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Volume 1, Issue 1 (4-2014)
Nowadays air pollution in large cities such as Tehran have dramatic effects on public health, hence study of the way air pollutions varies with meteorological parameters appears to be important. One important aspect of sustainability of large cities such as Tehran, is controlling the emissions of pollutants as the meteorological (climatic) conditions are becoming more acute in terms of air pollution and temperature rise. In this paper some recent records of near surface meteorological parameters as well as some pollutants records are examine to observe how they change daily, monthly and annually and how they are correlated. Considering the variations of winds and temperature (extracted from a 2D sonic anemometer at 10 m at the Institute of Geophysics, Tehran University in the northern part of central Tehran, with one minute intervals) and hurly data of CO and PM10 concentrations for the same station for 2007, their relations were investigated. Also using upper air meteorological data (at 00.00 and 12.00 UTC) from Mehrabad Airport station, the stability of the atmosphere during this period was analysed. Here the buoyancy frequencies that are measure of stability of air column were calculated. For averaging of winds two methods based on the real wind vectors and wind unit vectors were used. By correlations between the pollutants concentrations and meteorological parameters, their relationships were considered. Based on the probability distributions of winds for 2007, it was found that most of the time wind speeds were in the range of 0.5 and 2 m/s. Hence most of the time due to this weak wind there was a condition of air pollution accumulations over the city and only local winds could move the polluted air over the area. Annual cycle of variations of mean surface winds had small amplitude that appears to be due to high mountain ranges that surround the city from north and east. The annual cycle of CO variations showed a peak in autumn and winter while PM10 amounts showed a trough in winter and spring. The higher values of CO in winter seems to be due to the surface temperature inversions and improper burnings of the fuel of vehicles as well as the domestic heating systems. This was indicated in the correlations between temperature and CO concentration. In annual cycle the correlation between CO and PM10 concentrations was about 0.4 which increased to 0.7 for spring time. This may indicate that in this season the sources of these two are similar and one of them may be used to estimate the others is the sources are not changed. There are two maxima in the daily variations of CO which coincides with minima of wind in morning and evening transition times. In this study it was found that due to calm meteorological conditions (often od local origin, called mountain breezes) over the city air pollution problem is a serious problem requiring more emission control. Also trend factors as the pollutant sources (traffic) and the depth of the atmospheric surface layer are important. It is particularly noticeable that during the midday as the depth of the mixed layer increases, the air pollution concentration is reduced substantially. At night surface drainage flow from north of the city and surface radiation cooling creates near surface inversions that can limit mixing and ventilation of the polluted air from the area leading to higher values of gaseous pollutant over the city. Also lager stability in the air over the city at higher levels in autumn and winter is due to subsidence inversions as a result of the prevailing meteorological conditions of high pressure systems over this area in these months. Such conditions seem to have increased the creation of more acute conditions for air pollution over the city. For a more resilient city in terms of air pollution, some mitigation need to be undertaken in the face of climate change effects that are deteriorating the atmosphere of the city.
Volume 2, Issue 1 (4-2015)
Air pollution has become one of the main problems of cities. Among the sources of air pollution, vehicular traffic plays an important role. Planning for efficient management and control of the air pollution caused by vehicular traffic requires accurate information on spatio-temporal dispersion of the pollutions. This research studies 3D spatio-temporal dispersion of NOx pollution caused by vehicular traffic at Valieasr-Fatemi intersection resides in Tehran, Iran. It is selected for being crowded and having the required meteorological and pollution data sensed by the Air Quality Control Corp. of Tehran Municipality.
This study uses GRAL that is a local micro-scale air dispersion model defined based on Euleran-Lagrangian dispersion models. It investigates the level of spatio-temporal autocorrelation generated by GRAL simulations at both 2D and 3D modes and discusses how it adapts with the reality.
Adopting the GRAL air pollution dispersion model, streets are defined as the linear source of pollution of NOx caused by vehicular traffic. The traffic rate is estimated based on street areas and directions, the designed average traffic velocity, traffic volume and car passage counting at the intersection. The 3D geometry of the buildings is also added to the model. All the required data that were available for winter of 2007 are gathered and introduced into the model.
The model is executed at 9 heights vary from 1.7 m to 52.5 m. These heights are defined covering a range from an average human level height to average building height and above. These levels are considered both separately in 2D mode and integrated into a 3D mode. The formation of NOx clusters is investigated analyzing their autocorrelation using Moran Index at global and local scale.
The calculated Moran-I at global scale at each 9 levels of heights, varies from 0.7 to 0.9 that depicts the validity of the GRAL model adopted to simulate the expected autocorrelation of pollution density affected by spatial issues. The Moran-I increases at higher levels as less air turbulence happens. However the result show that the turbulence increases temporarily at about 10m to 15m which are the average building heights. At local scale, the Moran-I/Anselin shows that HH clusters dominate at lower levels, around streets central areas that are farther from the buildings, and around the intersections. At higher levels, esp. higher than buildings average height, the LL clusters dominate. However the HH clusters formed around intersections, while are shrank, are still visible at high levels. The turbulence caused by building fronts and their down wash effect is also shown in the result as no definite cluster is formed near the buildings front and back.
The autocorrelation analysis is also carried for an integrated 3D model consists of all the 9 levels of heights. Considering the weight matrix for a 20m 2D neighborhood and 1m/s dispersion of the pollution vertically, the global calculated Moran-I equals 0.229 which shows existence of a spatio-temporal autocorrelation of the results generated by GRAL. At local scale the results show that the HH clusters have higher temporal dispersion rate than LL clusters.
Volume 2, Issue 1 (4-2015)
Urban planning has to perform seismic pathology of urban streets in seismic cities. Streets and roads are the most important spaces and urban elements in the cities which should be considered not only in space occupation and connecting spaces and urban activities but also in seismic vulnerability and on this basis it is planned to reduce environmental hazards and on top of earthquake-related. Many physical and functional characteristics of urban spaces and the distribution and concentration of the urban population take shape to comply with the location, capacity and function of the city streets network. Therefore, one of the most essential and the most important topics in the study of seismic cities is understanding of the relation between seismicity and urban streets through seismic vulnerability studies. This paper aims to assess factors and patterns of seismic vulnerability of urban networks with a prevention planning view in the 3rd district of Tabriz City.
This research has descriptive-analytic method and the statistical population is street network of 3rd district of Tabriz city. Data and layers of information have been prepared by documentary method and have been processed using the Delphi method and the method of ranking and rating IHWP in GIS. The main factors and indicators influencing streets vulnerability have been selected based on the eight indicators. These indicators include distance and proximity to faults, quality of buildings, the degree of closeness (width of the wall), building density, population density, the traffic service or traffic volume toward roads capacity, access to health centers and services and the land use system. The final map of seismic vulnerability has been produced by combining eight layers of information related to above mentioned indicatorsand based on it the seismic vulnerability levels and factors of the street network has been analyzed.
The final results of the seismic vulnerability of streets have been categorized in the 5 classes of vulnerability including very low, low, medium, high and very high. From total area 18.4% is estimated very low, 29.37% low, 31.77% medium, 14.21% high and 6.22% very high. Thus, taking into account the streets with medium, high and very high degree as vulnerable axes, it is concluded that 52.2% or more than half of the streets are seismic vulnerable and other half are relatively stable.
Within the vulnerable and unstable network, more than 20% of the streets are in high and very high vulnerable classes. Street network with high and very high vulnerability are mainly arterial streets with commercial and service land uses in the scale of trans-regional or secondary roads leading to artery of trans-regional which have high population density. These streets compose a high degree of closeness, increase in traffic service level, population density and land use system with the concentration of commercial, recreational and trans-regional land uses are the main causes of vulnerability. But, in the narrow streets (8 to 10 meters), the degree of closeness of arterial streets, traffic parameters and user system have increased the seismic vulnerability index. Spatial pattern of streets vulnerability has an increasing trend from East to West and from North to south. The results show Spatial intensity of vulnerable streets is located at the center of the district and on Vali Asr, Shariati, Aref and Razi Streets. Thus, the efficient and sustainable streets are located in the East of the under studied district.
The results also show that high vulnerable streets has less distance to fault and more distance from medical centers. In addition, they have high traffic and lower quality buildings and high risk land uses (electric and gas infrastructure) are located there. Since the wide streets are more often subject to less obstruction, this characteristic in seismic time cause to transfer the traffic of narrow passage to the main streets. Grid pattern of streets and frequency of intersections by slowing down the speed of the vehicle increase the volume of traffic and lead to an increase in seismic vulnerability.
Volume 3, Issue 3 (10-2016)
Understanding the changes in extreme precipitation over a region is very important for adaptation strategies to climate change. One of the most important topics in this field is detection and attribution of climate change. Over the past two decades, there has been an increasing interest for scientists, engineers and policy makers to study about the effects of external forcing to the climatic variables and associated natural resources and human systems and whether such effects have surpassed the influence of the climate’s natural internal variability. The definitions used in the 5th assessment report were taken from the IPCC guidance paper on detection and attribution, and were stated as follows: “Detection of change is defined as the process of demonstrating that climate or a system affected by climate has changed in some defined statistical sense without providing a reason for that change. An identified change is detected in observations if its likelihood of occurrence by chance due to internal variability alone is determined to be small. Attribution is defined as the process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence”. Detection and attribution of human-induced climate change provide a formal tool to decipher the complex causes of climate change. In this study the optimal fingerprinting detection and attribution have been attempted to investigate the changes in the annual maximum of daily precipitation and the annual maximum of 5-day consecutive precipitation amount over the southwest of Iran.
This is achieved through the use of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources Project(APHRODITE) dataset as observation, a climate model runs and the standard optimal fingerprint method. To evaluate the response of climate to external forcing and to estimate the internal variability of the climate system from pre-industrial runs, the Norwegian Climate Center’s Earth System Model- NorESM1-M was used. We used up scaling to remap both grid data of observations and simulations to a large pixel. This remapped pixel coverages the area of the southwest of Iran. The optimal finger printing method needs standardized values like probability index(PI) or anomalies as input data, since the magnitude of precipitation varied highly from one region to another. The General Extreme Value distribution (GEV) is used to convert time series of the Rx1day and Rx5day into corresponding time series of PI. Then we calculated non-overlapping 5-year mean PI time series over the area study. In this research, we applied optimal fingerprinting method by using empirical orthogonal functions. The implementation of optimal fingerprinting often involves projecting onto k leading EOFs in order to decrease the dimension of the data and improve the estimate of internal climate variability. A residual consistency test used to check if the estimated residuals in regression algorithm are consistent with the assumed internal climate variability. Indeed, as the covariance matrix of internal variability is assumed to be known in these statistical models, it is important to check whether the inferred residuals are consistent with it; such that they are a typical realization of such variability. If this test is passed, the overall statistical model can be considered suitable.
Results obtained for response to anthropogenic and natural forcing combined forcing (ALL) for Rx1day and Rx5day show that scaling factors are significantly greater than zero and consistent with unit. These results indicate that the simulated ALL response is consistent with Rx1day observed changes. Also, it is found that the changes in observed extreme precipitation during 1951-2005 lie outside the range that is expected from natural internal variability of climate alone and greenhouse gasses alone, based on NorESM1-M climate model. Such changes are consistent with those expected from anthropogenic forcing alone. The detection results are sensitive to EOFs. We estimate the anthropogenic and natural forcing combined attributable change in PI over 1951–2005 to be 1.64% [0.18%, 3.1%, >90% confidence interval] for RX1day and 2.5% [1%,4%] for RX5day.
Volume 3, Issue 4 (1-2017)
Classifying daily climate circulation patterns has always been considered by climatologists. Investigating climate changes such as rainfall and the temperature in a same single time and place suggests that these changes are strongly influenced by atmospheric circulation patterns.
Regarding so, climate changes, known as variables here, such as rainfall, temperature, and other related phenomena, which are exemplified as flood, drought, glacial, and etc. are associated with special types of climate circulation patterns. The continuity and alternation of the systems are classified or identified climatically, therefore weather classification system is one of the main objectives of the synoptic climatology (Huth, 1996). Since every weather type creates its own special environmental condition, lack of identification in weather type frequencies leads to a difficult environmental explanation and alternation (Alijani, 1380: 64).
Identifying atmospheric circulation patterns different things that can be expressed inductively such as frequency, intensity, and spatial distribution of climate changes in rainfall and its physical causers (VicenteSerrano and LopezMoreno, 2006).
Heavy rainfall in many watersheds, particularly in the basin and sub-basin which involve less time exposure, causes floods and it also damages human, natural resources, infrastructure utilities and equipment. Before the occurrence of this kind of rainfall, it requires a deep understanding of the synoptic systems of their creator. This understanding is only possible through the classification and identification of rainfall patterns which used to cause floods in the studied basins.
The present study also aims at identifying and classifying the synoptic patterns of rainfall during the statistical stage of the study in the basin which caused flood in Taleqhan basin.
Taleqhan basin with area of (65/1242) per square kilometers is located in "36֯, 5', 20" to "36֯, 21', 30" north latitude and "50֯, 36', 26" to eastern longitude "51֯, 10', 18".
The study area is 120 kilometers away from North West of Tehran and located in a relatively high mountainous area in Alborz Mountain. This area is ranging from 1700 meters to 4400 meters above sea level. Average rainfall in this basin ara is 515/16 mm and its annual temperature fits 10.5 centigrade. About 79 percent of rainfalls occurs from the cold weather period in November to March. It is also know as semi-humid cold weather based on the De Martonne classification.
Circulation algorithm (CA) and pattern clustering algorithm (PCA) were determined based on the daily methods in synoptic scale by applying information from stations in Taleqhan basin (Gateh deh, Dehdar, Dizan, Snkranchal, armouth, Ange, Joostan, Zidasht). In order to classify the weather type, daily average rate of 500 HPa and the sea level pressure (SLP) were extracted and reconstructed over the period (1980-2011) at the 2.5 degree of NCEP. Selected range includes 608 points from latitude of 10 to the 60 of northern degree, and latitude of 10 to 80 of eastern degree.
Principal components method mixes the interrelated points and reduces the matrix size, so 13 main components are remained that they includes 93 percent of the total variance. This study employs S array and Varimax rotation to identify different types of weather. It also makes use of K-Means clustering method to classify daily weather types. And finally, a matrix was formed in 118×608 dimension for 118 common days of rainfall among stations. All days were divided into four groups. They offer the most common climate circulation patterns in the proposed area. At the end, and finally integrated maps of sea level pressure and 500 HPa were drawn for each weather type.
According to the results from factor analysis, 13 main elements were selected that they included 93% of the total variance of the data. According to the above mentioned method, all days (118 days) during the statistical period (1980-2011) were divided into 4 groups which provide the most climate circulation patterns in the study area. Then, integrated maps of sea level pressure and 500 HPa range were drawn for each of the types. Clusters were numbered according to the K-Means arrangement, and they were named based on the pressure patterns and the way circulation lines were ordered.
The classification shows two different resources for rainfall in this basin.
A: Those rain systems that are entered to the country from the West and South affect this basin. These systems humidity are caused by the Red Sea, the Mediterranean sea, the Black Sea, and the Atlantic Ocean. (B) Some parts of the Caspian coast rainfalls and the northern part of the Alborz mountain that has received their humidity from the Caspian Sea and it has infiltrated northern high-land, causes the rainfalls. It enters the basin from the wide valley of Sefid Rood. According to the rainfall measuring stations data, the least rainfall area is in western, which includes low-land areas. And the most rainfall area is its northern east. Rainfall in this area, in terms of rainfall time distribution in a year, is the Mediterranean. It does not involve a complete dry climate in summer and it takes 3 to 4 percent of the total rainfall. Rainfall in the basin, respectively, is distributed in winter, spring, fall, and summer.
Volume 4, Issue 2 (7-2017)
The aim of this study, is to identify, tracking and analysis of the winter season (December, January and February or DJF) rain producing cyclones using special database and algorithm during three recently decades (1979-2009).
In this study, in order to specify, tracking and statistical analysis of the DJF rain producing cyclones, relative Vorticity of 700 hPa were received from ECMWF data center with
spatial resolution and temporal resolutions of 6-hourly for a 30 years period (1979-2009). The study domain includes Mediterranean and Middle East, from 
E to 
E and 
N to 
N.Cyclone identification will follow the approach presented in Blender et al. (1997) and Flaounas et al. (2014), including two important points and conditions: 1- A cyclone is considered to be a relative Vorticity extrema, thus the aim will be to look for the maximum value of relative Vorticity at the 700 hPa level in a box of
grid points. 2. For the intensity of the cyclone, the threshold of relative Vorticity, is considered equal or greater than 
. Then by 6-hour tracking the maximum amount points of Vorticity and connecting them to each other, identification and routing of cyclone is implemented. The track 
can be written as 
, where 
describes the cyclone position in sequential time steps t = 0, … , T, which are given at 00, 06, 12 and 18 GMT. The initial position is considered the first detected maximum of relative Vorticity. During the cyclone detection and tracking method, different threshold values are commonly applied to eliminate, for instance, the weakest centers and short living systems. For this reason, the threshold of equal or greater than 8 time steps (3 days and more) is considered based on Alijani (1366) to eliminate short living cyclones.In this study, climatology of cyclones such as genesis and lysis centers, tracks and frequencies in the Mediterranean Basin and Middle East were analyzed. The results showed that, center and eastern part of the Mediterranean region include Aegean Sea, Cyprus, and northern borders of Mediterranean Sea, Adriatic Sea and also Red Sea, Sudan and Iraq, are most important cyclogenesis centers in winter season.
These cyclones which form in these cyclogenesis centers, move to the east with two eastward and northeastward distinguished directions. In northwest of Iran, the cyclones by passing over West and East Azerbaijan and Ardebil provinces in eastward and northeastward directions, move into western and southern shores of Caspian Sea. In southwest of the country, the cyclones are entered into Iran over Khozestan, Chaharmahal and Kohkilouyeh provinces. Part the cyclones are moved into center and northeast of the country with northeastward direction and other part by crossing over southern shores of the country move to the southeast of the country. In mid-west of the country, the cyclones are arrived into Iran in three different tracks. The most important path is Kordestan's path which the cyclones in the origin of Mediterranean are entered eastward into Iran by crossing over Zanjan and Hamadan provinces, under the Alborz ranges are moved into east and northeast of the country. Two other paths are observed in Ilam and Kermanshah Provinces which in these tracks also the cyclones are approximately moved eastward into center and northeast of the country. The results also showed that eastern part of the Mediterranean region specially Cyprus, Aegean sea, Adriatic sea, Red sea and Sudan and also Iraq are most important wintertime cyclogenesis centers of Iran. The main entrance paths of the cyclones includes northwest, mid- west and southwest. The averages cyclones lifetime are 4.5 days, movement speed is about 20 km/h and also travelling length is about 1700 km. Of the other notable results we can refer to decreasing of the rain producing cyclones during 3 last decades.
Volume 5, Issue 1 (6-2018)
Dust storms are natural hazards that mostly occur in arid and semi-arid regions and there are many harmful consequences. According to the topographic-climatic conditions in Iran and the significant increase in the number and severity of dust storms occurrence in recent decades, especially in the West and Southwest regions where the dust storms are the most important environmental crisis. Studying this phenomenon is necessary for better management its harmful effects.
Since most of the research are implemented as different case studies, and there is no comprehensive study that review a wide range of existing researches with overall results in the southwestern parts of Iran, in this study a comprehensive overview of available literature reviews are addressed including dust spatio-temporal variations, modeling, detection, and health issues.
This research is based on a library research and search of valid national and international scientific articles about the dust crisis and no data-processing. We attempted to analyze temporal and spatial variations in the south and southwest of the country using the available studies and the challenges of this phenomenon in the past and present to provide a new perspective to apply a comprehensive land management and managing environmental hazards in Iran with all the problems.
A review of the history of dust storm studies from information sources showed that most researchers (61.40%) used a synoptic method to study dust storms, and the most important indicators that were considered by the researchers in physical properties were frequency and density, 34.21% and 34.21% of the studies respectively.
Dust detection methods show that the use of thermal or reflective bands cannot detect dust phenomena with high precision, therefore, a model which applies both bands simultaneously should be developed. In other words, applying a combination of reflective and thermal
spectra of Military Origin Destination Information System (MODIS) could offer better
results in detection of dust storms in the study area. Studies indicate that most of the storms
originate outside of Iran. Moreover, exposure to airborne contaminants, especially when the
dust storms occur in the Middle East, can lead to an increase in the related disease outbreak
in the study area. For instance, there was a 70% increase in referring to medical centers for
lung related problems when a dust phenomenon occurred.
The Results showed that in cold seasons where low height and western waves is formed on the European and Mediterranean Sea, due to the heaviness, cold air in these days, can penetrate low latitudes and their trough is located over the Middle East area. Under warming condition, the front of rough is formed as ridge, then engendered turbulence and wind. In the warm seasons, thermal low pressure is rapt to ward in the high latitude, and severe dryness
of the area is also due to the fact that the dusty phenomenon is intensified in the area. Dust
storm occurrence in the summer due to bareness of the land, transparency of the atmosphere,
dryness of the air and the vast plains, which can reduce the formation of local instability in
the case of a sharp rise in air temperature. The dispersal of deserts and sand sea is mainly in
the northwest of Khuzestan province, especially in Fakkeh and Moussan which are located in the western borders of Iran with Iraq, which cover most of the Azadegan plain and west of the Karkheh and Mollasani and Maroon Rivers, and ultimately end in the Omidiyeh and Aghajari regions. Results show that the border between Syria and northwest Iraq, west and southwest of Iraq to east and northeast of Saudi Arabia are the main sources of dust in the studied region
. Synoptic conditions considering simultaneously with the occurrence of dust
storms showed the significant role of cyclonic systems in the occurrence and transfer of this
phenomenon. With the phenomenon occurrence during the warm period, the significant
strengthening in low pressure of Iraq along with the trough formation in Zagros causes the
formation and transfer of dust towards Southwest Iran. Simulation studies of dust particles
movement paths have shown that most of the paths are from the northern and central parts
of Iraq and Syria and the source of dust storms are deserts and dry regions of the northern
and central parts of Iraq and Syria. In addition, the study of the transmission paths of particles
in dust storms indicates the presence of a lower level jet, which causes horizontal
displacement of dust particles in a shallow layer and prevents its vertical propagation in the
higher layers of the atmosphere. In general, although the dust phenomenon is transnational
and uncontrollable, it can introduce limitations in terms of circulation patterns and statistical
properties at different time intervals to the different planners via its time and scope which
will necessitate appropriate programs for combating and adaptation.
Keywords: Dust, Air pollution, Spatio-temporal pattern, Southwest, Iran.
Volume 7, Issue 2 (8-2020)
Abstract
In this essay, we investigated the effects of climate change on the rivers of selected basins of Guilan province, one of the northern provinces of Iran for the period 2020 to 2050 under three climate scenarios: RCP2.6, RCP4.5, RCP8.5. For this purpose, rainfall and temperature data from 45 climate data stations and 20 hydrometric stations from 1983 to 2013 were used. The average precipitation and temperature at basin level were calculated by drawing both Isohyet and Isothermal lines by usage Kriging method. Mann-Kendall and Sen’s slope estimator tests were used to determine the significance of the data trends and their slope, respectively. The results showed that temperature has increased in all catchments during the study period and this trend was significant in most of them but no significant trend was observed for precipitation. Discharge has also decreased in most basins and this trend was significant in Shafarood, Navrood and Chafrood basins. However, for future periods, precipitation is not significant in any of the climate scenarios, but the temperature is increasing in all scenarios except for the RCP2.6 scenario. Rivers discharge in the RCP2.6 scenario is not significant in any of the basins, but in the RCP4.5 scenario the Shafarood and Ghasht-Roodkan catchments have a significant reduction in the 95% confidence level. In the RCP8.5 scenario, the Chafrood and Shafarood basins have a 99% confidence reduction trend.
Population and technology growth, increased water consumption and climate change have led many researchers to study and model water resources in the present and future periods. Especially in areas like Iran that are facing a lot of water stresses. The purpose of the present study, which was carried out in the Guilan province, is to provide information on the present and future status of surface water resources, and to prepare them for facing the problems of potential water resources exploitation.
In this study 45 synoptic, evaporative and rain gauge stations and 20 hydrometric stations data with sufficient statistics were used. The period of study is also between 1983 and 2013. In this regard, after calculating the average precipitation and temperature values of each basin using Kriging model, first, the annual average of precipitation and temperature values of each basin were calculated. Then, multivariate regression was used to obtain the regression equations between precipitation, temperature and discharge data, then by using SDSM model and climate scenarios (RCP2.6, RCP4.5, RCP8.5) future temperature and precipitation data were generated. By placing these generated data in the Created regression equations, the discharge of the rivers was calculated for the period 2020 to 2050. The trend of time series and their slope were analyzed respectively by Mann-Kendall and Sense tests.
The study of the annual average precipitation trend of the selected catchments during the study period showed that all the basins had no significant trend at any of the confidence levels (95% and 99%). However, for the temperature there is an increasing trend. In Chafrood, Zilaki, Chalvand, Lavandevil, Tutkabon, Chubar, Lamir, Hawigh, Dissam, Shirabad, Ponel, Samoosh, and Polrood basins there is significant trend at 95% confidence level. For the Hawigh River basin there is significant trend at 99% confidence level. Also in most of the basins there is a downward trend of rivers discharge. In addition, in the three basins of Chafrood, Navrood and Shafarood, there is a significant decreasing trend at 95% confidence level, which is also significant at 99% confidence level for Navrood and Shafarood rivers.
Analysis of future data showed that precipitation is not significant in any of the climate scenarios, but the temperature is increasing in all scenarios except for the RCP2.6 scenario in RCP2.6 scenario. For rivers discharge there was no significant trend in any of the basins, but in RCP4.5 scenario there is a significant decrease in 95% confidence level in Shafarood and Ghasht-Roodkan. Also in the RCP8.5 scenario, a significant decreasing trend of flow discharge at 99% confidence level is observed for Chafrood and Shafarood basins. Finally, the catchments were grouped according to the level of risk involved with decreasing discharge. The results of grouping showed that most of the basins in the three scenarios were in the medium risk group but Shafarood, Chafrood and Ghasht-roodkhan watersheds have higher risk than the other watersheds, respectively.
Investigation of river discharge trends for the period 2020 to 2050 in different scenarios showed that the basins of Ghasht-roodkhan, Chafrood and Shafarood are more sensitive to climate change than other basins. Overall, escalating temperature trends in future and precipitation irregularities can create very difficult conditions in future to use these resources. Especially, this study's concordance with other studies in Iran and the study area confirms that such crises are more likely to occur..
Keywords: Climate Change Scenarios, Rivers Discharge, Man-Kendall, Sen’s Slope estimator, Guilan Province
Volume 8, Issue 4 (1-2021)
Tehran metropolitan with its large population, daily migrant workforce and many students, needs to planning and designing watch/warning system to reduce the climatic problems for human health.for this purpose, we need to study the climate accurately and Since the factors affecting the climate of warm and cold periods in Iran are different, in this study , the meteorological variables of Tehran warm period (May to September 2002) turned into 4 components in Temporal Synoptic Index (TSI) using PCA Method and using P-Array and Varimax rotation.By the scores of components for each day, the clustering method (in ward method) were used and, the warm days of the year was divided into two cluster named favorable and oppressive airmasses. The average maximum air temperature that is more effective in mortality, was 36.13 ° C. Days with temperatures above 34 ° C, less pressure, mild winds , dryness and more sunshine resulted in more adverse weather conditions, which resulted in a 34% increasing in mortality compare with favorable weather. The total number of deaths from cardiovascular disease during the study period was 154046 that about 67%of deaths have been simultaneous with oppressive airmass.The epidemiological study of mortality also confirms the results of previous research in this area and shows that the incidence of mortality is higher in older people as well as in men. It is clear that not all mortality can be attributed to the effects of climate, but results show that change in climatic conditions will affect on mortality and also for study the effect of climatic hazards on human health, it is better that we study the effect of all variables together on humans.
Volume 8, Issue 4 (1-2021)
Conclusion
The results showed that the length of the precipitation period in the study area is 8 months (out of 213 systems, 60 systems were recorded in January and 50 systems were recorded in December). June, July, August and December did not have a comprehensive rainfall system. The difference in height between the Mediterranean Cyclone and the Arabian Anticyclone, i.e. the MAI index, was identified in 5 categories. The results showed that the higher the value of MAI index, the less rainfall systems and the higher the rainfall intensity. Most rainfall systems occur when the MAI index reaches 100 to 150 geopotential meters. In addition, the concentration of precipitation occurred in February when the MAI index reached 200 geopotential meters and above. In the continuation of the research, the difference between the Sudan Cyclone and Arabian Anticyclone, i.e. the SAI index, was also identified in 5 categories. The results showed that most of the systems occurred in the third category with a value of SAI index between 100 and 150 geopotential meters. Moreover, the results showed that the higher the value of the SAI index (, the lower the number of rainfall systems and the higher the average of rainfall systems.
Volume 10, Issue 3 (9-2023)
Volume 12, Issue 2 (9-2025)
Objective: The main goal of this research is to identify and analyze the seasonality of the most widespread Torrential rains in Iran during the years 1940 to 2023.
Methods: To achieve this goal, precipitation data was obtained from the ECMWF database with a spatial resolution of 0.25 by 0.25 degrees of arc for the Iranian region during the study period. The next step was to calculate the threshold of torrential precipitation for each cell seasonally using the 95th percentile, and days with torrential precipitation were identified. By applying the condition of the highest spatial spread of the 95th percentile, the days with the most widespread precipitation above the threshold were identified for each season. Finally, the prevailing atmospheric conditions were examined.
Results: Analysis shows that the highest precipitation of 146.85 mm occurs in winter and the lowest of 85 mm occurs in summer. The highest spatial coverage of total precipitation occurs in spring (41.9), winter (40.69), autumn (32.55) and summer (16.84), respectively.The analysis of sea level pressure indicates that during widespread precipitation in the summer, a low-pressure belt extended from the westernmost to the easternmost regions of the upper atmosphere map, encompassing Iran. In contrast, during other seasons, a high-pressure belt was present in the same area. At the 500 hectopascal level in summer, a closed high-pressure dynamic cell was observed over Iran, while at the 850 hectopascal level, two low-pressure centers over Saudi Arabia and Pakistan intensified instability over Iran. Consequently, it is evident that at lower levels, the conditions for atmospheric precipitation were stable, and even the omega level at 500 hectopascals over Iran on that day indicated a weak upward movement of air. However, in other seasons, a trough consistently positioned over western Iran, with active band patterns in spring and winter, facilitated the slowing and diversion of currents toward moisture sources, thereby enabling the transfer of more moisture than normal conditions to Iran. The precipitation study revealed that, except for the summer season, wind dominated over Iran. The presence of wind intensified instability at lower levels. A study of the Atmospheric River reveals that during widespread rainfall across all seasons, the Atmospheric River, which originates from the Red Sea and the Persian Gulf, has consistently been present. However, in the fall and winter seasons, a branch from the Mediterranean Sea also contributes, resulting in increased rainfall.
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