Introduction: Clouds and water vapor are important modulators of climate and are involved in feedbacks that strongly affect global circulation and energy balance. Typically، 50% of the earth surface is covered by clouds، at any given time. A cloud is defined as a visible mass of condensed water droplets or ice crystals suspended in the atmosphere above the earth surface. The cloud phenomenon plays an important role in the water cycle، radiation، temperature، precipitation، predictors of climate، and etc. As there are not adequate information on the spatial distribution of clouds in Iran، except for synoptic stations data، it is necessary to conduct researches on the physical properties of cloud by remote sensing data. Therefore، these kinds of data can provide us with a more accurate and comprehensive understanding of cloud phenomenon. This study examines the spatial distribution of cloud Fraction (cover) over Iran in 2007 using remotely sensed data. The results of this fundamental research could be applied in practical knowledge such as weather forecasting، climate modeling، seeding clouds، site selection of solar panels، and etc. Materials and methods: The aim of this research is to survey the spatial distribution of Cloud Fraction (CF) over Iran in annual and seasonal timescales. To do this، daily data of cloud product of MODIS Terra (MOD06_L2. A) over Iran was used in 2007. The data was obtained from the ftp linkftp: //ladsftp. nascom. nasa. gov/allData/6/MOD06_L2/. In this research، we have used spatial resolution of CF in 5 km×5 km scripting in MATLAB. In the first step، overlapping images have been removed and، then، the data within the Iranian border have been extracted from daily data. The data have been transferred into regular network of Iran for doing statistical computations. Results and discussion: The investigation on the annual mean percent of CF indicates that the value is 25. 3% for the morning and 29. 7%for afternoon. Thus، the amount of CF in the afternoon is increased compared to the morning times. In winter، the amount of CF for the morning is 48. 2% but for the afternoon it is reduced to 44. 1% and this reduction condition is not seen in other seasons. In spring، fall and winter seasons the amount of CF is increased in the afternoon compared to the morning. The spatial distribution of annual percent of CF indicates that the maximum is seen over the southern shores of the Caspian Sea and the minimum is observed in south east part of the country. The spatial distribution of seasonal percent of CF shows that the maximum amount of CF is over the highlands of Zagrous and Alborz mountains and the minimum is in south and south-east regions of the country. In this season، the maximum percent of CF is not seen over Caspian shores like other seasons. In spring، the maximum percent of CF can be seen over the southern shores of the Caspian Sea and parts of north-west but the minimum percent of CF can be observed over central areas of south and south-east regions of the country. In fall season، the maximum percent of CF is seen over the southern shores of the Caspian Sea and parts of north-east and the minimum is observed in south and south-east regions. In summer، the maximum percent of CF is in the southern shores of the Caspian Sea and the minimum can be seen over east and west parts of the country. In summer، the extent of minimum percent of CF is changed to other seasons and is far away from south-east regions. Conclusion: In this investigation، the CF parameter of MODIS Terra was applied in the daily temporal resolutions for the year 2007 to explore the spatial distribution of cloud cover over Iran. As the data did not have a regular geographical coordinated grid، a regular coordinate was initially constructed and CF data were trasnferred to this regular grid. This process was conducted to analyze the climatology of cloud cover. The results from MODIS Terra data for the pass of morning and afternoon times revealed that the maximum annual percent of CF is seen over the southern shores of the Caspian Sea and the minimum is occurred over south-east part of the country which is consistent with the results of Rasooli et al. (2013) and Masoodian and Kaviani (2008). For the seasonal time scales، the maximum percent of CF is occurred over the southern shores of the Caspian Sea for spring، fall and summer seasons but in winter it is seen over the elevations of Alborz and north-west parts of the country. The minimum percent of CF is seen in south-east and east parts of the country for spring، fall and winter seasons. In summer، it is observed over east and west regions where shows that the formation process of cloud is different in winter and summer compared to the other seasons. The validation of CF values in the annual time scale indicates that MODIS overestimes CF by 3% compared to the synoptic stations. This is acceptable when the results are compared with the findings of Bisoolli and Pahl (2001) in Germany with the erros of 6% and Kotarba (2009) in July and January months with the error of 4. 38% and 7. 28% for the year 2004. In general، the estimation of cloud cover is identical for the two data sets.

Assessment of Evapo-Transpiration (ET) in such a cases as Irrigation programming, water basin evaporation determination, water balance calculation, water runoff estimation and climatological studies are important. It is possible to determine ET by field measurements. However these methods can only determine ET for the regions with the limited areas. This limitation has made the use of remote sensing techniques reliable for the assessment of ET in a vast area.In this work, the amount of ET was evaluated in an army wheat field located in the Golestan Province (North of the Iran)for May, the 5th and June, the 7th, 2003using MODIS images. Surface albedo affects the outcome of SEBAL and we estimated it using two methods; a) 1 and 2 bands of MODIS image (old method) and b) 1 to 5 and 7 bands of MODIS image (new method). Comparison of the results of SEBAL with those of the other works showed that the accuracy of the estimation of surface albedo using the new method is better than when using the old method. Also, the accuracy of SEBAL outcomes was found to be relatively satisfactory and that can be improved by further detailed studies.

Introduction: The MODIS facility for the Earth Observing System is a key element that supports ambitious goals related to studying the Earth as a system. One of the MODIS products is high quality land surface temperature data produced in Terra and Aqua platforms. Knowledge of the LST provides information on the temporal and spatial variations of the surface equilibrium state and is of fundamental importance in many applications. Therefore, it is required to conduct a wide variety of climatic, hydrological, ecological, and biogeochemical studies. Due to the intrinsic scanning characteristics of the MODIS instrument onboard the polar-orbiting satellites, the differences in local solar time for pixels along a given scan line on the same day or for the same pixel on different days in one revisit period can be detected for 2 hours. As LST changes with local solar time, it is not possible to directly compare the LST of different pixels in the same day or of the same pixels in different days. Awareness about slope of land surface temperature is an important factor for cognition of land surface temperature behavior that can be used for increasing spatial and temporal resolution, comparability with other data, and accuracy achievement. The results will help calculate a time consistent land surface temperature.....

Introduction A cloud is a hydrometeor consisting of minute particles of liquid water or ice, or of both, suspended in the free air and usually not touching the ground. It may also include larger particles of liquid water or ice as well as on-aqueous liquid or solid particles such as those present in fumes, smoke or dust (WMO, 1975). Clouds, which display great variability in space and time, as well as in type, can influence climate through many complex interactions involving the hydrological cycle; however, their dominant role is in controlling the 3-dimensional field of radiative fluxes in the atmosphere. In turn, these radiative fluxes drive the thermally forced general circulations of the earth's atmosphere and oceans. These circulations then form clouds and a major climate feedback loop is joined (Rossow and Schiffer, 1983). Many researches have been done about sky conditions classifications abroad of Iran such as, Nakumura (1985), Qian et al (2012), Stove et al (1989) and Filipiak et al (2009). Bannayan et al, 2012 classified sky condition in northeast of Iran, they classified cloud amounts of synoptic meteorology stations in cloudy day (7-8 octas), partly cloudy (3-6 octas) and clear sky (0-2 octas). Methods and Material We have applied Cloud Fraction Parameter from Cloud product of MODIS sensor on board Terra satellite (MOD06). Data were downloaded from site of ftp: //ladsweb. nascom. nasa. gov/allData/ 6/MOD06_L2. Statistical period is from 2000 to 2013 solar year (2000 to 2014), so, the research has been done based on solar year. Cloud products of MODIS (MOD06) do not have neatly geographic data network on daily, so, we have used new method for gridding of data, At first, a network of geographical coordinates with the spatial resolution arrays of 5 × 5 km, based on the framework of Iran (25-40 degrees north latitude and 44-64 degrees east longitude) was prepared as a regular network or reference with dimensions of 618 × 353 (618 columns and 353 rows). Using geographic coordinates latitude and longitude of each cell in regular network, a framework was prepared 1. 5 times the distance between each pixel dimensions (a radius of less than 7. 5 km) and was spread on the granules geographical coordinates and the CF data within the framework of the granules were transferred to target cells in terms of latitude closest to the regular network. To transfer CF data parameters in each path to a regular network on a daily basis, this process was carried out for each individual cell in a regular network. So, CF data were ready for statistical computing and As a new database, next steps of research was carried out based on this database. Then, Sky conditions classified based on clear sky days (0-25%), partly cloudy days (25%-62. 5%) and cloudy days (>62. 5% to 100%). Daily data composite to sessional and monthly data. Then, spatial distribution and long-term average of sky condition classifications were identified in monthly and seasonal scales on Iran. Results and Discussion In Current research, the sky condition has been investigated based on Cloud Fraction parameter in cloud product of MODIS Terra satellite, at first, sky condition was classified to clear sky, partly cloudy and cloudy days based on thresholds considered. After calculating the long-term average and spatial distribution of sky condition classifications were analyzed. Due to the irregular geographical coordinate of daily granules of MODIS on country, first, the Cloud Fraction (CF) data were transferred to a 5× 5 km regular network to be able to analyze long term climatology of cloud cover. The findings of this study reveal that the highest frequency of cloudy days is in winter with 36 days and the lowest is seen in summer with 7. 8 days. The highest (lowest) frequency of clear sky days is seen in summer season with 79. 6 (45. 2) days. On monthly time scale, the highest (lowest) frequency of cloudy days is in the February (September) with 12. 8 (1. 8) days and the highest (lowest) frequency of clear days is in the September (February) with 27. 9 (14. 1) days. The spatial distribution of cloudiness indicated that the maximum of cloudy days in spring, summer and fall is seen over the south and west parts of the Caspian shores, however, in winter the maximum of cloudy days is over mountainous regions of the north. The minimum of cloudy days in spring, fall and winter is seen over south-east of the country but in spring it is far away from the south and south-east areas of the country and it is seen over central parts of Iran. The maximum of partly cloudy days is seen over mountainous areas and the minimum is over southern, central areas and also the hills and the plains. In general, the frequency of cloudy (clear) days decreases (increases) from north to the south-east but in summer it increases over south-east and in the north of Hormuz Strait and in winter over the mountainous regions of the north it has an increasing tendency and the decreasing (increasing) of cloudy (clear) days is no longer seen. Conclusion The aim of this research is identification of spatial distribution and frequency monthly and seasonal sky condition classifications on Iran, according to this, it was found that the spatial distribution obtained from the study method showed that the maximum frequent cloudy days is seen in the southern and western shores of the Caspian Sea in the Summer, Spring, and Autumn, and its minimum is seen in the southeast of country in spring, winter, autumn. these results are correspond with Rasooli et al (2014), but the maximum (minimum) territory of cloudy days and clear sky days vary over Iran in summer and Winter Compared with other seasons and this situation have also seen in some months that it differ with Rasooli et al (2014) results. Generally, the frequency cloudy days (clear sky days) decrease (increase) from north to south of country, but, this path is impaired in north of Strait of Hormuz and southeast of country in summer (July, August, September) and over the mountain heights of north of country in winter (December, January, February). The most frequent cloudy days occur in the winter and the lowest it occur in the summer. The most frequent clear sky days occur in the summer and the lowest it occur in the winter. In the monthly scale, the most frequent cloudy days occur in the February and the lowest it occur in the September.

Introduction Cloud is a special phenomenon formed by dynamic and thermodynamic changes of the general atmospheric circulation. Through dispersion and reflection of solar radiation, cloudschange energy balance of the Earth and affect its hydrologic cycleby producing rainfall in various forms. Determining the state of clouds (in terms of clouds being liquid or ice) is crucial, sinceitaffects the atmosphere feedback mechanism. Moreover, the state of clouds is related with itsheight, i. e., higher clouds tend to have an icy state. Therefore, determiningtheir statusis especially important for the accuracy of elevation estimation. The present study seeks toinvestigatetemporal and spatial variation of liquid clouds in the geographical range of Iran using information received from meteorological stations and remote sensing techniques. It aims to find the feedback of cloudsin liquid phase and theirdominant condition. Research Methodology Data received from MODIS Sensor of TERRA Satellite (2001-2015) and Cloud mask (CM) algorithm were used in the present study. Moreover, long-term data of 31 synoptic meteorological stations collected during the period of 1960– 2015 were used to compare satellite data. Followingdata decoding and required calculations, maps of each season were produced using Kriging method. Results and discussion Results indicate that maximum number of liquid clouds occurs in winter, while their minimum number occurs in summer. In winter, Rasht, Ramsar, Babolsar and Gorgan stations (with cumulative frequency of 174. 33 to 305. 66 days) have maximum frequency of liquid clouds. This country almost lacks liquid clouds in summer. Only in the coastal zone of the Caspian Sea, Rasht, Ramsar, Babolsar and Gorganstations with 153, 93. 33, 77. 66 and 26 days, respectively, had the maximum frequency of liquid clouds. The average thickness of liquid clouds in Iran was calculated on a seasonal scale. In winter, spring, summer and autumn, it was 22. 23, 17. 13, 14. 11 and 16. 7 microns, respectively. Results indicate that the average thickness of liquid clouds decreases in warm seasons. Maximum thickness of liquid clouds in winter, spring, summer and autumn was 33. 04, 24. 56, 24. 85, 22. 84 and minimum thickness of liquid clouds was 13. 98, 6. 82, 6. 27, 8. 09, respectively. In winter, maximum frequency of liquid clouds occurred in western Iran and the Caspian coastline, while maximum thickness of liquid clouds occurredin northwestern and western Iran. Moving from north to south and west to east, the frequency of liquid and icy clouds decreases. In contrast, maximum frequency of liquid clouds occurs in summer. Conclusion Results indicated that maximum frequency of winter and autumn liquid clouds mainly occur in high latitudes of northern regions, southern hillside of Alborz(west to east direction), and northwestern and western regions of the country. Maximum frequency of summer liquid clouds occurs in the Caspian Coasts, while maximum frequency of spring liquid clouds occursin the northern half and southeast regions of the country. This is well-justified due toactivities of the expected systems and local factors in each season. Liquid clouds of Iran have a nonlinear and possibly complex relationship, and factors such as hillside orientation, precipitation systems, distance from sources ofmoisture, lack of ascending factor, lack of sufficient moisture and many other factors contribute to this relationship. Evaluation of liquid clouds thickness indicated that elevated regions of central and western Zagros have the highest amount of liquid clouds in cold seasons, since low-pressure systems, fronts and mid-latitudewaves of atmosphere play a decisive role in the growthof cloud numbers in these seasons. This is also in consistencywith Masoudian (2011) results. Northwestern Iran and the Alborz belt are almost always affected by the western winds. Western winds pass over the Mediterranean Sea and its sufficient moisture resource, which play a significant role in the cloudiness of this area. Results are consistent with Alijani’ sstudy(2010) that reported 120 cloudy days in Alborz Mountains, Khorasan and northern Azerbaijan altitudes. Increased cloudiness of southern and southeastern Iran during warm seasons is related with the monsoon system in July-September, which is also confirmed by Ghasemifar et al. (2018) and its mechanism is discussed by Yadva (2016). Results are also in consistency with the results of Ahmadi et al. (2018), which examined the cloud optical thickness (COT) and the total cloud cover (TCC) of Iran. In other words, results of Ahmadi et al. (2018) also confirm our findings.

Remote sensing is an efficient tools for monitoring and estimating of agriculture planted areas.Vegetation reflection properties and some indices are used for this. This study reports the results of estimating winter wheat planted area by using MODIS (one of the TERRA sensors) images, which are prepared for 16 days periods in three different spatial resolutions, 1000, 500 and 250 meters. The images have been used for winter wheat areas of Khorasan Razavi province (North East of IRAN) during agricultural season of 2004-05. Four different areas were selected for this study. These areas are wheat farm, mountain, dense vegetation cover and desert. Then some image processing techniques and statistical analysis were used to analysis this area. Afterward we produced the wheat planted map and calculating area of wheat. Our results showed that MODIS images (which are easily available) are an appropriate data for estimation and monitoring wheat-cultivated areas.

Land surface temperature (LST) estimation is widely used in many applied and environmental studies such as agriculture, climate change, water resources, energy management, urban microclimate and environment. LST, which is the result of atmospheric-earth interaction, due to the sensitivity and influence of land surface conditions such as soil cover, soil moisture, albedo, surface roughness and the interaction of these factors with the atmosphere, can well determine changes in land surface temperature conditions. In the present study, Modis nighttime sensor products of both Terra and Aqua satellites (MOD11C3 & MYD11C3) from http: //reverb. echo. nasa. gov/reverb for LST estimation in the Jazmourian drainage basin (southeast of Iran), were used in the period 2013-2019. After providing the products with monthly and spatial time steps of 5 km, calculations on two matrices, One monthly with dimensions of 2784 x 204 (204 represents the number of observations in consecutive months of 17 years studied (17 x 12) and 2784 represents the number of gridded points (cells) in Jazmourian drainage basin area) and the other is a seasonal matrix with dimensions of 2784 x 68 (68 representing the number of observations in consecutive chapters (17 x 4) were performed. After performing the relevant statistical and spatial analyzes in Excel and GIS software environment, nighttime LST estimation was used. The results showed that the nighttime LST in the statistical period increased by about 1 degree Celsius and this increase was more in the minimum temperatures (cold period months of the year) than the maximum nighttime LST. According to the findings, the maximum nighttime LST has occurred in the low altitudes of the central and southern regions and the minimum LST has also occurred in the northern heights of the drainage basin. The seasonal spatial distribution of the Earth's nighttime LST indicates the distribution of nighttime LST in the range of-10 to +35°C in winter and summer, respectively. Extreme fluctuations in nighttime LST during the seasonal terrestrial surface well show the prominent role of altitudes and latitudes in the temperature distribution of the Jazmourian drainage basin. Also, the time analysis of the studied variable shows a positive trend of nighttime LST in all four seasons, among which the spring and winter seasons had a higher upward slope. In addition, spatial estimation of nighttime LST anomalies, while confirming its increasing trend, shows the maximum location of nighttime LST anomalies in the central and western parts and the minimum anomalies in the eastern parts and northern heights of the drainage basin. Also, the analysis of monthly anomalies of nighttime LST shows the maximum occurrence of positive anomalies with +0. 07°C in September 2016 and the minimum anomalies with-0. 01 °C. are in January 2008. In general, the values of the nighttime LST significantly increased from 2008 onwards, especially in the months related to the cold period of the year (with a greater increase in the minimum nighttime LST than the maximum nighttime LST). This indicates the nighttime LST trend of the cold period of the year towards a warmer pattern. These conditions can be considered as an indicator of climate change and lead to changes in some environmental parameters such as relative humidity, evapotranspiration, soil surface moisture, snow persistence, dew point temperature and nightly reflective energy. Considering the high capabilities of the Jazmourian drainage basin in agricultural products and also the capability of seasonal tourism in different areas of this drainage basin, the importance of investigating nighttime LST changes, in this regard, is undeniable. On the other hand, with the continuing increase of environmental sensitivities and the accelerating trend of continental climate in this drainage basin, it is suggested that in future research, while estimating other climatic variables, their correlations with LST are considered. This will provide more climate knowledge of the environmental changes that have occurred in this less studied drainage basin.