Theoretical and Applied Climatology (14344483)155(1)pp. 273-288
In the present study, the precipitation regime (PR) was investigated as a feature of the structure of Iran’s climate and its relationship with spatial-topographic variables and its spatial pattern. Spatial patterns of the indices of the PR used in the present study exhibited significant agreement in illustrating the diverse PRs of Iran. The diversity of spatial factors provided the spatial diversity of precipitation characteristics, including PR. Harmonic analysis (HA) results confirmed the country’s diverse PRs, which were attributed to different mechanisms affecting Iran’s precipitation patterns throughout the year. Using multiple methods in the present study, four PRs were identified. According to the methods used, the increase in precipitation in each location was associated with a reduction in the month-to-month difference in precipitation and an enhancement in the uniform distribution of precipitation. All indices indicated that the northern regions of Iran, including the Iranian coast of the Caspian Sea (ICCS), exhibited a uniform PR. The northwestern (NWI) and southeastern (SEI) regions displayed a relatively uniform regime, while the remaining parts of the country experienced a seasonal regime characterized by a longer dry season. Furthermore, there was a notable correlation between the PR and latitude, particularly from approximately 35 degrees northward. Moreover, there was a notable correlation between the PR and latitude, particularly from approximately 35 degrees northward. As for the southern regions of the country, beyond the latitude of 35 degrees, the spatial distribution of PRs was influenced not only by latitude but also by other variables such as longitude, altitude, and the shape and length of the Persian Gulf coast adjacent to the eastern deserts. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Theoretical and Applied Climatology (14344483)155(2)pp. 1103-1112
One of the parameters affecting albedo is snow. Therefore, the effects of snow on albedo can be a tool to understand environmental changes. Moderate Resolution Imaging Spectroradiometer (MODIS) continuously produces snow and albedo products of the land surface on a global scale and with appropriate spatial resolution and makes them available to researchers. In this study, to investigate the relationship between albedo and snow in Iran, first, the daily data of the MODIS sensor MCD43A4 and MOD10A1 products in the area of Iran in the period of 1/1/2001 to 12/30/2021 for 6770 days were downloaded from the NASA website. Since the temperature conditions for snowfall are provided from an altitude of 1700 m, was calculated the seasonal and long-term correlation between albedo and snow at altitudes above 1700 m. These altitudes, which cover 27% of Iran’s area, were known as Iran’s Mountains (Mts.). The results showed that in the winter and autumn seasons, which are known as Iran’s snowy seasons, the land surface albedo also increases with the increase in snow cover. Therefore, in these seasons, the correlation between albedo and snow over Iran’s Mts. is strongly positive. In these seasons, positive correlation covers 91 and 81% of Iran’s Mts., respectively. In spring, there is a strong positive correlation in high altitudes and a weak positive/negative correlation in low altitudes. The negative correlation in the spring season is due to the delay in the measuring time of the sensor and the conversion of precipitation from solid to liquid. In the summer season, due to the establishment of Subtropical High-Pressure Systems Azores and the increase in air temperature, the snow cover of the Mts. disappears and the albedo was expected to decrease. But with the reduction of snow cover, albedo has increased. As a result, in these seasons, the correlation between albedo and snow over Iran’s Mts. is negative. It seems that the increase in albedo in spring and especially summer is caused by the increase in the land surface temperature (LST), which requires separate research. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Pure and Applied Geophysics (00334553)180(12)pp. 4275-4293
In the current study, the decadal changes in Iran's precipitation regimes (PRs) were investigated by adopting Iran's precipitation dataset and using the precipitation index (PI). Our finding revealed that significant decadal variation occurred in the PI, which led to different spatial patterns during under investigation decades. From the 1st to last decades under study, the area decreased in the regions with equal monthly distribution of precipitation (ED). The regions with a relatively equal monthly concentration of precipitation (RED) presented a sharp decreasing trend in the first 3 decades and a slight increase in the last decade. The irregular distribution of precipitation (ID) in most of the decades covered an area above the long-term average. The highly irregular distribution of precipitation (HID) covered a small area of Iran's territory on the southern coasts. Nevertheless, its decadal variation, particularly in the first 3 decades, was relatively noticeable. The decadal variability of the number and tracks of cyclones affecting Iran showed that although the number of cyclones increased from the 1st to the last decade, the origins of cyclones in the 1st decade were mainly in the Mediterranean Sea and the Red Sea. In the following decades, the diversity of the origins of the cyclones was one of the decades' characteristics. In addition, from the 1st to 3rd decade, the cyclone centers (excluding the Red Sea-Sudanese cyclones) took a more northerly route. This decadal variation in cyclones' characteristics might lead to the decadal variation of PI in Iran. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Theoretical and Applied Climatology (14344483)152(1-2)pp. 599-615
In the current study, the variation of Iran’s rainy season (RS) was investigated as a manifestation of climate change by using three daily datasets from 1976 through 2015. The results revealed that Iran’s RSs occurred on two spatial scales (widespread and regional). The decadal variability of the onset, cessation, and length of the widespread rainy season (WRS) was investigated as a season affected by large-scale atmospheric systems. Our findings showed that the onset of the rainy season (ORS) experienced a significant decadal variation on the Iranian coast of the Caspian sea (ICCS), the northwest of Iran (NWI), the Zagros mountains, and in the eastern half of the country, where the eventual consequence led to delay in the ORS. The cessation of Iran’s RS in the first decade was not significantly different from the cessation of the RS during the entire understudy period. From the second decade, the difference started in the form of spots of up to 100 days early cessation of the rainy season (CRS). In the third decade, spots extended over the northern part of the country, covering an area that included NWI to the south and finally the southeast of Iran in the fourth decade. Although the number and origin of cyclones concurrent RS increased from the first to the last under investigation decades, from the third decade, the cyclone centers (except for the Red Sea-Sudanese centers) took a more northerly direction. Consequently, the moisture flux convergence reduced, and the dust storm increased over Iran. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Theoretical and Applied Climatology (14344483)153(1-2)pp. 709-726
Land surface albedo (LSA) and land surface temperature (LST) are used in many environmental studies. Linking topographical factors (altitude, aspect, and slope) with LST and LSA plays an essential role in climate modeling, environmental changes, hydrology, energy balance, architecture, etc. Knowing the relationship between them is of particular importance. In this research, the data of two remote sensing products that are Modis Terra and Aqua (for the period of 2000–2019) were used to investigate the link between topographical factors, LSA, and LST. Investigating the relationship between the altitude, aspect, and slope with LST showed that this parameter is strongly influenced by topographical factors; an increase in altitude, aspect, and slope leads to a decrease in LST. The correlation coefficients of altitude, aspect, and slope with the LST are estimated to be − 0.968, − 0.927, and − 0.684, respectively. The results of linking topographical factors with albedo showed that this parameter has a strong link with altitude, so as the altitude increases, there would be an increase in albedo. But there is no significant relationship between aspect and slope considering the low correlation coefficients. The correlation coefficients of latitude, aspect, and slope with LSA are 0.95, 0.087, and 0.18 respectively. Therefore, the altitude, aspect, and slope are important factors affecting the LST in Iran. Altitude also plays a vital role in the Iran’s LSA. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Journal of the Earth and Space Physics (25383906)49(2)pp. 503-516
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. © 2023 Institute of Geophysics. All rights reserved.
Journal of the Indian Society of Remote Sensing (09743006)51(6)pp. 1297-1307
Environmental changes such as ablation of ice and snow, drying of lakes, deforestation, desertification and urbanization may affect the thermal properties of the land surface, and hence, it affects the land surface temperature (LST). MODIS LST data, make it possible to investigate the variations in the frequency distribution of LST. In this research, 16 years of MODIS\Aqua LST data (2002–2022) have been analyzed using principal component analysis. This study shows that the frequency distribution of LST in Iran depends to a great extent on altitude and then depends on the terrain surface features. Lakes, river systems, sand dunes, deserts, woodlands, forests and metropolitan areas are among the terrain surface features that affect the frequency distribution of LST. Hence, analysis of the frequency distribution of LST may be considered as a tool for identifying the geographical boundaries of these terrain features. Additionally, it could be a robust tool for tracking the changes in the boundaries of such geographical phenomena over time. Frequency analysis of LST in Iran reveals many natural and anthropogenic environmental changes. For example, the analysis shows that the drying out of Zayanderud downstream and Urmia Lake is related to man-made changes in the upstream. The comparison of the interdecadal of LST shows that the frequency of LST has increased in some temperature categories and decreased in some other temperature categories. In general, the frequency shift of LST both during the day and at night has been toward higher temperatures. © 2023, Indian Society of Remote Sensing.
International Journal of Climatology (10970088)43(10)pp. 4396-4423
Identifying the rainy season (RS) is significantly important from the meteorological, hydrological and socio-economic points of view. In the current study, the climatology of Iran's RS was identified based on developing a definition by mainly relying on examining daily rainfall observations from 2188 stations in the period of January 1, 1971–December 31, 2015 (45 years). Accordingly, it was revealed that at most two RSs could be distinguished in Iran; and there was a widespread rainy season (WRS) covering the entire country in three consecutive months (phases). In the northwest of the country, the Alborz Mountain chains, and in the southeast of Iran, the RS was mainly interrupted by a dry season. Therefore, two RSs occurred in these areas (widespread and regional rainy seasons [RRS]). The four withdrawal phases of the RS were relatively different on the regional scales. However, they generally showed a relation with latitudes. Unlike the onset date of phases of the RS, these phases did not occur at the same intervals. The diversity of spatial factors in Iran (including geographic coordination, topographic features and sea surface temperature of surrounding seas) caused the spatial diversity of the timing of the RS. Consequently, linear relationships could not illustrate the nature of the spatial pattern of this diversity. The linear spatial relationship was statistically significant only for the onset date of the RS. The regression model used in the present study showed that despite the effect of local factors on the onset date of the RS, the major regional differences could be attributed to systems and mechanisms that probably affected the onset date of the RS from outside of the country. © 2023 Royal Meteorological Society.
Advances in Space Research (02731177)71(3)pp. 1451-1472
The goal of this study is to assess the performance of four widely-used satellite precipitation products in capturing extreme precipitation indices across Iran over the period 2001–2018; these products include GPM IMERG (Integrated Multi-Satellite Retrievals for Global Precipitation Measurement), TRMM 3B42 (Tropical Rainfall Measuring Mission), CHIRPS (Climate Hazards Center InfraRed Precipitation with Station data), and PERSIANN-CDR (Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record). For this aim, a national gridded precipitation dataset was developed using a dense network of rain gauges as a reference dataset. The results suggest that the IMERG product outperforms the other three precipitation products in capturing extreme precipitation indices both temporally and spatially. TRMM 3B42 data show promising results in identifying many extreme indices, while the CHIRPS and PERSIANN-CDR products show less performance in accurately generating many of the extreme precipitation indices. © 2022 COSPAR
Acta Geophysica (18957455)71(2)pp. 1063-1084
In the present study, according to a provided definition of the widespread rainy season (WRS), the onset of the WRS (OWRS) and the cessation of the WRS (CWRS) occurred in three and four phases, respectively. The phases of the OWRS (26 Sep, 5 Nov, and 15 Dec) were related to the interaction of the sub-polar low pressure (central pressure lower than 996 hpa) and the Siberian high pressure (central pressure higher than 1020 hpa) at the tropospheric lower level and the ridge of Arabia at the 500 hpa (higher than 5850 m). Thus, the eastward-moving of the Mediterranean cyclones (the number of cyclones from the first to the third phase was 264, 245, and 407, respectively) bred the positive moisture flux convergence and reduced the outgoing long waves radiation (OLR) values to about 240 W/M2. Simultaneous with the northward shift of the sub-polar low pressure and penetrating the Siberian high pressure to the west of Iran and the extension of 300-hpa jet stream, the next phase of the OWRS appeared in the southern regions. The four phases of the CWRS (6 Oct, 31 Dec, 5 Mar, and 3 Apr) commenced with the strength (central pressure higher than 1032 hpa) and expansion of the Siberian high pressure, concurrent with the formation of high pressure in the northwest of Iran, followed by the second phase on the Iranian coast of the Caspian Sea. The reduction in gradients of 500 hpa height in the latitude of 20–40 N was associated with increased zonal wind in the longitude of 40 E toward the east and the weakening of the jet stream at 300 hpa. In addition to increasing the OLR (more than 250 W/m 2), the thermal low pressure, positive values of meridian wind, and negative values of zonal wind over Iran led to the transfer of the characteristics of the adjacent desert, and the maximum OLR planetary belt moved toward the country. Contrary to previous studies, which attributed the onset and cessation of the rainy season to a few atmospheric features, the results of the current study suggest that the onset and cessation of the rainy season resulted from a very complex interaction of several tropospheric factors and geographical features of different regions. This interaction, primarily in geographically diverse realms (e.g., Iran), leads to complicated spatial patterns of the onset and cessation of the rainy season. © 2022, The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences.
Iranian Journal of Remote Sensing and GIS (25886185)13(4)pp. 35-50
The expansion of urbanization and the increase of population in metropolises and the growth of industrial activities of cities, It has caused changes in urban area climate. One result of these changes is the city's heat islands. The city of Mashhad has also grown rapidly in recent years. This study investigates the heat/cold island of Mashhad metropolis based on the background climate in order to identify its spatiotemporal behavior. For this purpose The MODIS Terra and Aqua land surface temperature (LST) data were obtained and the heat island was examined accordingly. A new was used to measure the heat island. In this method, Modis land use data was used to determine the urban and suburban boundaries as well as to determine the land use type of the study area. The background climate was determined based on Far-side temperature and the representative non urban area was selected based on the most frequent temperature and the heat island was calculated. Survey of heat/cold island in the daily period showed that during the day the average temperature of city is lower than non urbun temperature and at night is higher. Also the seasonal survey of heat island/could island of Mashhad metropolitan shows that daily cold island is the highest during the warm seasons and lowest in the cold seasons and the seasonal variability of nightly heat island is less than the daily cold island. The core of the daily cold island is located between the Haram and the Shahid Fehmidah Square towards the western area of Mashhad. The day time cold island matches the areas of the city with high vegetation coverage. The core of the nightly heat island is consistent with the old texture and dense area around the Haram towards the northwest of the city. The heat/cold island intensity is also directly related to the wind speed. The role of land use in intensifying or reducing the intensity of the heat island of Mashhad is well seen. In the development of the city, more attention can be paid to the use of urban land use in order to moderate the temperature of the city. © 2022, Shahid Beheshti University. All rights reserved.
International Journal of Climatology (10970088)42(4)pp. 2039-2064
Satellite remote-sensing products with high spatial and temporal resolution are viable sources of precipitation information, especially for data-sparse and remote regions. The aim of this study is to examine the performance of four precipitation products including Integrated Multi-satellite Retrievals for GPM (GPM IMERG), Tropical Rainfall Measuring Mission (TRMM 3B43), Climate Hazards Centre InfraRed Precipitation with Station data (CHIRPS), and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) in estimating precipitation and capturing meteorological droughts over Iran for the time span from 2001 to 2019. For this aim, a ground-based gridded precipitation dataset was constructed over the country using a dense network of quality-controlled rain gauges as a reference dataset. Different statistical metrics including the correlation coefficient (CC), the bias, the relative bias, and the root mean square error (RMSE) were applied to evaluate the performance of the products. The results suggest that GPM IMERG and TRMM 3B43 outperform CHIRPS and ERA5 in capturing the spatial distribution of precipitation and meteorological drought events across the country. The estimates of precipitation from the four products are seasonally influenced, with the least accurate precipitation estimates during summer season over the southern shores of the Caspian Sea. The GPM IMERG and TRMM 3B43, with higher CC and lower RMSE, show better performance in detecting drought events at both short and long time scales while the CHIRPS demonstrates the least accuracy. Spatially, all of the products show the best performance in identifying drought events over western and southwestern regions. © 2021 Royal Meteorological Society
Theoretical and Applied Climatology (14344483)150(1-2)pp. 389-403
The recent droughts in Iran have contributed to declining runoff, diminishing lake water levels, and rising salt levels due to lower runoff. This study aims to quantify how the recent changes affected to investigate the trend of land surface albedo in Iran between 2000 and 2018. Accessing field data from the Iran is difficult, and thus the common understanding of climate change in the region is strongly based on satellite data. We use remotely sensed data of land surface albedo, land surface temperature (LST), number of snow-covered days (SCDs), normalized difference vegetation index (NDVI), and the land cover type, obtained from Moderate Resolution Imaging Spectroradiometer (MODIS). The results show decreasing trends in albedo and SCDs by − 0.02 and − 0.52, respectively, and upward trends in the LST and NDVI data by 0.07 °C and 0.009, respectively. Due to the recent drought condition in Iran, SCDs decreased significantly, which might explain the reason behind the albedo decreases in winter time in Iran. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Climate Research (16161572)84pp. 59-73
Climate change can manifest in many ways, including impacts on the start, end, and duration of the frost-free season. We examined the climatology and variability of the first fall frost day (FFFD), last spring frost day (LSFD), and length of the frost-free season (LFFS) across Iran for the period 1978-2017. Trend analysis revealed that FFFD shifted later by 6.4 d over the study period while LSFD shifted earlier by slightly over 2 wk, and LFFS is now >3 wk longer than it was only 4 decades ago. Since land-use changes around meteorological stations may affect the temperature measured at these stations (especially the magnitudes of nocturnal cooling rates), atmospheric thickness changes, which reflect temperature changes and are independent of stationbased measurements, were used as a secondary dataset to investigate minimum temperature trends. The analysis revealed a very strong relationship between frost-related indices and atmospheric thickness. Sequential Mann-Kendall statistical analysis revealed abrupt changes in the applied frost-related indices, minimum temperatures, and atmospheric thicknesses. The first abrupt changes in FFFD and LFFS occurred around 1996, which matched the timing of abrupt changes in atmospheric thickness over Iran. Interestingly, seasonal trend analyses of minimum temperature over the Northern Hemisphere using Era5 reanalysis data indicated consistent regional patterns of warming over the last 4 decades. The results suggest that the increase in LFFS is largely driven by regional-scale warming as opposed to local urbanization and/or land-use changes. Our results document an important and ongoing change of potentially considerable interest to agriculturalists in Iran and elsewhere. © 2021 Inter-Research. All rights reserved.
Landscape and Ecological Engineering (18601871)17(2)pp. 147-156
The cities that are built on the arid biomes with the hot and dry climates can adjust the temperature (oasis effect) and create the urban cool island (UCI) during the day. As the background climate of the Isfahan metropolis is warm and dry, we can expect an UCI during the day. The MODIS land cover product data were used to distinguish between the urban and nonurban areas. The MODIS/Terra/LST data from 2000 to 2016 were then used for day-time view to examine the UCI. In the next step, the UCI intensity index was calculated by the spatial correlation representative pixel method for the city and the background. This study showed that due to the passage of the Zayandehrood river from the middle of the city and the expansion of vegetation in the urban environment, the metropolitan area of Isfahan is 3.5° cooler than the suburban barren lands during the day. The UCI intensity index has been intensified over the last few years and has fallen below − 4.5°. The studies have shown that the UCI intensity index is weakened during the cold months and intensified in the warm months of the year. The seasonal changes in UCI intensity in the metropolitan area of Isfahan can be related to the high variability of vegetation throughout the year. © 2021, International Consortium of Landscape and Ecological Engineering.
Physical Geography (02723646)42(3)pp. 283-295
Despite its adjacency to seas in the north and the south, Iran suffers from relatively low humidity. Spatial distribution of the atmospheric humidity across Iran is a function of altitude, distance to water bodies, and moisture advection. The analysis of the daily data on precipitable water from the MODIS Aqua sensor for a period of 15 years shows that average precipitable water across Iran is 12 mm. This quantity is maximal near the coasts, with the coasts of the Oman Sea exhibiting the highest values of precipitable water. In the vicinity of the Caspian Sea, the maximum precipitable water is observed at about 4 km to the shoreline, while it is 11 km away from the shoreline when it comes to southern coasts of Iran. In the areas far from the sea where the altitude exceeds 366 m, the precipitable water is mainly affected by the altitude and decreases logarithmically with the altitude. © 2020 Informa UK Limited, trading as Taylor & Francis Group.
Asakereh, Hossein,
Hedjazizadeh, Zahra,
Tarkarani, Fatemeh,
Karbalaee, A.R.,
Hedjazizadeh, Z.,
Masoodian, S.A. Theoretical and Applied Climatology (14344483)145(1-2)pp. 245-260
The aim of this study is to investigate the spatiotemporal variations of albedo in Iran. To this aim, the daily albedo datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) from onboard Aqua and Terra (MCD43A3v006) were applied for the period of 2000 to 2019 with a spatial resolution of 500 x 500 m(2). First, the long-term average of Iran's albedo was calculated; the obtained results show that the average albedo of spring, summer, autumn, and winter in Iran is 13.7%, 14.7%, 15.2%, and 19.2%, respectively. Second, the temporal-spatial variations of albedo values in Iran were analyzed using principal component analysis, and the results showed that the three main components are able to explain 97% of the data variation. The first component explains more than 74% of the total changes, the second component more than 20%, and finally, the third component explains more than 3% of the changes. Finally, the linkage between the three main components with aspect, slope, and elevation was examined in Iran. The results showed that the role of solar zenith angle, elevation, and aspect in the first and third components and also the role of slope and elevation in the second component were the most significant. In general, it can be said that snow cover in the first component, salt cover in the second component, and also snow reservoirs in the third component had albedo above average; this issue depends on the roughness and the surface of the ground. The results showed that this technique is very suitable for the analysis of the spatiotemporal variations of Albedo.
Advances in Space Research (02731177)66(9)pp. 2094-2112
The goal of this study is to examine the capability of the TRMM 3B42 product to detect spatial and temporal patterns in extreme precipitation events over southwestern Iran during the period of 1998–2016. A ground-based gridded precipitation dataset was created using a dense network of surface observations for the evaluation process. Various extreme precipitation indices in the three categories of fixed threshold indices, grid-related threshold indices, and non-threshold indices were examined and compared with the ground-based gridded precipitation dataset. The findings suggest that the TRMM 3B42 product is able to capture the spatial and temporal behavior of many extreme indices especially for fixed and non-threshold indices. In terms of the spatial error metrics, the satellite product has better performance over mid-elevated areas in the south and southeastern parts of the study region. © 2020 COSPAR
Climate Research (16161572)82pp. 55-73
Characterizing the errors in satellite-based precipitation estimations for drought monitoring is of great importance, as these estimations provide both spatially and temporally complete records. The aim of this study was to evaluate satellite-based quantitative precipitation estimates to monitor meteorological drought in southwestern Iran. The reliability of the Tropical Rainfall Measuring Mission Version 7 products (3B42 and 3B43) in estimating the standardized precipitation index (SPI) was evaluated against a ground-based gridded precipitation dataset at 0.25° spatial resolution for 1998−2016. The analysis conducted for the SPI at various time scales revealed that both products (3B42 and 3B43) are capable of capturing the spatial and temporal behavior of drought events over the study region, with the best performance at SPI6. 3B43 is also more efficient in the identification of shorter severe drought events compared to 3B42. The findings suggest that both satellite products, particularly 3B43, are suitable to be used directly for SPI computation in the region for drought monitoring and early warning in terms of the accuracy and the spatial and temporal resolutions they provide. © Inter-Research 2020 · www.int-res.com
Journal of the Indian Society of Remote Sensing (09743006)48(2)pp. 263-270
The population of Isfahan City has been increased by ten times during the last six decades. This increase has had extensive environmental consequences. In this period, drying up of Zayandehrood River, increase in temperature and variability of precipitation has exacerbated the environmental conditions. Formation of the heat island is only one of the consequences of environmental changes in the last decades. The heat island also has many consequences in terms of health and water and energy consumptions. In this research, the land surface temperature (LST) data corresponding to daytime and nighttime using MODIS Aqua/LST from 2000 to 2016 are utilized. Using these data, the background climate of Isfahan metropolis was detected by the distance–azimuth diagram method. Then, the representative pixel within the city and the representative pixel of the background climate were identified. Based on time series of LST over these two pixels, SUHI index of Isfahan metropolis was calculated. Investigations showed that Isfahan metropolis area is colder than suburbs during the day but at night is about 2 K warmer than its surroundings. The intensity of the SUHI is maximal in January and turns weaker in summer. Regarding the temporal and spatial behavior of Isfahan metropolis SUHI, it seems that changes created by the urban concerning the moisture, albedo and composition of the atmosphere have a great role in the formation of the SUHI. Zayandehrood River has a major role in mitigation of temperature at the land surface, and its drying up has environmental consequences. © 2019, Indian Society of Remote Sensing.
Journal of the Earth and Space Physics (25383906)45(1)pp. 149-164
Meteorological radar is usually used to estimate rainfall. The relationship between rainfall and the reflectivity of the radar is exponential. Measurement of the intensity and amount of precipitation in the management of water resources, agriculture, and flood alert is widely used. Radar and rain gauges can better estimate the amount and spatial distribution of rainfall. Marshall et al. (1947) proposed = based on the relationship between the reflectivity coefficient Z and the precipitation intensity R. Here, a and b are coefficients of the model and may differ in different places and seasons. The factors affecting these variables are: 1- type of rainfall, 2- Season; 3-Geographic and Topographic Surface of the Region. The size of precipitation drops and their distribution varies in different rainfalls. The sources of error in the radar are (1) the difference in radar reflection height, that is related to the height of the ground, while the rain-gauge measures rainfall on the earth's surface. 2) Radar calibration error. 3) Echoes of recurrences from obstacles near the ground. 4) Radar beam attenuation 5) Unrealized echoes of solid phenomena such as hail, snow, melting region. Estimates are more credible near radar. The best way to collect rainbow data is to use both radar and rain gauge simultaneously. Data used in this study include two series of ground station data and radar data. The rain gauge was used between 30 and 100 kilometers from Amirabad radar. The rainfall in July and September 2015 were selected. The severity of the two selected rainfall was appropriate, and their rainfall was remarkable. In this research, radar beam angles were measured at 0.2, 0.3, 0.4, 0.5 and 0.6 degrees as well as radar beam at constant altitudes of 200, 500 and 1000 meters from ground level. At the specified times, the radar reflection value was matched to the amount of precipitation obtained from the rainfalls during the same time interval. In the coordinate system on the vertical axis, the values of log Z (logarithm of reflectivity) were plotted on the horizontal axis and log R (rainfall rainfall intensity logarithm) and correlation between the logarithm of reflection and the logarithm of precipitation were obtained by regression method by which linear equation is extracted where the slope of this line is equal to b and the width of its origin is log a. For all the studied stations and for both selected precipitation and all selected angles, the values of the new radar parameter were obtained separately and the new values of radar precipitation were estimated with the help of new parameters and the relation Z = aR. Using the obtained coefficients, the intensity and total radar rainfall were estimated. The results were different for each station. Regarding estimated radar rainfall values and station distance from the radar, for each station, the optimal beam angle was chosen to have the best estimate of precipitation. In Gorgan, Sari, and Dash-e-Naz ratio of precipitation estimated by radar to rain gauge measurement is about 90 percent. Meanwhile in Babolsar and Banda-e-Gaz the ratio is only 2 percent. Estimated rainfall was 12 percent higher at Gomishan station. At Amol station, it was 25% less than the rain, measured. Because it was difficult to get radar coefficients for each station as it took a lot of time. So, for the rain event of September 1 and 2, 2015, using the rainfall data of all ground stations and the radar reflection coefficient Z, a general equation was obtained. Comparison of total radar precipitation data before calibration and after calibration, with rainfall values of ground stations, showed that in most stations, the total estimated rainfall data of the radar after calibration, approached the amounts of actual rainfalls. The average rainfall increased from 6.8 mm to 28.5 mm, and just 3 mm lower than the average rain gauges. Estimated rainfall data in two samples of the hot season of the Amir Abad radar showed that the range of radar parameters was high, and their value was very different from the radar default value. The estimated rainfall was much lower than the rainfall before calibration. If a radar is calibrated for each precipitation and location, the estimated radar precipitation value is very close to what is measured by ground stations. The results of this study showed that radar coefficients are different for each rainfall. It is also different for rainfall that occurs in one area at different times, and this depends on the geographic location and distance from the radar. To achieve better results, the number of additional stations and the number of additional rainfalls should be studied. © 2019 Institute of Geophysics. All rights reserved.
Iranian Journal of Geophysics (20080336)13(2)pp. 26
All objects whose temperature exceeds absolute zero (-273°C) can emit energy. The amount of energy emitted from the objects depends on their temperature and can be measured according to Stephan-Boltzmann's law. The maximum emission of this energy is at a certain wavelength defined by Planck's law. Regarding the surface temperature of the sun, it emits maximum energy at a wavelength of 0.48 microns, in the middle of visible waves, while the Earth emits its maximum energy at 10 microns (infrared) wavelengths. This radiation which starts from 3 microns and continues to 100 microns (infrared), is known as Outgoing Long Radiation (OLR). Measuring this radiation is very important for understanding the energy balance and the temperature of the Earth. Because of the difficulties in measuring this radiation, the use of remote sensing data can effectively help in understanding the tempo-spatial variations of OLR. The purpose of this study is to estimate the seasonal trend of Iran's outgoing longwave radiation by using National Oceanic and Atmospheric Administration (NOAA) satellites. In this study, the daily mean outgoing longwave radiation data for the period 1988/3/21 to 2018/3/20, with 1° spatial coverage, was extracted on a global scale from the United States Climate Data Record (CDR) database. Then, based on nearly 700 million pixels, the seasonal mean of Iran's outgoing longwave radiation was calculated for each year, and a time-space matrix was obtained with dimensions of 154*30, for each season. The rows of the matrix are locations (pixels) and the columns are the time (season). For each season of the year, the nonparametric test of Mann-Kendall was calculated at a confidence level of %90 for each individual pixel. The results showed that there was no negative trend in different seasons in Iran, and only in winter, Iran's territory has an extensive positive trend. Hence, the outgoing longwave radiation does not show trends in other seasons of the year. The positive trend of the outgoing longwave radiation during winter is due to cloudiness and snow in most of Iran. Also, in this study, the long-term mean outgoing longwave radiation pattern of Iran was calculated for each season, separately. Findings of the long-term mean of the seasons showed that outgoing longwave radiation depends on latitude and topography of the earth. So, the highest outgoing longwave radiation is seen in low and flat latitudes (especially in summer) and the lowest one is seen in high and uneven latitudes(especially in winter). © 2019 Iranian Geophyisical Society. All rights reserved.
Physical Geography (02723646)39(4)pp. 354-367
Land Surface Temperature (LST) is considered important in monitoring the energy flux between the land surface and atmosphere. Due to the diversity of topography in Iran and its effect on the climate diversity, we decided to study the effect of topography on the LST variations. To this end, the LST digital data derived from the observations of the MODIS Terra and Aqua were used. The results indicated that, during the daytime, from sea level up to a height of 400 meters, the LST increased, and then the temperature decreased with increasing altitude, and up to a height of 3000 meters, there was a strong correlation between the two. LST lapse rate was more during the daytime compared with that of the night time and it was more during the winter compared with the summer. LST lapse rate showed larger variability in diurnal cycle, but its monthly patterns were similar in different aspects. The aspect had substantial effect on LST inversion elevation. Furthermore, the inverse relationship between LST and slope was strong in slopes up to 20°. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
Water (Switzerland) (20734441)9(12)
The Karoon River Basin, with an area of about 67,000 km2, is located in the southern part of Iran and has a complex mountainous terrain. No comprehensive study has been done on the spatial and temporal variations of snow cover in this region to date. In this paper, daily snow data of Moderate Resolution Imaging Spectroradiometer MODIS Terra (MOD10A1) and MODIS Aqua (MYD10A1) were examined from 1 January 2003 to 31 December 2015, to analyze snow cover variations. Due to difficulties created by cloud cover effects, it was crucial to reduce cloud contamination in the daily time series. Therefore, two common cloud removal methods were applied on the daily data. The results suggested that in winter nearly 43% of the Basin's area experienced a negative trend, while only 1.4% of the Basin had a positive trend for snow-covered days (SCD); trends in fall and spring were less evident in the data. Using a digital elevation model of the Basin, the trends of SCD in 100 m elevation intervals were calculated, indicating a significant positive trend in SCD during the fall season above 3500 m. © 2017 by the authors.
Indian Journal of Science and Technology (discontinued) (09746846)9(40)
Objectives: The purpose of this study is to find the relationships of snow-covered days (SCDs) with topographic variables such as elevation, slope and aspect by using MODIS data. Methods/Statistical Analysis: MODIS data were used from 1 January 2003 to 31 December 2015. Due to cloud contamination in the daily data of MODIS snow products, it is not reasonable to use the data without any processing aimed at reducing cloud blockage. To reduce cloud cover effect, the daily data of MOD10A1 and MYD10A1 were combined and a three day filtering technique was applied to further reduce cloud cover effect. Findings: 1) The relationship of SCDs with elevation is not necessarily a linear relation; 2) The slope value of 22° is the critical slope in the Basin above which the snow accumulation decreases; and 3) The most SCDs are on the N and NE facing slopes and the least SCDs are on the SW facing slopes. Application/Improvements: The study showed that the slopes steeper than 22 degree are not suitable for snow accumulation. So in a country like Iran that is 3 degree Celsius warmer than the globe and snowfall frequency is dramatically low and this may be considered as a new restriction to accumulation of snow in high altitudes of the country.
Theoretical and Applied Climatology (14344483)120(1-2)pp. 367-376
This study compares the precipitation regimes by using harmonic analysis during the last four decades (1965–2004). We used the measured precipitation data from 428 rain-gauge sites and weather stations distributed across Iran by applying 15 × 15 km spatial grids to generate the interpolated data. Data validations were carried out by statistical tests. In this study, first three harmonics of precipitation variances were evaluated. Variability of precipitation regime was explored by using three harmonic analysis methods. In addition, the effect of geographical factors (GF) (site elevation, latitude, and longitude) affecting the precipitation regime (P) was verified by multivariate regression method. The resulted regression equation between P and GF for spring showed the highest correlation coefficient (r = 0.79). For other seasons, r was lower than for spring and varied between 0.26 (summer) to 0.58 (autumn). Analysis of the first harmonic proved that the main precipitation regime in Iran tends to concentrate in one specific season (winter) as a result of large-scale Mediterranean systems passing over the country. In other words, the first harmonic is able to explain most of the precipitation variations which are caused by large-scale atmospheric circulation. For all the three harmonics, variances of precipitation were mainly a function of the geographical factors. This effect was more evident in the third harmonic; in such a way that increasing the latitudes caused higher precipitation variance. This means that the precipitation regime in northern sites is more sensitive to the local factors than those of southern sites. The results of this research can be used for reliable estimation of precipitation in ungauged sites. © 2014, Springer-Verlag Wien.
Journal of the Earth and Space Physics (25383906)40(4)pp. 155-168
Temperature is one of the essential elements of forming a climate and plays a crucial role in the lives of flora, fauna and human activities. The extreme temperature is one of the thermal indexes in meteorological and climatological studies. The extreme temperature is divided into two types: the extreme warm and extreme cold. The extreme warm includes the temperatures much above the normal value and the extreme cold includes temperatures much below the normal value. Studying the extreme warm events due to their social and economical effects and their impact on human's health has prominent importance. In order to regionalize the extreme warm of Iran, we used Sphezari dataset. The Sphezari base has been provided from the average temperature based on daily data from 663 synoptic and climatological stations from 1 January 1961 to 31 December 2004. The pixel of this dataset has been calculated in the form of 15 × 15 km2 and by kriging method. Therefore, the matrix dimensions of day to day temperature of Iran is in the form of 15992 × 7187 Sphezari dataset. In this dataset the rows (915992 days) represent the time and the columns (7187 pixel) represent the place. We have used normalized temperature departure index to identify the events of extreme warm events in this survey.The index has been introduced by Fujibi et al. (2007). To obtain this index, the long term average temperature of calendar days must first be calculated. The thermal amounts of 44 years are averaged to calculate the long term mean temperature of the given days. To avoid the existing noise in the daily mean temperature,the nine-day running average was applied three times in order to filter out day-to-day irregularities. After carrying out this phases temperature departure (AT) of each of the 15992 days is investigated in the long term mean of the same day. Thus it is necessary that the amount of the absolute temperature departure becomes standardized by the averages of AT. In this way, the amount of temperature departure in different times of a geographical point and different spatials in a particular time can be compared to each other. As an index of day-to-day variability, the variance of AT in the 31 days centered on each calendar day was calculated as σ2 Then the moving mean of nine days σ2 in three times will be conducted to dimnish the noise. Then normalized temperature departure (NTD) indexed with x∗ symbol was calculated. This index was calculated for 7187 pixels, each pixel for 15992 days. Then, the index of location x∗ was investigated over Iran and the percent area of Iran which had the amount of x∗≥2 was determined. In this way, an index of 15992 × 2 was obtained, indicating the greatness highest temperatures of Iran for the period of 1 Jan 1961 to 31 Dec 2004. This matrix was arranged according to the mean of NTD and area amount. The first 264 days was selected as the sample. Whereas the temperature was in over of Iran, at least, 2 standard deviation more than its long term mean (x∗≥2) and a large area was warmmer of Iran. The NTD of 7187 pixels in the selected 264 days was classified using the cluster analysis technique and agglomeration based on the entered method. Results of this research showed that according to the extreme warm events, Iran can be classified into five distinctive regions.The most important characteristics of the extreme warm events in Iran are as follow: Most of the extreme warm events of Iran have occurred in winter and autumn days. The maximum warm events of Iran has occurred in west and southwest of Iran, specially, in recent years. NTD is one degree above the other areas. The setting of this region with the maximum rate of the NTD index shows that the systems creating the extreme warm events was entered from west and southwest of Iran; thus there are regions was influenced more and prior to the other regions. The highest spatial standard deviation belongs to these regions. It means that these regions have little spatial similarity from the viewpoint of the NTD index. It means that the extreme warm events creating systems donot attack this region equally. Some regions are influenced more and some less than others by these systems. Maximum temporal standard deviation belongs to northern and western regions. This means that events of the extreme warm events happen in these regions in some months. Therefore the systems creating the extreme warm events in these regions are activated in part of the year. The least temporal standard deviation belongs to the northeastern region and the least spatial standard deviation belongs to south and southeast regions.
Journal of the Earth and Space Physics (25383906)38(4)pp. 241-258
In different regions, precipitation takes place with different persistencies and every persistency supplies a share of rainfall days and precipitation. Therefore, the importance of rainfall persistence could be evaluated in all places. Iran is located in Mid-Latitude of an arid region, in which the mean rainfall is 250 mm and it has dramatic tempo-spatial changes. Rainfalls with short persistence are of characteristics of arid regions and it is also tangible in Iran. However, Iran's rainfalls persistence ranges from 1 to 45 days and have dramatic tempo-spatial changes, but the maximum amount and days of rainfalls are supplied by rainfalls with short persistency. So, the phenomenon of rainfalls with long persistency is considered as an extreme event which has extreme variability. As the persistence of precipitations increases, their role in generating Iran's rainfall days decreases severely in such a way that the maximum rainfall days of Iran is supplied by one-day rainfalls. However, the share of one-day rainfalls in the supply of precipitation days of Iran's Western half is more accentuated. In contrast, the increase in the persistence of rainfalls does not have an identical role in decreasing the supply of Iran's precipitation. As the persistence of precipitations increases, the share of precipitation in the Central and Southwestern Iran decrease severely, but in Western and Northern Iran, vice versa is the case. In some heavy precipitation regions of Iran's Western half, the decrease of precipitation persistence is associated with the decrease of the share of precipitation supply and in other regions; the decrease of the share of precipitation supply is gradual. Therefore, in every space, some of the persistent rainfalls supply the great share of precipitation days and precipitation amount and are considered important. However, it is possible that this precipitation persistency do not have such importance in those areas. Every kind of variability and change in the role of precipitation persistence in every space will be considerable. Spatial changes of one-day precipitation's share in the supply of Iran's precipitation days and precipitation amount could be evaluated from this angle. To evaluate the changes in one-day precipitation' share in the supply of precipitation days and precipitation amount, the daily observations of precipitations in 1437 stations of throughout Iran was used. Drawing upon Kriging method, the observations of the stations were generalized in a regular network by 15*15 km dimensions and Iran's isotheral digital maps were developed from 1961/03/21 till 2004/12/30. These digital maps include daily time series (15991 days) of precipitation amount for 7187 cells. Precipitation persistence in the time series of every cell was evaluated and in addition to that, their share in the supply of precipitation days and precipitation amount of each cell were also calculated. Then, the most important persistence of Iran's precipitations (one-day persistence) was identified and their importance was investigated. Yearly and monthly time series of one-day precipitation' share in the supply of precipitation days and precipitation amount were entered in a trend analysis for evaluating and understanding its changes and its results were considered. In spatial analyses including identification of climatologically variables trend, more confident way is that firstly, spatial interpolation is done; then, an appropriate trend test is performed on the data on the nodes. The results obtained from such analyses not only enjoy higher degree of spatial attribution, but based on closeness principle, spatial order of points themselves provide intuitional reason for accepting or rejecting trend analysis. One-day precipitations supply more share of Iran's precipitation days compared to remaining precipitation persistencies in such a manner that it may be noted that in all regions of Iran, the frequency of one-day precipitations is maximum compared to remaining precipitation persistence. In contrast, Iran's precipitation is provided by different persistencies and the share of one-day precipitations in precipitation supply is maximum only in Western half (Central and Southeastern parts). However, although oneday precipitations do not have much importance throughout Iran, the degree of their importance in Eastern half is maximum compared to Western half. The share of on-day precipitations in the supply of Iran's precipitation days and precipitation amount has changed with time. The results of yearly changes of share of on-day precipitations in the supply of Iran's precipitation days and precipitation amount indicate that their share in the supply of precipitation days decreases in one quarter of Iran's area and only in 3% of Iran's area, their share increases. Given that Western and Central Iran's maximum precipitation days are provided by one-day precipitations, precipitation days of Eastern Iran have decreased. In addition, their share in the supply of precipitation days decreases in 1/5 of Iran's area and only in 6% of Iran's area, their share has increased. On the other hand, Given that Central Iran's maximum precipitation days are provided by one-day precipitations, their share in the supply of precipitation days has decreased; just in discrete regions and along with Zagros and Alborz unevennesses, their share increases. The results of yearly changes of share of one-day precipitations in the supply of Iran's precipitation indicate that their negative trend in all rainfall months is greater than their positive trend. Looking more generally into the share of monthly changes of one-day precipitations in the supply of Iran's precipitation, the aspects of Iran's precipitation concentration becomes evident, especially in Eastern and Central Iran.
Journal of the Earth and Space Physics (25383906)39(2)pp. 171-186
One of the effects of climate change is the possible increase in both frequency and intensity of extreme weather events. Extreme weather and climate events have a major impact on ecosystems and human society due to their severity and the fact that they often occur unexpectedly. In warmer climates and during transition seasons, cold extremes have agricultural impacts that are manifested in the damage of crops due to frost. The identification of teleconnections and the analysis of their impact on the atmospheric circulation can be very useful for the understanding of anomalous events at many regions of the planet when one assumes that local forcing may influence the atmosphere circulation at remote locations. Teleconnection patterns are simultaneous correlations in the fluctuations of large scale atmospheric parameters at points on the Earth that are wide apart. The effect of these patterns could be significant throughout the dominant modes of the atmospheric variability. Teleconnection patterns reflect large-scale changes in the atmospheric wave and jet stream patterns, and influence temperature intensity over vast areas. Thus, they are often the culprit responsible for abnormal weather patterns occurring simultaneously over seemingly vast distances. The objective on this study is to clarify whether the frequency of extreme cold temperatures occurrence in Iran during cold period have correlation with North Sea-Caspian pattern (NCP) and East Europe-Northeast Iran (ENEI) . In order to study the relation between the monthly numbers of extreme cold temperature day number of Iran during cold period with North Sea-Caspian pattern (NCP) and East Europe-Northeast Iran (ENEI), temperature data of 663 synoptic and climatic stations during 1/1/1962 to 31/12/2004 has been used. Then temperature on 15×15 kilometer pixels by using Kriging method interpolated over Iran. A matrix that was 7853×7187 has been created that for this period (7853) located on the rows and pixels on the columns (7187). There is no single definition of what constitutes an extreme event. In defining an extreme event some factors that may be taken into consideration include its magnitude, which involves the notion of the exceeding a threshold. The most general and simple, and so more wide used method for defining an extreme event of temperature is based on the definition of frequency of occurrence of the event. In this study, at first the extreme cold days during cold period recognized with Fumiaki Index. Then for each month during cold period, the number of extreme cold temperature occurrence was calculated. Monthly data during cold period of North Sea-Caspian pattern (NCP) and East Europe-Northeast Iran pattern during study period extracted from NCEP/NCAR data site of United States National Oceanic and aAtmospheric Center. The correlation between the monthly numbers of extreme cold temperature days in Iran during the cold period with North Sea-Caspian pattern (NCP) and East Europe-Northeast Iran (ENEI) was calculated. After extracting the number of extreme cold day's occurrence for each month during the cold period of the year during the study period, the correlation was calculated with North Sea-Caspian pattern (NCP) and East Europe-Northeast Iran (ENEI). Also, the magnitude of explanation coefficient has been calculated. The map of correlation and explanation coefficient are showed in figures 2 to 6. There is a significant correlation between monthly numbers of extreme cold days during cold period with NCP and ENEI at the 95% confidence level. The results showed that there is a positive correlation between the monthly numbers of extreme cold temperature days in Iran during cold period with an North Sea-Caspian pattern. The positive phase results in increase of cold extreme days in western part of Iran. The positive phase of North Sea-Caspian pattern (NCP) accompany with positive anomaly of the 500 hPa geopotential height level in the North Sea and negative anomaly in Caspian Sea. This indicates in cold air advection towards Iran especially in the western parts. In January, the correlation for 95% of Iran area is significant and positive. The highest explained coefficient is observed for the west and northern part of Iran.
Journal of Applied Sciences (discontinued) (18125654)9(18)pp. 3326-3334
In order to recognize Tehran weather types, 22 atmospheric variables are studied for Tehran synoptic station from January 1, 1978 to December 31, 2004. Cluster analysis on the standardized matrix of data and linking days on the basis of ward method shows that Tehran has four Weather Types (WT). These are- 1) Cold, frosty, rainy WT, 2) Moderate WT, 3) Warm, dry WT and 4) Cold, windy WT. Based on this study results, warm and dry WT is the most dominant and durable and cold, frosty, rainy WT is the least frequent and short-lived weather types in Tehran. Only 25.4% days of a year, moderate WT can be seen. Warm and dry period involves almost 40% days of a year Because of the dominance of Azores subtropical high pressure, Tehran's weather is much stable around this time and only warm, dry WT occurs. Because of relative increase of the warm and dry weather type in this period, Tehran's weather has become warmer. © 2009 Asian Network for Scientific lnformation.
