Razavi Synoptic Meteorological Station. According to the World Meteorological Organization (WMO) guidelines, when wind speeds exceed 30 knots per station and horizontal visibility is less than one kilometer due to the dust phenomenon, a dust storm is reported and, the WW = 30-35 codes related to dust or sand storms are introduced, the occurrence of these codes in Khorasan Razavi synoptic stations was investigated. In the next step, the source of the dust storm event was investigated as a case study on 10/17/2017 using the image of MODIS satellite in Mashhad. Monitoring of dust source region, transport pathways and plume characteristics is only possible from satellites because ground-based measurements are very limited in space and time. Therefore, it is important to identify, also for prognostic purposes, the atmospheric circulation patterns facilitating the transport of dust particles from their source regions over distances of thousands of kilometers downwind. Compared to ground-based measurements, satellite observations offer a more efficient way of determining key characteristics of aerosols at temporal and spatial scales that are needed to study and monitor aerosol impacts upon the climate system. The Modis sensor was used to detect the path of the phenomenon and to examine satellite images. Compared to other sensors, MODIS measures the entire earth's surface in 36 bands, covering from the visible band (0.415 micrometers) to the thermal infrared (14235 micrometers). The Modis sensor is a high radiometric resolution (12-bit) device which is carried by two American satellites, Terra and Aqua. The crossing time of the two Terra and Aqua satellites along the equator is at 10:30 and 13:30 local time. In this study, images of the MODIS visible True color band with a resolution of one kilometer on the date under study in the area were received from NASA. Aerosol Optical Depth (AOD) is one of the most important parameters in the study of dust. The Aerosol Optical Depth actually refers to the distribution of dust aerosols in the atmosphere. This wavelength-dependent quantity is defined as the decrease in light per unit length on a given path Aerosol Optical Depth (AOD) is the degree to which aerosol particles prevent the transmission of light. It is defined as the integrated extinction coefficient over a vertical column of unit cross-section. It is an indirect measurement of the size and number of concentrations of aerosol particles present in a given column of air. The spectral dependency of AOD contains information about the dominance of fine and coarse mode particles, the aerosol source regions, the modeling of aerosol radiative effects, the air quality (through monitoring of particulate matter), and the correction for aerosol effects in satellite remote sensing of the Earth’s surface. Aerosol Optical Depth (AOD) maps were obtained with a spatial resolution of 0.1 by 0.1 degree and were received at three-hour time intervals from the Barcelona Forecast Center for the study. After the dust storm was detected and the source areas were identified, the tracing of the dust particles to Mashhad was determined using the HYSPLIT mode. The HYSPLIT model, which is a dual model, was used to calculate the dust trajectory, dispersion, and simulate it. HYSPLIT is a complete model for computing trajectories, complex dispersion, and deposition simulations using either puff or particle approaches. It is plausible to detect transport pathways through monitoring the dust source region in HYSPLIT. Developed by National Oceanic and Atmospheric Administration (NOAA), it is a Lagrangian model. This model is widely used for air parcel dispersion, transportation, and deposition simulation.

The results showed that the highest amount of dust storms is associated with Sabzevar with 136 mild storms and 79 severe storms and Sarakhs and Gonabad were in the next ranks. The dust phenomenon was observed case-by-case by detection and tracking that, this phenomenon has been formed in Turkmenistan in the early hours and affected Mashhad by penetrating the eastern borders of the country. According to satellite imagery, the origin of the dust storm in history has been in parts of Turkmenistan northeast of Mashhad. The output of HYSPILT maps shows good overlap with satellite imagery. This path has also been overlapped in AOD and Trajectory_Wind survey. In general, it can be stated that initially the primary dust cores were formed in the Turkmen desert and the density of dust increases as it moves west, and it has penetrated to the west and on the eastern borders of Iran and then to the city of Mashhad.

Dust storms are observed and recorded at meteorological stations as a weather phenomenon that is categorized according to the degree of visibility deterioration. In this study, the days with dust storm (observation code 30 to 35, present weather), the synoptic analysis of wind speed, horizontal visibility and weather conditions have been adopted. The results showed that the highest amount of dust storms is associated with Sabzevar with 79 severe storms and Sarakhs and Gonabad were in the next ranks. Studieswith the various methods have shown that initially the primary dust cores were formed in the Turkmen desert and the density of dust increases as it moves west, and it has penetrated to the west and on the eastern borders of Iran and then to the city of Mashhad.

Land Surface temperature is an appropriate manifestation of energy balance in the surface and greenhouse effect; because key parameterization in the physics of land surface processes is on a regional and especially global scale. It has been almost two decades since the MODIS sensor measured the surface temperature. Analysis of Land surface temperature (LST) Variation can help us understand the behavior of this key metering meter. The purpose of this study is to investigate the trend of land surface albedo in Iran. For this purpose; The Land surface temperature data of the Modis Terra sensor (MOD11A1) was used daily for the period 1379-1389 at a spatial resolution of 1. 1 km. After extracting the data in Iran, the Land surface temperature trend of Iran in 1884077 cells was examined using the Mann-Kendall test. The results of this study showed that in all seasons, increasing and decreasing trends in Land surface temperature are observed; however, the largest range of increasing trends of Land surface temperature in winter can be seen in January, February, and March. The results showed that in winter, the most significant increasing trends are seen in the heights, which can be related to the reduction of snow cover and reduced albedo in these areas. Using the digital elevation model of Iran, the Land surface temperature trend was calculated at altitudes of 100 meters, which showed that in January month, all height levels have an increasing trend in surface temperature, which is significant at the level of 0.05(the 95th confidence level).

Albedo is one of the parameters needed in environmental and climate studies. Therefore, examining its temporal and spatial behavior can be a tool for understanding environmental changes. The MODIS sensor produces Albedo the surface of the earth continuously on a global scale with low spatial resolution and provides free access to the public. In this study, for measuring the Analysis of Barriers to Albedo Observations in Iran, The first daily data of Albedo MODIS Sensor in the kernel of Iran was downloaded from the MODIS website during the period from 2000/03/20 to 2018/12/31 for 6867 days. After mosaic tiles, based on 48 billion observations, the long term frequency of land surface Albedo Iran was calculated separately for each season. The results showed that the limiting factors of satellite view were different at times and places. Humidity has a limiting role in summer, especially on the coast of Oman. In the winter, especially in the Alborz and the Zagros Mountains, cloudiness is a limiting factor. In addition to the humidity and cloudiness factors, Dust storms are also known to limit albedo harvest. Surveys of 394 ground stations proved that more than 70 percent of the factors listed were reported when the satellite was unable to measure albedo.

The agricultural sector is inherently susceptible to climate change, making it one of the most vulnerable to the risks and side-effects of environmental changes. The purpose of this study is to evaluate environmental change in Najaf Abad County. The research method is descriptive-analytical and the data were obtained via the survey method. Mann-Kendall trend studies showed that the temperature had an upward trend over a statistical period of 20 years. And in the field of rainfall, there is no clear trend and a decrease in rainfall in the city. The study showed that there is a strong correlation between extraction from groundwater resources and changes in groundwater level and also the destructive effects of the process of increasing the derivation of groundwater resources in the Najafabad County. The correlation coefficient of precipitation and groundwater level fluctuations showed that there is no relationship between these two-time series. In this study area, the trend of falling groundwater level is independent of precipitation and due to the improper use of groundwater and the reduction of surface water entering the region. The results of the cross-correlation coefficient of the two-time series (water level drop and electrical conduction) indicate the strong correlation between these two-time series as well as the negative effects of groundwater level drop trend on the electrical conduction of water in Najafabad. Findings showed that in the south and southeast of Najafabad, due to the change in the use of farmers from agriculture to planting trees and gardens, vegetation has increased. But in most parts of the township, the vegetation trend has been negative. Studies have shown that the amount of agricultural and horticultural lands in the city has decreased sharply and the number of employees in the agricultural sector has decreased.

According to previous investigation and examining climatic elements, the hypotheses of global warming and consequently, global climate change is confirmed by majority of climatologists society around the world. The global changes probably continue for the next decades. The changes in climatic elements, by and large, categorized into two types; trends and variation. The trends refer to long term changes, whiles variations indicate vary time interval changes including oscillation, phase, jump (sift), and persistence.Precipitation is one of climatic elements which can properly reflect chaotic behavior of climate system, and illustrate the nature of changes in the system. Trends, Oscillation, and persistence in this element are investigated in national and international scale, whilst the decadal variations as an index of climate variation can contribute to the current literature. In current study we attempted to illustrate an objective feature of precipitation characteristics and its anomalies over four recent decades by using Asfezari National Dataset (AND).          

In the present study, the gridded precipitation data of the third version of AND with spatial resolution of 10×10 km during the time period of 1970/3/21 to 2016/3/19 (46 years including 16801 days) is used. This dataset adopted from 2188 synoptic, climatology, and rain gauge stations and subjected to interpolation by using Kriging interpolation method. The dataset covers an area from  N  and E. Accordingly, a pixels cover the area for 16203 days. Consequently, the dataset includes  dimensions.General spatial features of Iran precipitation for the whole under investigation period was studied based on climatological annual precipitation. Next, the same characteristics calculated for four decades ending up to 2016/3/19. Finally, for every decade the anomalies of precipitation in compare with the whole understudy period and its previous decades calculated in order to discover the spatial pattern of decadal fluctuation in precipitation.   

General characteristics of annual precipitation Annual mean of precipitation over Iran is 250.5 mm. Due to decline in temperature contrast and strength of fronts in the Mediterranean cyclones, as a main source of precipitation in Iran, the annual precipitation over Iran decreases from west to east, and from north to south.The annual precipitation in 63.2% of Iran is lower than the climatic annual mean. The annual mean of precipitation in this area which generally located in east and south of the country is approximately 150.5 mm. Thus, the total precipitation in this area is equal to the total precipitation in the rest 36.8% of the country which its annual precipitation is more than the annual precipitation in the country, 422 mm.  The spatial variation of precipitation is confirm by other statistics, for instance, skewness, kurtosis, the extreme threshold indices. For instance, a large part of Iran (26.73%) includes 100-150 mm annual precipitation, whiles the precipitation in 15.8% of the country reaches to 150-200 mm. Parts of northeast of Iran, and the coast  of Persian Gulf  and Oman Sea in the south, in addition to southern slops of Alborz mountain chain experience a precipitation amount of lower than 100 mm. In contrast to the above-mentioned dry regions, the (approximately) wet regions include limited areas for each precipitation class. For example, only 9.1% of the country characterized with 500 mm of precipitation, while the classes of 200-300, 300-400, and 400-500 comprise 20.62, 12.64, and 6.11 percents of the country, respectively.

Decadal variation of precipitation :

 In current section the spatial distribution and statistical features of precipitation in each decades was illustrated. The following list includes our finding of statistical - graphical analysis of precipitation in four successive decades:1)Thedifference between spatial mean and median of annual precipitation increased from the first to the last decades. The increasing in this characteristic refers to increase in spatial asymmetrical distribution of precipitation over the country.2) A comparison between spatial distribution of precipitation maps showed that generally, the areas experienced precipitation above the decadal and whole period average are decreased from the first and last decades.3) The increase in spatial skewness from the first decade to the last decade is another evidence of increasing in precipitation spatial differences.4) The last but not the least finding is the changes in the extreme threshold indices. From the first to the last decade, the range of 10th and 90th percentiles have increased.           

Previous studies depicted that the amount of Iran precipitation has decreased over recent decades. In order to investigate the role of each decade in the decreasing values, the gridded precipitation data of the third version of AND with spatial resolution of 10×10 km during the time period of 1970/3/21 to 2016/3/19 (16801 days) is used. General spatial features of Iran precipitation for the whole under investigation period was investigated based on climatological annual precipitation. Next, the same characteristics calculated for four decades ending up to 2016/3/19. Finally, anomalies of precipitation in compare with the whole understudy period and previous decades calculated in order to discover the spatial pattern of decadal fluctuation in precipitation. Our finding showed that by and large, precipitation has decreased over recent decades. The changes has been more pronounced in southern and northern coastal area, western slopes of Zagros mountain chain, and northern slopes of Alborz mountain chains. Previous researchers attribute these changes to changes in humidity advections in recent years.

A Discrimination of Roles of Internal and External Factors on the Decadal Variation of Annual Precipitation in Iran over Recent Four Decades (1975-2016)IntroductionAccording to Intergovernmental Panel on Climate Change (IPCC) the Earth's climate has been changed during recent century (IPCC, 2007). These changes may continues for the next century. The changes have happened in two ways, log- term change (trend) and variation (in form of Oscillations, phases, shifts, and persistence) (Asakereh,2017). Moreover, some of these changes are due to internal factors of a region, whilst some of them result from external culprits of a given region. The distinguish between these two groups of factors is an important scientific effort to understand the changes mechanisms governing them. The emerge of climate changes and climate variation can be traced by investigation of some sensitive climate elements. One of those chaotic elements is precipitation which experiences changes in different tempo-spatial scales (Goudi, 1994). Most of these changes, specially the trends, are studied in global (Todorov, 1985; Vining and Griffiths, 1985; Diaz et al. 1989) and national (Askari and Rahimzadeh, 2003; Asakereh,2004; Zahedi et al., 2007; Katiraie , 2007; Mohamadi, 2012; Ekhtesasi et al. 2015; Nazeri Tahrudi, 2016) scals. In the climatology literature (Singh et al. 1995; Ghayur and Masoodian, 1996; Glazirin, 1997; Mojarrad and Moradifar, 2003; Asakereh, 2004; Raziei and Azizi, 2009; Asakereh and Seifipour, 2013) spatial changes of precipitation was attributed to spatial coordination (longitude and latitude) and topographic features (elevation, slope magnitude and aspect). The temporal changes in precipitation in association with these topo-spatial factors has not been considered in details and in proper ways in climate researches. In current study we put the spotlight on the decadal variation in relation with the topo-spatial features as a representative of climate change and as a vital context of research. Accordingly, a regression model is adopted so as quantify the effects of topo - spatial factors effecting variability of precipitation over recent four decades.Materials and methodsIn order to achieve the aim of current study, two dataset were adopted; a national precipitation dataset, Esfezari, and Digital Elevation Model (DEM):The third version of Esfezari dataset is result from Kriging interpolation of daily record of 2188 synoptic, climatologic, and rain gauge stations for 46 years (1970-2016) with 10 km resolution. The 16801 daily maps with 167×205 pixels were created accordingly. Consequently, the dataset include dimensions of 167×205×16801. The DEM data with 10 meters spatial resolution was adopted from The U.S. Geological Survey which was provided by "Astet" satellite images. This dataset was applied to extract the topographic features (elevation, slope and its aspect) for Iran. To start with, the annual precipitation for the entire under investigation period (1970-2016) was analyzed according to abovementioned data. In the second place, the topo-spatial distribution of precipitation for four decades ended up to 2007-2016 was compared in an analyzing effort by using linear and non-linear correlation. In this stage, according to Law of Parsimony, it is revealed that linear correlation illustrate the relation between precipitation and topo - spatial factors in proper way. Moreover, A multivariate linear regression fitted on the five topo-spatial elements for every under study decade so as to detect precipitation accordingly. The regression model can be expressed as follow: where refers to annual precipitation in th pixel which is detected by the topo - spatial factors and considered the internal- cause precipitation. and are latitude and longitude, respectively. In the above regression model, , and are elevation, slop, and aspect of slop, respectively. Consequently, the external - cause precipitation is the model residual. Finally, the descriptive characteristics of precipitation maps of internal-cause and external - cause were analyzed. Results and discussionGeneral Features of Iran PrecipitationThe general feature of precipitation over Iran shows a decreasing trends from west to east and from north to south. The coast of Caspian Sea and the summits of Zagros Mountain chain receive the highest values of precipitation. The spatial average of annual precipitation is about 250.5 mm. The strongest relationship between precipitation and topo-spatial factors is related to longitude in negative way. This feature is reflected in eastward decreasing of precipitation. The determine coefficients for latitude and elevation are 13% and 4.5%, respectively.The variation of effects of internal and external factors In spite of the stability of the determine coefficients of all regression models for all decades, some of topo - spatial factors have noticeable variation. This feature refers to the fact that increasing in the effect of one factor may decrease the effect of other one(s). The models, however, illustrate a stable feature for precipitation over all four under study area during four decades. Consequently, the external factors are the main culprits in decadal changes of annual precipitation. Our finding showed that in the first decade the ratio of factors was 52.38% which increased gradually to 54.08% , 58.44%, and 59.72% among of four under the rest decades (Table 1). This refer to the fact that the changes in variation of precipitation is in association of global changes.Table 1: The areas under the effects of variation due to internal and external factors (%)Priod The percent of the country due to ---effects internal externalFirst decade 47.62 52.38Second decade 45.92 54.08Third decade 41.56 58.44Forth decade 40.28 59.72Entire period 44.38 55.62ConclusionThe climate and precipitation climatology of Iran is effected by internal and external factors, due to geographic features of the country. The internal factors include spatial (latitude and longitude), and topographic (elevation, slop and its aspect) features. In current study, in order to discriminate internal and external characteristics which effects precipitation variation we fitted a multivariate linear regression on internal factors to separate them out and distinct external factors. Accordingly, our finding revealed that the ratio of external factors in variability of precipitation increased from the first decade (52.38%) to the last decade (59.72%). This result is in line with previous studies (Khodadi et al. 2013; Farajzadeh and Ahmadian, 2014; Darand, 2015; Karimi et al., 2018). The most influenced area from the variations of external factors are internal parts rather than marginal parts of the country. 

Snow cover plays an important role in the water and energy cycle of the world due to its high albedo and thermal properties and it can also reflect global climate change (Dozier et al., 2008; Shi, 2012). Precise monitoring of the extent of snow cover is an issue that has received much attention (Lampkin and Yool, 2004). Monitoring snow parameters, such as the extent of snow cover and snow equivalent water, are a challenging topic for meteorologists and climatologist. Snow cover plays an important role in balancing the earth's energy due to its high albedo and affects the climate (Akyurek et al., 2010). Many studies have been conducted to investigate snow cover and its changes. for example, Khadka et al. (2014), used the MODIS data for the period 2000–2009 to analyze snow trends in the Tamakoshi Basin of the Himalayan Mountains, The findings of the researchers showed that during the ten years of the study, there was a decreasing trend in the area of snow zones during spring and winter, while the area of snow zones had an increasing trend in the autumn season (Khadka et al. 2014). Sharma et al. (2012) applied MODIS data for the years 2000–2011 to analyze the snow trends in the Jalom River Basin and its sub-basin located in the northwest of the Himalayas. The results showed decreasing trend in all sub-basins with the highest negative rate for Banihal sub-basin (Sharma et al. 2012). Maskey et al. (2011) studied the trend of snow cover in and around Nepal for the years 2000–2008. For this purpose, they applied MODIS data. The findings show that in January for three elevation zones below 6000 m and in March for two elevation zones above 5000 m snow cover trend are seen. In the fall, snow cover showed increasing trend for four altitudes above 4000 m (Maskey et al).

In this study, the daily data of MODIS Terra (MOD10A1) and MODIS Aqua (MYD10A1) version 6 were applied for the period from 1380/7/1 to 1397/6/31. One of the problems that is always a big obstacle to monitoring snow cover is the cloud issue. Clouds cause the underlying snow cover to be hidden from the satellite view. To reduce cloudiness and better observation of snow cover, various methods and strategies have been suggested by various researchers to minimize cloud cover effects. The applied filtering methods included combination of MODIS Terra and MODIS Aqua, spatial combination with four pixel neighbor and 1 to 5-day temporal windows. All calculations were performed using programming operations in MATLAB software and at the climatological laboratory of the University of Isfahan.

In order to better present the research findings and to classify them, calculations related to the accumulation and melting timing of snow cover in Iran have been provided spatially and temporally for each of the accumulation and melting parameters. Climatological survey of snow cover accumulation in Iran shows among the first days that the earth is covered with snow and the elevation there exist a strong relation, in other words, the first days of snow cover occur at the highest altitudes and slowly move to the lower elevations as we move toward autumn. Analyses shows the first days of snow cover in the first decade of Mehr are seen on the Alborz Heights and the Sabalan Heights in the northwest. Snowfall days in other northwest elevations begin around the second half of late Mehr. The onset of the snow cover season on the central Zagros highs begins around the first decade of Aban and covers many of the lower elevations until late Azar. It seems that the delay of the onset of the snow cover season on the Zagros Mountains compared to the northern and northwestern highlands of the country is due to the delay in autumn rainfall rather than the necessarily warmer temperature.A long-term study of the average snow cover melting in Iran shows that there is a very strong relationship between altitude and the last day when the ground is covered with snow. The analyses show that, on average, the last day when the ground is covered with snow starts from lower altitudes and slowly migrates to higher altitudes. For example, in the lower elevations of the Zagros Mountains the snow cover on the ground is melted in the middle of February, in the higher elevation areas due to the colder weather the last day when the ground is covered in snow are seen in the late of winter. However, there is snow cover in the Zardkouh highlands until the end of June and even early July, and afterwards, these areas lose their snow cover. On the Alborz Mountains due to their higher altitude and higher latitude, snow cover will persist even in some areas until late Amordad and early Sharivar. During the months of snow accumulation in Iran, which covers the months of Mehr to Azar, snowline moves downwards at an average rate of 54 m / day, while during the months of snow melting (Dey to Shahrivar) snowline migrate to higher altitudes at the rate of 15 meters per day.

The purpose of the present study is to study the climatological accumulation and melting of snow-covered days in Iran. In this regard, the sixth version of the MODIS Terra and MODIS Aqua daily data at the spatial resolution of 500 × 500 m for the period from 1380/7/1 to 1397/6/31 were downloaded from the NASA Web site. In order to reduce the cloud effect on the data, three data refinement techniques were applied on the raw data including combination of MODIS Terra and MODIS Aqua, spatial combination with four pixel neighbor and 1 to 5-day temporal windows were applied to the raw data. The findings of this study show that the first snow-covered days are seen in the first decade of Mehr over the Alborz and Sabalan highlands and gradually snowline stretches to lower altitudes at 54 m / day. But during the melting months of snow cover, which includes Dey to Sharivar, snowline migrates to higher altitudes at a rate of 15 m / day. The reason for the slower rate of snowmelt migration to higher altitudes in the melting season can be attributed to the highly effective role of temperature in the melting season, but in the snow cover accumulation season, the role of temperature and precipitation mechanisms lead to the snow cover moving to lower altitudes.

The main sources of albedo change are variations in snow cover, variations in soil moisture, droughts, and variations in vegetation phenology, forest fires, and land use/ cover changes directly related to human activities, such as deforestation, irrigation, and urbanization. Forests obtain lower albedo values than shrubs, dry crops, grasslands, and bare soils. As a result, the conversion of forests to these land cover types leads to increases in surface albedo. This potentially has local and regional feedback, since an increase in surface albedo leads to a reduction in net radiation, turbulent heat fluxes, convective clouds, and precipitation, leading to a drier atmosphere Furthermore, black carbon decreases the surface albedo when deposited on snow and glaciers because it is incorporated in snowflakes, darkening snow and ice surfaces and increasing surface melt. Aerosols like dust transferred into the atmosphere and transported by the wind into the mountains where it settles on snow and glaciers, reducing albedo and leading to enhanced warming at higher elevations. It is noted that even though precipitation is the main driver of variations in soil moisture, its impact on albedo is controlled by evaporation, soil type, irradiation, vegetation, and topography. The present paper aims to evaluate the spatiotemporal variations of white sky albedo in Iran. For this, daily Albedo datasets from Moderate Resolution Imaging Spectroradiometer (MODIS) from onboard Aqua and Terra (MCD43A3v006) were applied from 2000 to 2019 with a spatial resolution of 500 × 500 m. MODIS provides black-sky albedo for direct and white-sky albedo for isotropic diffuse radiation at local solar noontime. For this, daily white sky albedo datasets from Moderate Resolution Imaging Spectroradiometer (MODIS) from onboard Aqua and Terra (MCD43A3v006) were applied. One of the main applications of the principal component analysis (PCA) is climatic zoning which is a method of determining environmental changes in temporal dimensions. A plethora of studies have been conducted using principal component analysis in the field of climatology but little has been done in relation to the albedo variation. To the best of the authors’ knowledge, this study uses a technique that has not been applied in scientific texts related to Modis albedo data. The questions that we will address in this study include: what is the temporal-spatial behavior of white sky albedo in Iran? How many components explain the variation of white Sky Albedo? What factors will distinguish white sky albedo in Iran?

In this investigation, daily white sky albedo datasets from Moderate Resolution Imaging Spectroradiometer (MODIS) from onboard Aqua and Terra (MCD43A3v006) were applied for the period of 2000-02-24 to 2019-06-03 (7040 days) with a spatial resolution of 500 × 500 m. Among the various MODIS datasets, white sky albedo datasets were extracted. The daily white sky albedo was averaged over the 19-year period for each pixel inside the border of Iran. The size of this array was 7541502 pixel *12month. Long-term monthly and seasonal means were also calculated by the available time series data. In the next step, the PCA method was applied to analyze the spatio-temporal variations of albedo in Iran. PCA is a method to reduce the number of the data and convert them into several finite components so that these few components explain the largest amount of the variance. This procedure is searching for the variable with the largest amount of the variance in space (PCA was invented in 1901 by Karl Pearson , and it was later developed by Harold Hotelling in the 1930s. In this method, initial variables are converted into n principal components each being a linear combination of the variables. In this way, the first principal component has the largest possible variance, and the components afterward explain a smaller percentage of the variance. Principal component analysis leads to the analysis of space-time array into two time-array and space-array. In this case, it is possible to identify what important spatial patterns the primary data have and at what time periods each of these patterns has been active or inactive. Because the principal components are finite, the temporal and spatial patterns introduced by the first component are more important than the temporal and spatial patterns of subsequent components.

The long-term average of Iran's white sky albedo was calculated; The results showed that the average albedo of spring, summer, autumn and winter in Iran 14.99%, 16.06% , 15.53%, and 19.58%, respectively. The evaluated long-term mean white sky albedo for each season showed that the highest value had occurred in winter. The dramatic increase in this value was placed along the Zagros, Alborz, Sahand, and Sabalan Mountains which exceeds 90 to 100 percent in some places. In the next step, the temporal-spatial variations of white sky albedo values in Iran were analyzed using principal component analysis, and the results showed that the three main components are able to explain 97.7% of the data variation. The first component explains more than 73%, of the total changes, the second component more than 20.8% and finally the third component explains more than 3.9% of the changes.

Spatial analysis revealed that the values which are higher than the mean are places in highlands and mountainous regions of Iran, such as the Zagros and Alborz Mountains, Sabalan, Sahand mountains and Zard Kuh-e Bakhtiari, which are associated with snow cover Therefore, the first component was named as snow cover as the maximum variance of albedo was explained by snow cover. The spatial analysis of the second component revealed that higher values were placed in small areas across Iran including, Hajaligholi desert Gavkhuni wetland, Qom salt lake, Sirjan salt lake parts of Loot desert. In the second component, most of the cell's scores upper of average in Iran corresponded to areas covered with salt. As the maximum variance is explained with salt cover, therefore, it can be named as the salt land. Spatial analysis indicated that in very limited parts of Alborz, Zagros, Alam-Kuh Mountain , Sahand, and Sabalan mountains Kino Mountain values are mostly positive which is related to the glaciers (regions with appropriate conditions to keep the snow cover in most of the year) and is the origin of the seasonal or permanent rivers Therefore, according to the cell scores (upper of average in Iran) in the third component, it was found that these cells corresponded to the , so it was named as the glacier component.

In current study, we underlined the trends of annual precipitation over Iran in relation with changes in high and low extremes and normal values of precipitation from spatial analysis point of view. To this end, the third version of Asfazzari national database with 10 10 km spatial resolution and daily temporal resolution for 46 years (1970/3/21 to 2016/3/19) is adopted. Trend analysis depicted that in the major parts of the country (approximately 80.9%) the annual precipitation has experienced decreasing trends which tend to reducing about 1.5 billions cubic meters of input water in the hydrologic system of the country. Our finding showed that the decreasing trends of precipitation prompted by large scale and global systems. However, the local factors (longitude, latitude, elevation, slop) are culprits for changing the effects of abovementioned factors. These factors cause the decreasing trends to be statistically significant solely in a part of 33.53% of Iran territory (northeast, parts of eastern of Iran, parts of inner slops of Zagros mountain chain, an area from Kerman to Isfahan, Charmahal-o-Bakhtiari, Kohgiloyeh-oBoyerAhmad, from west of Shiraz, and north of Bushehr to Sanandaj in the west of Iran). Furthermore, the results of our study illustrated that the decreasing trends are due to decreasing in high values of precipitation, particularly decreasing in the 75th percentiles and above of precipitation values. The areas which include increasing trends covered spatially spread areas of about 2.93% of the country. This area has not been able to compensate for the lack of precipitation due to decreasing trends in the area associated with statistically significant decrease in precipitation.

One of the clearest manifestations of climate change is greater near-surface warming of the high latitudes than the low or middle latitudes of the Northern Hemisphere. This so-called Arctic amplification (AA) is evident in observations over recent decades. This disproportionate temperature rise is expected to influence the large-scale circulation, perhaps with far-reaching effects. The North/South temperature gradient is an important driver of the polar jet stream, thus as rapid Arctic warming continues, one anticipated effect is a slowing of upper-level zonal winds. It has been hypothesized that these weakened winds would cause the path of the jet stream to become more meandering, leading to slower Eastward progression of ridges and troughs, which increases the likelihood of persistent weather patterns and consequently extreme events.In the present research, we have attempted to detect the impacts of change atmospheric circulations under this hypothesis on variations of temperature in Iran and develops a method to assess the estimation of these changes in the studied area.

Precipitable water (PW) is highly variable in space and time and is one of the most important abundant greenhouse gases that play crucial role in the study of climate change, hydrological cycle, energy budget and numerical weather prediction. The knowledge about the spatial and temporal variability of PW is important in understanding climatic processes and in order to monitor drought conditions and desertification processes (Kaufman & Gao,1992). It is therefore necessary to obtain the distribution condition of water vapor in the atmosphere and to understand the effects of spatial–temporal variation of PW on regional, meso-micro scales and on global climate change (Wang, 2013). PW has a very short life cycle in atmosphere and this rapid turnover, joined to temperature variations with altitude and geography, distance to sea, evapotranspiration and moisture advection causes an irregular PW distribution in atmosphere, both horizontally and vertically. The purpose of this study was to identify the distribution patterns of PW in Iran and relationship these patterns with elevation and distance to sea.

In the present research, MODIS Aqua data (MYD05_L2. A V06) were used. The data with spatial resolution of 1 km (Near Infrared) have been selected. The selected study period covers since 2002/07/04 to 2017/07/25 (5501 days) that was exploited from NASA web site. These data are errors in the range between 5% and 10% (Kaufman & Gao,2003). The spatial resolution of the PW data are 1 km and temporal resolution is twice per day. Then using functions, these data converted from Level_2(swath data) to Level_3(grid data) and PW values interpolated on sinusoidal grid in 1800×2700 matrix with 1 km spatial resolution and daily temporal resolution. These data have been extracted for pixels within the political boundary of Iran and obtained a matrix with 1884080 rows (locations) and 200 columns (PW classes). Then on the base this matrix, calculated frequency distribution in 1 mm intervals from 0-199 mm for each of pixels (1884040×200). Finally, Principal Component Analysis (PCA) performed and frequency distribution patterns in Iran identified. The effects of altitude and distance to sea on these patterns, analyzed. The special program was developed and employed in MATLAB software for analysis the data.

The spatial distribution of atmospheric humidity in Iran is controlled by the height above the sea level, distance to sea and moisture advection. Based on the results, the mean annual PW of the country is about 12 mm. PW is maximum near the southern and northern coasts of the country. The highest and lowest amount of PW near the Oman sea coast (31 mm) and the peak of Damavand (3 mm), respectively. The results of PCA showed that 95% of spatial variation of PW can be explained through 4 components. Based on the results, local factors like distance to sea and altitude are the most important in spatial distribution of PW. The study of the relationship between distance from the sea and frequency distribution patterns of PW shows the effect of distance and proximity to the sea in the frequency distribution patterns. This fact is more evident in the first and second components. Up to the distance of approximately 250 kilometers in the first component and 150 kilometers in the second component, as expected, the amount of PW will gradually decrease. From now on, the spatial pattern of PW is affected by altitude and morphology rather than by distance from sea and sealand breeze. In the third component, due to the formation of a moisture convergence belt at approximately 11 and 4 km, respectively, on the south and north coasts, the amount of atmospheric moisture is maximum. Then from 11 to 66 kilometers due to the Alborz Range, which is a short distance from the Caspian Sea, the amount of PW is minimal. Minimal atmospheric humidity on the southern coast occurs approximately at 250 kilometers away from the sea. In the South Coast, moisture penetrates the country further away from the coast, as it is smoother than the North Coast; so that sea moisture enters through the straits of Kahnouj area into the Jazmourian plain and distinguishes this area from its surrounding areas in terms of moisture. Moisture in the Caspian Sea enters the Tarom Valley through the Manjil Strait. The spatial distribution of moisture in the western, middle and eastern Persian Gulf coasts does not have a similar pattern; this difference is due to factors such as the dominance of the sea-land breeze in the eastern areas of Bushehr and the presence of small firth and bays in the area that increase the atmospheric moisture of these areas. than the environment around them. The amount of moisture in the coast of the Oman Sea is clearly different from PW of the Persian Gulf; PW MODIS is also overestimated in places such as near beaches with high temperatures and humidity.In addition to the height above the sea level and distance to sea, the role of moisture advection should not be ignored. In the coastal region the variability caused by the high temperature and moisture advection and in areas far from coastline, height above the sea level causes many spatial differences in moisture distribution.

Although Iran is bounded from the north and south to the sea, atmospheric moisture is very low in the country. Based on the result, minimum and maximum difference of PW is about 27 mm, so that, in the region with more than 3000 m elevation PW is less than 6 mm, and the coast of the Oman Sea 60% of the time is above 26 mm. This result means, in spite of the great source of water in south and north, atmosphere of Iran suffers from poor moisture. Topography is a barrier to the entry of moisture north and south seas to the inland. In the inland region, altitude and in the coastal region, moisture advection and temperature, play crucial role in frequency distribution of PW. In this way, moisture advection is the important factor that well justified spatiotemporal variations of PW in Iran and through this, affected on water budget.

Studies of the atmosphere over the last hundred years have shown that human activities have caused changes in the atmosphere. The tropopause is one of the layers of the atmosphere whose changes have recently been introduced as a sign of a human impact on climate change. The height of the tropopause is affected by its upper and lower layers (the stratosphere and troposphere). The results of the studies conducted by various researchers have shown that different factors affect the height of tropopause and its changes, which can be divided into two groups. The first group of natural factors (such as changes in solar radiation and weather due to volcanoes, etc.) and the second one is human factors (including changes in greenhouse gases, human-induced changes affecting the ozone of the stratosphere and the production of air vents from human resources, etc.). Thus, altitude tropopause is naturally influenced by spatial characteristics (e.g. latitude and altitude), time (such as the time of year and hours of the day) as well as the frequency of atmospheric actions that determine climatic conditions. Compared to the studies performed globally, a limited number of studies concerning the tropopause have been conducted in Iran. Moreover, the applied methods and the length of the dataset were often inadequate. Therefore, in the present study, the daily data of temperature, and geopotential height from the European Centre for Medium-Range Weather Forecasts (ECMWF) for 700 to 50 hpa with a spatial resolution of 0.25 × 0.25 longitude/latitude were applied from 1979 to 2018 for the detection of tropopause. Accordingly, 2491 cells covered across Iran. The LRT was used to detect tropopause. The tropopause is defined as ‘‘the lowest level at which the lapse-rate decreases to 2 ºC/km or less, provided that the average lapse-rate between this level and all higher levels within 2 km does not exceed 2 ºC /km”. In the present study, in addition to changing the position, changing the scale (variance) as well as the shape of the frequency distribution (skewness and elongation) of the tropopause pressure level in each of the pixels on Iran was investigated. To calculate skewness, and kurtosis, daily tropopause height data were used. For each of the months studied, diffraction, skewness, and elongation were extracted using daily data and finally using data during the 40 years. The extracted trends of variance, skewness, and kurtosis were examined for each month. To track the synchronicity and conformity of changes in altitude and trend of tropopause pressure level with the trend of changes in mean monthly temperature in the lower and upper levels of the tropopause and the trend of the temperature difference between the two layers around tropopause was also evaluated over 40 years. In order to evaluate the long-term trend of each of the studied indices (mean, variance, skewness, and kurtosis) in relation to the height and pressure level of the tropopause, linear regression method with least-squares error method was used. The results of the study of altitude trend and tropopause pressure level showed that in most of the months studied and in most parts of the country, the trend of changes in tropopause pressure level was not significant at the level of 95% confidence. According to the results obtained for the winter months, it was found that the trend of a tropopause pressure level in December had no statistical significance over Iran at a 95% confidence level. In January and February, the obtained trend was not statistically significant except for southeastern areas. In the summer months, unlike the winter months, the trend of tropopause pressure levels was significant in most regions. During the summer months, in areas where the trend was significant, the trend of tropopause pressure levels was positive. Examination of the trend of tropopause height in terms of meters showed different results with pressure level. During the winter months, the trend was positive in all regions, and in January and February, this trend was significant in many areas, while the summer months did not exhibit a significant tropopause. The results of examining the trend of the low temperature of the tropopause in summer and winter months showed that the observed trend was not statistically significant in December, but in other months, a positive and significant trend was detected. Examination of the temperature trend in the high level of tropopause also showed that the temperature trend in this part of the atmosphere, like the low level of the tropopause in large parts of the country in the studied seasons, lacked statistical significance. Examination of the trend of the temperature difference between high and low levels also showed that the trend of the temperature difference between these two levels was statistically insignificant at the majority of cases. The temperature difference trend of the two levels studied in the summer months was negative and significant at most regions. In other words, the decrease in the temperature difference between low and high tropopause in these two seasons and in some areas indicates a strong decrease in tropopause. Examination of the trend of variance, kurtosis and skewness also showed that the observed trend lacked statistical significance in the two studied chapters at most areas. There was also no relationship between the surface temperature trend and changes in tropopause height. The results of this study showed that tropopause had no statistically significant trend in most areas and months. Moreover, the significant trend was not related to the two temperatures around tropopause and surface temperatures.