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Zahra Hejazizadeh, Meysam Toulabi Nejad, Zahra Zarei Chaghabalaki, Behzad Amraeei,
Volume 5, Issue 4 (3-2019)
Volume 5, Issue 4 (3-2019)
Abstract
This research was conducted to identify the dust storms in the Midwest of Iran from June 16 to 19, 2015. To investigate the synoptic conditions of the causes of this phenomenon, the ECMWF has an array of 0.125 degrees, including geopotential, omega, and sea level pressure, orbital and meridian components of the wind, specific humidity Soil moisture was applied to a depth of 10 cm. Similarly, for the purpose of routing the source of dust particles, the model of the Minimum Meteorological Parameters (HYSPLIT) Marv was used. The results of this study showed that in Lorestan province, non-ditches created by low-pressure thermal springs and high-altitude movements in Saudi Arabia caused the convergence and sucking of flows to the west of the country, as well as the establishment of a low-pressure cut at the middle levels of the atmosphere in the east of the Caspian. In the event of this risk, it has been effective. According to the average soil moisture from the surface of the earth to a depth of 10 cm in days with dust hazards, the moisture content of dust particles in the dust was less than 15%, due to the flow of streams from these fields without sufficient moisture, fine particles the soil is easily directed towards the study. A survey of Hysplit tracking maps shows that two general paths for the transfer of dust to the studied region can be detected. 1-Northwest - Southwest At an altitude of 1500 meters: passing through the dust nuclei formed in the northwest of Iraq and east of Syria, carry out the transfer of dust to the west-west of Iran. As these currents have been able to transfer dust to the southwest of Iran, this path can be considered the main route of dust dispersion to the region. 2- The western-eastern route at an altitude of 500 to 1000 meters: is the source of particles of this route inside the country (around Hurralazim) that entered the West of Iran and greatly reduced the horizontal visibility, which is the main source of dust on June 18 and 19. The investigation of the path of dust particles in the walnut shows that these particles were initially transferred to lower levels by low-pressure systems in the Midwest of Iran and then pulled in three directions on the ground.
Sir Vahid Safarian Zengir, Sir Behroz Sobhani,
Volume 5, Issue 4 (3-2019)
Volume 5, Issue 4 (3-2019)
Abstract
Introduction
Changes, although low in temperature, change the occurrence of extreme phenomena such as droughts, heavy rainfall and storms (Varshavian et al., 2011: 169). Reducing the daily temperature variation has led to a reduction in the frequency of occurrence of temperature minima, especially in winter (Schiffinger et al., 2003, p. 51-41).
Material and method
The purpose of the present study was to investigate and predict the risk of monthly rainfed temperatures on horticultural and agricultural products in northern Iran. For this purpose, first, the data of the temperature of the whole station were obtained at a time interval of 30 years. Then, using Anfis's adaptive neural network model, data were collected for prediction and prediction for the next 6 years. Then, to measure the land suitability of the northern strip Iran was used for cultivating according to the predicted data using two models of Vikor and Topsis.
Conclusion:
In recent years, damage to agricultural and horticultural products has been increased due to temperature fluctuations. Accordingly, in this research, the prediction of the risk of monthly rainfed temperatures on horticultural and agricultural products in northern Iran has been investigated. Based on the predicted data, the minimum temperature of the Gorgan station was the lowest educational error with a value of 0.10 and at the maximum temperature, the lowest error was 0.015. Finally, in Golestan province, the maximum temperature And at least both are weak in the incremental state. Minimum and maximum temperature of Bandar Anzali station was the lowest educational error with the value (0.013, 0.10). In Gilan province, the maximum temperature peaks and at least both are in incremental conditions and the maximum temperature has a higher intensity. Be The minimum temperature of the Babolsar station was the lowest educational error with the value of 0.019 and at Ramsar maximum temperature, the lowest error was 0.016, and Mazandaran province exhibited maximum and minimum temperatures at both incremental and minimum levels Temperature showed greater intensity.
Results:
According to the findings of the study, with respect to the friction frain modeling, the maximum temperature showed the lowest defect compared to the minimum temperature. In Golestan province, the maximum temperature peaks and at least both are in weak increment, but in Gilan province, the maximum temperature peaks and at least both the maximum and maximum temperatures are higher. Mazandaran province showed maximum temperature and minimum temperature in both incremental and minimum temperature conditions.
Yousef Ghavidel, Manouchehr Farajzadeh, Bashir Ghahramani,
Volume 6, Issue 2 (9-2019)
Volume 6, Issue 2 (9-2019)
Abstract
The application of Extreme value analysis method in heat wave hazard climatology; case study in Mid-Southern Iran
Abstract
Greenhouse warming poses the main cause of atmospheric hazards’ exacerbation and emergence in recent years. Earth planet has been witnessing frequent and severe natural hazards from the distant past; however, global warming has strongly influenced the occurrence of some atmospheric hazards, especially the ones induced by temperature and has increased the frequency and severity of those risks. Such extreme risks arising from temperature element and being affected by global warming could be referred to hot days and their frequency more than one day which undergo heat waves. Of the studies conducted worldwide in conjunction with the phenomenon of heat waves, the following can be pointed out; Schär (2015) has focused his studies on the Persian Gulf and the worst heat waves expected in this area. The recent work revealed an upper limit of stability which enables the adaptability of human body with heat stress and humidity. If people are exposed to a combination of temperature and humidity over long periods higher than this level, they will lead to hyperthermia and death, because heat dissipation from the body is physically impossible. Paul and al-Tahrir (2015) using a high-resolution regional climate model demonstrated that such a situation can occur much earlier. In Iran, in relation to heat waves, Ghavidel (2013) analyzed climatic risk of Khuzestan province in 2000 regarding super heat waves using the clustering approach. The obtained results unveiled the establishment of a low pressure at ground level and high pressure dominance at mid-altitudes up to 500 hp as well as the increase in atmosphere thickness having led to the ground overheating. Added to that, the source of heat entering into Khuzestan is advective and hot and dry air transport through Arabian Peninsula, Iraq and Africa. Ghavidel and Rezai (2014) addressed in a study to determine the temperature-related threshold and analyze the synoptic patterns of super heat temperatures in southeast region of Iran; the results of study approved that the only pattern effective on the occurrence of super heat days in Iran’s southeast is the establishment of the Grange’s heat low-pressure at ground level and subtropical Azores high elevation dominance at 500 hPa level. In this study, absolute statistical indicators, also recognized as above-threshold values approach, were used in order to identify, classify and heat waves synoptic analysis in the warm period of the year in the southern half of Iran. To use above-mentioned indicators, firstly daily maximum temperature statistics of studied stations with the highest periods were averaged every day once in June to September and once for the months of July and September. Using statistical indicators of long-term mean and standard deviation or base period, indicators would be defined for the classification of heat waves and days with peak extreme temperatures. In such classifications, usually long-term average or base period is multiplied by 1 to 3 to 4 times standard deviation and each time is account for the factor of each class.
To select the days for synoptic analysis, averaging was performed of all classified waves into four heat wave categories of low, intermediate, strong and super heat; accordingly based on the maximum blocks in each class of heat waves, days that had the highest temperature values were selected as the class representative for mapping and synoptic analysis.
This study dealt with investigating heat waves synoptic during the year’s warm period in the southern half of Iran. Studies showed that a variety of synoptic systems in the year’s warm period affect the study area. As well as, synoptic analyses concluded that in the southern half of Iran over the year’s warm period when occurring heat waves, low-pressure status dominates the ground level (caused by Gang’s low-pressure and local radiant mode); thus high-pressure status with closed curves is prevailing in atmosphere’s upper levels that gives rise to the divergence, air fall and Earth's surface heating. Studying the status of the atmosphere thickness in the days with the heat wave in the study area indicates its high altitude and thickness that this itself implies the existence of very hot air and susceptibility of the conditions for the occurrence of heat waves. In addition, wind maps at atmosphere’s different levels well illustrate the wind of very warm and hot air masses from the surrounding areas to the southern part of Iran; therefore it can be noted that aforementioned hot air masses mainly wind from places like different regions of the Arabian Peninsula, Iraq, North Africa and the low latitudes to the study area.
Keywords: Synoptic analysis, heat waves, maximum blocks, southern half of Iran.
Dr. Sahar Nedae Tousi, Ms Roza Hosseini Nejad,
Volume 6, Issue 2 (9-2019)
Volume 6, Issue 2 (9-2019)
Abstract
Resilience, as a concept to confront abnormalities, surprises and unexpected changes in recent years has been raised as the ability of places, societies, and systems to respond to the dangers of tensions and pressures; so that the system can quickly return to pre-stressed situation, threats It accepts the future and confronts them. Central region of Iran according to the zoning studies of the national physical plan of Iran, including three provinces of Isfahan, Chaharmahal and Bakhtiari and Yazd, in a desert climate with many crises in the permafrost environment that has disturbed the state of resilience of the region, and as a result the scheme and target application regional resilience on policy and planning to reduce vulnerability and to cope with various trans-regional crises. Despite the fact that the concept of resilience at the level beyond the city has become apparent, there is still no clear framework for measuring this situation at the regional level. Based on this research, it is believed by the trans-regional and multi-dimensional nature of the resilience that by modifying and applying the concept of resilience to the integrated and multi-dimensional at the regional level, an appropriate framework for status measurement regional resilience in the form of a composite index and thereby risk reduction planning and promoting the resilience of the presentation To give. In this regard, the major purpose of the research is to develop an optimal framework for assessing, measuring and ranking the resilience situation in the central region of Iran. The results show that Chaharmahal and Bakhtiari province have the highest resilience and then there are two provinces of Isfahan and Yazd, respectively. In the meantime, Yazd province has the lowest resilience among the provinces of the central region; therefore, it is necessary to focus on planning and allocating resources to promote and improve priority sectors. Responding to resilience agendas requires the adoption of transregional planning and decision-making approaches such as environmental regionalism.
Mr Masoud Jalali, Mr , Mr Abdullah Faraji, Mr Ali Mohammad Mansourzadeh, Mr Sayyed Mahmoud Hosseini Seddigh,
Volume 6, Issue 4 (2-2020)
Volume 6, Issue 4 (2-2020)
Abstract
Analysis and zoning of thermal physiological stresses in Iran
Abstract
Human health is influenced by weather variables in all circumstances, including atmospheric pressure, humidity and temperature around them. Based on climate hazard and climate changes, different parts of human life and economic and social strategies such as health, hydrological pollutants And agriculture had a profound effect, including the discussion of the effects of thermal stress on human health over the last few decades, and has become a major issue in the world's scientific circles. Heat and cold stresses, the exposure of humans to extreme heat and cold, are part of the extreme events, often encountered by people during daily activities or in the workplace, and affecting human physical activities. It is important that, if the body is not cooled through transpiration or cooling mechanism, severe deaths are inflicted on human health; therefore, the person has to reduce his activity in order to reduce the adverse effects of heat stress. Hence, many researchers consider the thermal stress component more important than other components in assessing human health.
In this study, using the physiological equivalent thermometer of PET thermal stress assessment and zoning of human thermal physiological stresses in Iran, with the length of the common statistical period from 1959 to 2011, and for the arsenal of thermal physiological stresses of Iran Forty stations have been used as representatives of Iranian cities. To calculate the physiological equivalent thermal temperature, all the effective meteorological elements in the human energy bill are measured at an appropriate height of climate biology, such as 1/5 meters above the Earth's surface. Data on climatic elements are provided by the Meteorological Organization of Iran. In the absence of data for some courses, linear regression method was used to reconstruct these missing data. After calculating the indices, the frequencies were also monitored and finally, using the GIS technique, the Kriging method of the study area was based on the frequency of occurrence of the indicators. Therefore, in order to achieve the results and objectives of the present study, software such as SPSS for data normalization as well as missing data was analyzed and analyzed using Ray Man's model based on meteorological elements to calculate the equivalent thermal physiological temperature of humans. Also, using the GIS software and Ordinary Kriging method, the best interpolation method was used to zon the human cysiological stresses.
Today, in the planning of human health and comfort, the study of the physiological thermal stress plays an important role. In this regard, weather conditions can be used in the long-term planning of climate and in the short term planning of atmospheric conditions. In the present study, using the thermophysical Thermal Equivalent Thermal Index (PET), the climate climatic Atlas of Iran was prepared on a monthly basis. Calculated values for 40 stations in the country with a total statistical period of 52 years (1959-2011) were prepared. The results of this study showed that the spatial distribution of the physiological equivalent thermal temperature index in the country follows the altitudes, roughness and latitude. Accordingly, the low values of the indicator, which relate to the stresses of the cold, are consistent with the high and mountainous regions as well as the high latitudes, and vice versa, the thermal stresses occur in low and low elevations, as well as low latitudes, which of course, severe heat stresses occurred in the summer. Because throughout this season, the entire country of Iran is dominated by high tidal altitudes at high and low levels of ground pressure (1000 hp) with its warm and dry air, causing extreme heat and The term effects of heat waves on humans, heat loss, thermal contraction of the muscles and skin dryness, infectious or skin diseases, inflammation, sunburn, dizziness, fatigue, and mortality due to an increase in allergies can be mentioned. Significant differences in the environmental conditions of the mountainous masses of Kerman, Yazd and Sistan and Baluchestan provinces with their surrounding areas or low and low northern areas, and especially the Moghan Plain and Sarakhs plain, located in the upper latitudes of the country The issue is that the role of elevation in spatial distribution of the country's climate is much more colorful than factors such as latitude and longitude. The results of the analysis of the monthly thermal physiological stress maps showed that in terms of the area without tension, the march of the month with 47/8% of the area (778424/2km2) is in the first place and has the most favorable environmental conditions, The moon with 43/5 percent of the area (709275/2km2) is in the second position and also in March with 22.6 (359128/9km2) in the third, August and the last month. The highest thermal stresses (29
Dr. Firouz Mojarrad, Dr. Hassan Zolfaghari, Mr. Mehdi Keyghobadifar,
Volume 6, Issue 4 (2-2020)
Volume 6, Issue 4 (2-2020)
Abstract
Analysis of the Characteristics of Sultry Days in Iran
Extended Abstract
Sultry phenomenon occurs due to the combined effect of high temperature and humidity. Sultry intensity increases with increasing relative humidity and decreases with decreasing temperature. This phenomenon has a tremendous impact on comfort and other human activities. Various indices have been used to study this phenomenon in Iran and in the world. According to previous studies, and as far as information is concerned, there has not been a comprehensive study across Iran on the characteristics of sultry days based on degree of severity. Therefore, the purpose of this study is to investigate the frequency, duration and severity of sultry days and its temporal and spatial analysis throughout Iran.
To do this research, daily temperature, relative humidity and partial water vapor pressure of 101 synoptic stations were used for a 28-year period (1987-2014). In choosing the indices of sultriness, the goal was to select indices that show the sultry state on a daily scale. For this purpose, in the first stage, 16 empirical sultry or sultry-related indices were used, all of which used climatic parameters such as temperature, relative humidity, water vapor pressure and cloudiness to calculate the sultry state or comfort. Among them, 13 indices were eliminated because they surveyed the phenomenon on a monthly or annual basis or were not consistent with the objectives of this study. Finally, according to the objectives of the study, three indices were chosen: 1- Sultry Intensity Index (Lancaster-Carstone empirical equation), 2- Partial Water Vapor Pressure Index (partial water vapor pressure equal to or greater than 18.8 hPa), and 3- Heat Index (HI).
The results of this study showed that two indices of Sultry Intensity and Partial Water Vapor Pressure are suitable for explaining the conditions in Iran and their outputs are not significantly different. But Heat Index did not lead to desirable results. According to the results of the Sultry Intensity Index, the sultry phenomenon is not comprehensive in the country and is limited to 21 stations adjacent to the Caspian Sea coasts in the north (besides Parsabad Moghan Station) and the Persian Gulf coasts (besides Ahwaz station) and the Oman Sea coasts in the south. In other parts of the country, due to their internal and leeward position, being away from moisture sources, poverty or lack of vegetation and insufficient penetration of wet and rainy systems, there is no sultry condition and, on average, even one day is not seen with sultry circumstances. On the southern coasts, on average, sultry conditions begin on April 3 and end on November 16. Therefore, in this area, 7 months and 11 days of the year have sultry conditions. This is natural due to the lower latitude and the Azores high pressure sovereignty in the south. But on the northern coasts, the sultry period is shorter and with a 48-day delay compared with the southern coasts, the average sultry day begins on May 22 and ends on October 12. Therefore, the duration of the sultry period is on average 4 months and 19 days. In terms of the number of sultry days, the most frequencies belong to the southern coasts stations. The largest number of sultry days related to the Chabahar port on the coasts of the Oman Sea with 291 days, followed by Jask port with 264 days. The lowest number of sultry days is also from Ahwaz station with 1 day and then Mahshahr port with 42 days. Among the stations on the southern coasts, the Oman Sea stations compared with the Persian Gulf stations have more sultry days due to lower latitudes, Azores high pressure sovereignty and Southeast Asian monsoon moisture influence. In contrast, the number of sultry days on the northern coasts is much lower and averages 140 to 150 days a year. Sultry severity is also less, so that there are no extreme severe sultry days in any of the stations on the northern coasts. But the number of extreme sultry days is remarkable on the coasts of the South, to 160 days in the port of Chabahar and 111 days in the port of Jask. At Parsabad Moghan in the north and port of Mahshahr in the south, due to distance from the coast and lack of sufficient moisture, the duration and severity of sultry is much lower and there are basically no days of severe and extreme sultry states. The annual trend of the number of sultry days at any station is not significant.
Keywords: Sultry, Temperature, Relative Humidity, Sultry Indices, Iran
Reza Doostan,
Volume 6, Issue 4 (2-2020)
Volume 6, Issue 4 (2-2020)
Abstract
An Analysis of Drought Researches in Iran
Extended Abstract:
Iran is located the spatial geographical position in the south of the temperate region and north of the tropical region between the northern latitudes 40 to 25 degrees north and 65-44 degrees eastern along the seas, oceans and warm and great desert, on the other hand, with complex topography in the Alpine- Himalayas mountain belt (the world's largest mountain belt). These conditions have caused the climate of Iran to experience a variety of the prevailing natural hazards (33 of 43 world-wide risks). One of the natural hazards is the drought that happens over the Iranian plateau since the distant past, with the name of Dave of Drought, and so far. The Iranian plateau has undergone various drought periods over the past decades and various civilizations have faced this risk, and some of the Iranian ingenuity and management have emerged about this risk of the Iran. These include qanats, reservoirs built on commuter routes and cities, historical gardens, and so on. Today, this risk is dominant over the Plateau of Iran every year, and with increasing population and growth in different sectors and, in some cases to mismanagement, followed by a larger crisis called the water crisis and the crisis Economic-social, immigration, and so on. So, given the importance of the subject, different researchers have studied different aspects of this hazard. The fact is that in the past few decades, with the advent of computers and software and data, research has become easier and more scientific, naturally, in Iran, with these tools and data, researchers has been done on different parts of the crisis. What was the achievement of these studies, and most importantly, did the researchers contemplate a practical solution to the crisis on the Iranian plateau? This study provides an overview of past studies of drought and their achievements over the last few years.
In this study, used Four hundred and three of scientific articles were published in various journals to termed "drought" in the article titled of scientific information database (SID), one of the most important sources of internal research in Iran. The distribution of the time of research and distribution of various scientific fields that investigated the drought was identified. By studying the articles and the results from them, we found that 384 scientific articles with a specific output. Based on these findings, the frequency of articles in different fields of study was determined and analyzed.
researches of drought in the past years (1379 to 1391) had increasing trend and since 1394 has been decreas in Iran. The most drought research has been done in agricultural sciences with 166 papers from 403 papers (41.2%), geographic sciences with 118 papers (29.3%) and Medical and basic sciences and engineering sciences have the least research, 0.2, 2 and 5% respectively. 78% of the studies have examined the drought in different parts of Iran And 11 percent of the articles evaluated the consequences of this phenomenon. 7% of drought studies have predicted this phenomenon with different statistical models and 2.5% and 2% are dedicated to drought management and zoning in different regions of Iran respectively. Most drought studies hase been in Iran, Khorasan, Fars, Sistan and Baluchestan, Tehran, Isfahan and Kermanshah, but in other parts of Iran, studies have also been conducted in different regions. Therefore, the drought phenomenon has been studied in all regions of Iran and drought assessments have been carried out.
The reduction of drought researches in recent years suggests that quantitative and qualitative research has been carried out in this basin before 1395, and drought has been studied and evaluated with different indicators in different regions of Iran. The reality of Iran's climate and research shows that every part of Iran experiences a drought phenomenon, which is an Inherent characteristic of the climate of Iran, that given the geographical location and atmospheric patterns affecting these latitudes on the planet. The consequences of drought have also been reflected in different parts of the environment, social, economic, and so on. As part of the newspapers has indicative of the damage to this climatic phenomenon in recent years. It seems that the dominant section of the phenomenon is associated with the unconscious and real perception of managers and people of this phenomenon (which has a cultural root). At present, the consequence of severe and droughts in recent decades is the lack of proper planning and environmental degradation and crisis in various parts of Iran's environment. On the other hand, the negative consequences of global warming for the climate of Iran and similar climates are more and more worrying. Therefore, it is essential to take practical and practical solutions instead of evaluations and mere studies. The practical solutions and the production of technology and operational program in relation to these environmental crises require group research in the sub-sectors with together. While, for example, engineers play the most role in controlling superficial fluid (water and dam), But the smallest drought- research related in this area. Therefore, the separate study of each part of these hazards is merely an evaluation and is not a practical way of solving the risk for managers and planners; For example, a water crisis requires a team of researchers such as hydrology, climateology, meteorology, agriculture, urban management, rural, etc. Of course, it should be noted that our researchers have not been trained and not accustomed to group work, and the idea of teamwork is poor in our culture; But there is no way and should start from one point. Perhaps we should start with kindergartens and elementary schools in order to find suitable solutions for at least the next 20 years, researcher’s teams. Finally, it is necessary to address the sustainable development and drought, localization of indicators, operational and management plans based on the environmental capabilities and knowledge of the native area of each region.
Keywords: Drought Research, Evaluation, Achievement, Iran.
Saeid Jahanbakhsh Asl, Behruz Sari Sarraf, Hosein Asakereh, Soheila Shirmohamadi,
Volume 7, Issue 1 (5-2020)
Volume 7, Issue 1 (5-2020)
Abstract
The study of temporal - spatial changes of high extreme rainfalls in west of Iran (1965-2016)
Extended Abstract
Introduction
Rainfall is one of the appropriate weather parameters not only in describing weather condition in one specific area but also is in estimating potential impacts of climate change in the environment and in many economic and social systems. Some studies show that during half a century weather patterns by more and severe raining events and by changes in scheduling and rain status has been changed. From 1960s with its much slope, the abundance and severity of extreme rainfalls throughout the world has increased and it is expected to continue the increase until the end of the current century. So understanding the behavior of extreme events is one of the main aspects of climate change and the increase of information about heavy rains has utmost importance for society, especially for the population who lives in areas with increased flood risk.
According to above mentioned cases and abnormal behavior and irregular rainfalls in Iran and its high variability from one hand and Iran's west region ability to heaviness and extension of rainfalls on the other hand, the necessity of understanding and study of temporal and spatial dangerous rainfalls is recognized. Among extreme rainfall characteristics, the portion of such rainfalls in total rain production is studied less. Due to the experiments carried out, the increase of annual rainfall in Iran happens through heavy rainfalls. Therefore heavy rainfall portions out of total annual rainfalls can be defined as an index of crisis. The increase of this index implies the heavy floods in rainy years and severe drought and drought years.
Data and Method
Iran's west region including East and West Azerbaijan provinces, Zanjan, Kurdistan, Kermanshah, Hamadan, Lorestan, and Ilam consists of about 14 percent of Iran's total area. The height of this region includes a domain of 100 to about 4000 meters. Zagros mountain ranges are the most important characteristic of west of Iran, which are drawn from north-west to south-east.
In this research, we used network data from interpolation daily rainfall observation of 823 meteorology stations from January 1st up to December 31st, 2016 by using Kriging interpolation method and by separating 6×6 km spatial. The results formed matrix interpolation process by dimension of 18993×6410. This matrix has the rain status of 6410 points of west of Iran for every day rainfall (18993). Extreme rain falls are identified in terms of threshold of 95 percentile in each point and each day of year. The rainfall of each day and each pixel is compared to that related pixel and corresponding to that day and those days which their rainfalls rates were equal to or larger than threshold were identified for studying extreme rain fall portion in total yearly rainfall, the total of equal rainfalls and more than 95 percentile is calculated for each year and each of pixel and, it is divided to total of the same pixel rainfalls in that year.
We used the least squarely error for understanding temporal- spatial behavior of regression.
Results and Discussion
The average extreme rain falls in west of Iran is under the influence of their roughness and placement and also synoptic rainfall. The proof of this claim identifies through placement of average extreme rainfall over altitudes of region. By increasing geographical latitude in Iran's western provinces, it is decreased both of total extreme rainfalls and portion of such rainfall out of total yearly rainfall. Total extreme rainfall trend shows a frequency in a domain with 16 mm in each year. The negative trend of total rainfall with the area of 74.72 percent consists of three quarters of Iran's west.
The narrow strip of the west of Kurdistan and south-west of west Azerbaijan have the highest amount of positive trend which is meaningful in certainty level of 95 percent.
The study of process showed the ratio of extreme rainfalls portion to total yearly rainfall, which is increasing about 60.7 percent of west area of this country extreme rainfalls in total yearly rainfall and the greatest part of this area is located in southern half of the studied area.
The negative trend also is located in northern half and they have consisted of 39.29 percent of studied area of these, only in 29.81 percent of region, the trend ratio of extreme rainfalls to total yearly rainfalls are meaningful in certainty level of 95 percent.
Keywords: Extreme Rainfalls, Trend, 95 Percentile, Rainfall Portion, west of Iran.
Mr Farshad Pazhoh,
Volume 7, Issue 1 (5-2020)
Volume 7, Issue 1 (5-2020)
Abstract
Identification of the Effective Jet Stream Patterns In the Heavy Precipitation of the Cold Season In the Southern Half of Iran
Farshad Pazhoh[1], PhD in Synoptic Climatology, Department of Natural Geography, Faculty of Geographical Sciences, University Kharazmi, Tehran, Iran
Every year, important parts of a large part of our country are affected by the climatic hazards of heavy precipitation and lots of damages are done to the country. If the generating circulation patterns of heavy precipitation waves will identify, its occurrence can be predicted from at least one or two days before the beginning of the sequence of patterns ending in floods (Alijani, 2006, 156). Occurrence of heavy precipitation, so that its amount is more than the soil penetration capacity, causes runoff and floods. Now, if these heavy precipitations occur in urban areas, it is associated with more dangers, because the permeability in urban areas is less than in out-of-town areas, and a significant amount of such precipitation in urban areas has turned into runoff and floods. Cause damages to places, buildings and urban facilities (Taheri Behbahani and Bozorgzadeh, 1996, 2).
Two sets of data were used to conduct this research. One is surface data and the other is high atmospheric data. For this purpose, in the first category, the related precipitation data of the cold season of 8 synoptic stations in the southern half of Iran (Table 2) in the period from December 1, 1970 to March 31, 2014 were obtained from the Meteorological Organization. To identify the occurrence of heavy precipitation leading to major floods in the study area, considering that heavy precipitation has covered more than 50% of stations and the precipitation of each station is more than 95% during the study period.
Considering the above two conditions, 61 heavy and pervasive precipitations were selected from the total precipitations above the percentile of 95% of the stations. In the second category, high atmospheric data obtained from the National Oceanic and Atmospheric Administration of the United States. The synoptic scale in order to tracking the troposphere synoptic patterns includes a longitude of 20 west degrees to 100 east degrees and a latitude of 0 to 80 north degrees. In the selected synoptic scale, 1790 cells are located; the distance between each cell is 2.5 by 2.5 arc degrees.
In order to identify the jet stream patterns, first the factor analysis method with Varimax rotation was applied on the geo potential height data of 500 hPa during the selected 61 days of heavy and pervasive precipitations and found that the first 12 factors explain more than 90% data’s diffraction. The first factor accounts for about 32% of geo potential height data diffraction (Table 4). In the next step, in order to reduce the data volume and identify the synoptic patterns, the cluster analysis method was performed on the scores of the first 12 factors by the integration method and 4 synoptic patterns affecting the arrangement of the winds were extracted. Then, for each of the identified patterns, a representative day that had the highest correlation with the desired pattern determined (Table 3) and appropriate maps for the representative days of the patterns were drawn and analysed.
The results showed that the merged jet stream patterns (subtropical-sub polar), tropical jet stream (ridge-trough), orbital subtropical jet stream and meridian subtropical jet stream were effective in the occurrence of heavy precipitation, which meridian subtropical jet patterns and merged have played the most important role. In the first pattern, the merged jet stream plays role in 16 days and 26.3% of the precipitation days. The merged jet streams core is generally located on the Red Sea, and the subtropical jet stream penetrates from North Africa, and after crossing the Red Sea and northern Saudi Arabia, the left half of the jet stream’s exit covers the whole of the southern and central half of the country. The sub polar jet stream in a northwest-southeast direction from central and the west of the Europe from the centre and west of Europe penetrate to the lower latitudes and from central and eastern part of the Mediterranean and at the entrance part of the left side merge with subtropical jet stream. In the merger pattern, the sub polar jet stream corresponding to the western half of the trough of the middle-level of troposphere plays the role of cold air Advection and transferring the western winds to the lower latitudes, and the subtropical jet stream, corresponds to the eastern half of the trough, play the role of the discharge and divergence of warm and southern humid air on the southern half of the country’s atmosphere. In the second pattern, the subtropical jet stream (ridge-trough structure) with 13 days and 21.3%, generally in Northeast Africa, the subtropical jet stream with a huge ridge structure in direction of northwest to south east extends to the centre of the Red Sea and Saudi Arabia and also the trough structure of jet stream stretches from north of Iraq to the centre of the Red Sea. This trough structure’s sinkhole of jet stream this subtropical sinkhole has caused the left half of the jet stream's outlet with meridian curvature cover the whole of the southern half and most of the country after crossing Saudi Arabia and the Persian Gulf. But in the third pattern of the orbital subtropical jet stream, which plays a role in 14 days and 23.4% of heavy and pervasive precipitation days, the jet stream core has the most stretching and range, mainly from the eastern Mediterranean and north of Saudi Arabia to the western half of Iran, and the jet stream structure is completely formed west to east with least meridian structure. The intensity and pervasiveness of precipitations in this pattern such as the second one is weaker than the other patter. However, in the fourth pattern, the meridian sub-tropical jet stream is present as the most frequent pattern with 18 days and 29% of the selected precipitations days. In this pattern the jet stream has a southwest to northeast direction and the jet stream's core, like the third pattern, generally extends from north of Saudi Arabia to centre of Iran and sometimes to northeast of Iran. The locating of this jet stream with a suitable curvature on the important water resources of the south of the country and corresponding to the north eastern half of the trough from north eastern of Africa to north eastern of Iran after the merged pattern, has caused the most pervasive and intensive precipitations days in the south of the country.
Keywords: Heavy and Pervasive precipitation, Cluster Analysis, Subtropical Jet stream, Low Pressure, Trough, Southern half of Iran
Farshad Pazhoh[1], PhD in Synoptic Climatology, Department of Natural Geography, Faculty of Geographical Sciences, University Kharazmi, Tehran, Iran
Every year, important parts of a large part of our country are affected by the climatic hazards of heavy precipitation and lots of damages are done to the country. If the generating circulation patterns of heavy precipitation waves will identify, its occurrence can be predicted from at least one or two days before the beginning of the sequence of patterns ending in floods (Alijani, 2006, 156). Occurrence of heavy precipitation, so that its amount is more than the soil penetration capacity, causes runoff and floods. Now, if these heavy precipitations occur in urban areas, it is associated with more dangers, because the permeability in urban areas is less than in out-of-town areas, and a significant amount of such precipitation in urban areas has turned into runoff and floods. Cause damages to places, buildings and urban facilities (Taheri Behbahani and Bozorgzadeh, 1996, 2).
Two sets of data were used to conduct this research. One is surface data and the other is high atmospheric data. For this purpose, in the first category, the related precipitation data of the cold season of 8 synoptic stations in the southern half of Iran (Table 2) in the period from December 1, 1970 to March 31, 2014 were obtained from the Meteorological Organization. To identify the occurrence of heavy precipitation leading to major floods in the study area, considering that heavy precipitation has covered more than 50% of stations and the precipitation of each station is more than 95% during the study period.
Considering the above two conditions, 61 heavy and pervasive precipitations were selected from the total precipitations above the percentile of 95% of the stations. In the second category, high atmospheric data obtained from the National Oceanic and Atmospheric Administration of the United States. The synoptic scale in order to tracking the troposphere synoptic patterns includes a longitude of 20 west degrees to 100 east degrees and a latitude of 0 to 80 north degrees. In the selected synoptic scale, 1790 cells are located; the distance between each cell is 2.5 by 2.5 arc degrees.
In order to identify the jet stream patterns, first the factor analysis method with Varimax rotation was applied on the geo potential height data of 500 hPa during the selected 61 days of heavy and pervasive precipitations and found that the first 12 factors explain more than 90% data’s diffraction. The first factor accounts for about 32% of geo potential height data diffraction (Table 4). In the next step, in order to reduce the data volume and identify the synoptic patterns, the cluster analysis method was performed on the scores of the first 12 factors by the integration method and 4 synoptic patterns affecting the arrangement of the winds were extracted. Then, for each of the identified patterns, a representative day that had the highest correlation with the desired pattern determined (Table 3) and appropriate maps for the representative days of the patterns were drawn and analysed.
The results showed that the merged jet stream patterns (subtropical-sub polar), tropical jet stream (ridge-trough), orbital subtropical jet stream and meridian subtropical jet stream were effective in the occurrence of heavy precipitation, which meridian subtropical jet patterns and merged have played the most important role. In the first pattern, the merged jet stream plays role in 16 days and 26.3% of the precipitation days. The merged jet streams core is generally located on the Red Sea, and the subtropical jet stream penetrates from North Africa, and after crossing the Red Sea and northern Saudi Arabia, the left half of the jet stream’s exit covers the whole of the southern and central half of the country. The sub polar jet stream in a northwest-southeast direction from central and the west of the Europe from the centre and west of Europe penetrate to the lower latitudes and from central and eastern part of the Mediterranean and at the entrance part of the left side merge with subtropical jet stream. In the merger pattern, the sub polar jet stream corresponding to the western half of the trough of the middle-level of troposphere plays the role of cold air Advection and transferring the western winds to the lower latitudes, and the subtropical jet stream, corresponds to the eastern half of the trough, play the role of the discharge and divergence of warm and southern humid air on the southern half of the country’s atmosphere. In the second pattern, the subtropical jet stream (ridge-trough structure) with 13 days and 21.3%, generally in Northeast Africa, the subtropical jet stream with a huge ridge structure in direction of northwest to south east extends to the centre of the Red Sea and Saudi Arabia and also the trough structure of jet stream stretches from north of Iraq to the centre of the Red Sea. This trough structure’s sinkhole of jet stream this subtropical sinkhole has caused the left half of the jet stream's outlet with meridian curvature cover the whole of the southern half and most of the country after crossing Saudi Arabia and the Persian Gulf. But in the third pattern of the orbital subtropical jet stream, which plays a role in 14 days and 23.4% of heavy and pervasive precipitation days, the jet stream core has the most stretching and range, mainly from the eastern Mediterranean and north of Saudi Arabia to the western half of Iran, and the jet stream structure is completely formed west to east with least meridian structure. The intensity and pervasiveness of precipitations in this pattern such as the second one is weaker than the other patter. However, in the fourth pattern, the meridian sub-tropical jet stream is present as the most frequent pattern with 18 days and 29% of the selected precipitations days. In this pattern the jet stream has a southwest to northeast direction and the jet stream's core, like the third pattern, generally extends from north of Saudi Arabia to centre of Iran and sometimes to northeast of Iran. The locating of this jet stream with a suitable curvature on the important water resources of the south of the country and corresponding to the north eastern half of the trough from north eastern of Africa to north eastern of Iran after the merged pattern, has caused the most pervasive and intensive precipitations days in the south of the country.
Keywords: Heavy and Pervasive precipitation, Cluster Analysis, Subtropical Jet stream, Low Pressure, Trough, Southern half of Iran
[1] Corresponding Author: Email: climate.synoptic@gmail.com
Kaveh Mohammadpour, Mohammad Saligheh, Ali Darvishi Bloorani, Tayeb Raziei,
Volume 7, Issue 1 (5-2020)
Volume 7, Issue 1 (5-2020)
Abstract
Analysis and Comparing Satellite Products and Simulated
Of AOD in West Iran (2000-2018)
Kaveh Mohammadpour, Ph.D. Student in Climatology, Kharazmi University of Tehran
Mohammad Saligheh, Associate Professor in Climatology, Kharazmi University of Tehran
Ali Darvishi Bloorani, Assistant Professor in RS & GIS, Tehran University
Tayeb Raziei, Assistant Professor in Climatology, SCWMRI, Iran
Introduction
Dust are the main type of aerosols that affects directly and indirectly radiation budget. In addition, those affect the temperature change, cloud formation, convection, and precipitation. In recent years, the increase of different sensors and models has made possible to research the dust. The most important studies about dust analysis has been considered of Aerosol Optical Depth (AOD) as the most key parameter, which are based on the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve this, it has used of MODIS and MACC to study and identify the behavior of dust in the last two decades over west Iran.
Materials and methods
Areas in this study are Ilam, Kermanshah, Kurdistan, Lorestan and Hamedan provinces. The area has studied of two data series such as: first is MACC data with a spatial precision of 14 km2 and a 3-hour time scale; and other one is MODIS sensor production on the Terra satellite with a 10-square-kilometers resolution. In order to analyze the dust in the area in the period 2000 to 2018, statistical methods and simulation has used of the AOD parameter in MACC and MODIS. Before any processing, the data regraded to 0.2 × 0.2 degrees in order to compare the data. Then, the average daily AOD formed in a 22 × 23 matrix with 560 pixels that presented with 3653 × 560 for MACC during 2003 to 2012 and 6489 × 560 for MODIS during 2000-2018. Average of daily AOD obtained of MACC and MODIS calculated using of statistical equations. Then, the spatial distribution of AOD during the dusty months for synoptic stations and total province surface extracted using of R packages during the daily time series of the periods. Finally, the spatial distribution of the obtained AOD interpolated using the kriging function.
Results and Discussion
The average annual AOD obtained from Deep Blue algorithm from MODIS was less than MACC in all of the interested stations, except for Hamedan and Khorramabad stations, and provinces surfaces.
Correlation of AOD between MODIS and MACC shown that the correlations is high between model and sensor data (R2 = 59). In addition, the spatial correlation map shows 0.38 to 0.76 in which indicates a significant relationship between the MACC and MODIS pixels and the relationship is more in the western provinces of the area than the northeast of the region (Hamedan). The monthly comparison of the mean of AOD of the sensor and the model in the whole the area shows a highest correlation between the AOD in February and October.
The interpolation of the spatial distribution in the decade of the study (2003-2012) in MACC showed that the spatial variations of AOD is decreasing from the south of Ilam to the north of Kurdistan and reached the lowest level in the north of Kurdistan province. In general, the findings of annual and seasonal spatial distribution (dry period) of dust showed that MACC overestimated AOD compared to MODIS in the area. Nonetheless, the dust pattern in both of the sensor and the model increased from south to north. Although, the dust pattern is more regular in the sensor than the model. The spatial distribution of dust in Ilam, Kermanshah, and Kurdistan provinces in MODIS and MACC shows that dust in the southern point of the Ilam province has the highest concentration and the lowest is observed in the northeast of Kurdistan province. This spatial distribution of dust showed that dust in western provinces of the area follow latitudinal trend , in which is influenced by the high topography of Kermanshah and Kurdistan provinces and the proximity of Ilam province to dust sources in the distribution of dust intensity.
Conclusion
The results showed that there was a significant correlation between the sensor and the model and the coefficient was more than 0.4 in all months on the area. The findings of the annual amount of dust in MODIS showed that the amount of dust in the years 2000 to 2009 has increased in whole areas and from 2009 onwards, this annual trend has been reduced by 2018. MACC findings also showed that the AOD has been growing up in the period, although AOD amount have had a steep slope by 2010, but since 2010, dust has a steady slope. Therefore, West Iran has experienced two active (before 2010) and inactive (after 2010) periods in dust during an 18-years period on the area. The findings of MODIS and MACC in the study area indicate that the monthly distribution of dust from April to August has the highest concentration. In general, the annual and seasonal spatial distribution (months with the highest AOD) of dust indicates that the intensity of AOD in MACC was higher than MODIS in the area. Although the sensor and model has a roughly similar pattern and increases from south to north, but the trend in MODIS is more regular than MACC.
Keywords: Aerosol Optical Depth (AOD), MACC, MODIS, West Iran
Koohzad Raispour, Yones Khosravi,
Volume 7, Issue 2 (8-2020)
Volume 7, Issue 2 (8-2020)
Abstract
Abstract
Air pollution is one of the most important problems in many countries in the world, which, besides the environmental damage and human health, imposes many adverse social and economic impacts. Therefore, considering the vital importance of air and the rising course of increasing the contaminating agents in recent decades, it is necessary to study the elements and their pollutant gases in order to be aware of the existing situation and to adopt the necessary solutions. The phenomenon of atmospheric air pollution in Iran, as part of the world's atmosphere, is one of the goals of the industrial revolution, which has been increasing day by day as industrialization; population growth and urbanization have grown dramatically. Carbon monoxide (CO) is a colorless, odorless, and tasteless gas that is slightly less dense than air. In the atmosphere, it is spatially variable and short lived, having a role in the formation of ground-level ozone. Carbon monoxide consists of one carbon atom and one oxygen atom, connected by a triple bond that consists of two covalent bonds as well as one dative covalent bond. Carbon monoxide is produced from the partial oxidation of carbon-containing compounds; it forms when there is not enough oxygen to produce carbon dioxide (CO2), such as when operating a stove or an internal combustion engine in an enclosed space.
Carbon monoxide is one of the most dangerous air pollutants. Due to its importance, many techniques and methods have been used to monitor the Earth's atmosphere in recent years. as well as, the use of satellite data has become widespread because of the availability and availability of features such as spatial, temporal and spatial resolution. In this study, the data from Aqua / AIRS Carbon Monoxide data can be used to study the rate and trend of carbon monoxide gas changes in the atmosphere of the entire world, including Iran.The relevant data in NetCDF format, with one-day and 13.5 x 13.5km spatial resolution of during the 16-year statistical period (2003-2018), was extracted from ttps://disc.gsfc.nasa.gov/datasets/AIRS3STM_006 using ArcGIS software And Grads are processed, represented, analyzed.
The results indicate that the amount of carbon monoxide was reduced during the monthly and annual time series. Of course, monthly and seasonal variations have been impressive. Monthly, the highest concentration of carbon monoxide in January, February and March, and the lowest in August, September and October. Among the seasons, the highest and lowest levels of carbon monoxide were observed in the seasons of winter and summer, respectively. In spatially, the highest amount of surface carbon monoxide with an average of 150 ppb above the city of Tehran and the coastal area of the Caspian Sea and its lowest level with an average of 115 ppb on the Zagros heights was observed.
The results clearly show a clear picture of the dispersion of carbon monoxide gas in the horizontal and vertical direction of Iran's atmosphere. Based on the results obtained from the monthly carbon monoxide data collected during the statistical period (2003-2018), conducted in a three dimensional and regional area extending to the geographical area of Iran, The average surface carbon monoxide of more than 150 ppb above the Tehran metropolitan area and northern coast of Iran is less than 115 ppb on Zagros altitudes. Among other results, there are significant differences between the monthly carbon monoxide average in the surface troposphere of Iran, so that in the twelve months, the highest amount of carbon monoxide was observed in cold months and the lowest was observed in the warm months of the year, respectively. Seasonally, the highest level of seasonal carbon monoxide has been observed in winter and its seasonal season has peaked in summer. The results of vertical profiles (vertical aspect) of carbon monoxide changes in Iran's atmosphere in line with latitude and longitude indicate the maximum carbon monoxide concentration at lower levels of barley so that the maximum amount of carbon monoxide in the Iranian atmosphere is concentrated in the lower levels and Rarely exceeds the level of 250 hPa. Also, the results indicate that the rate of carbon monoxide emissions in the atmosphere of Iran has decreased, so that in the last years of the statistical period, about 30% of the amount of carbon monoxide in the atmosphere of Iran has been reduced, compared to the early years of the statistical period.
Key words: Air Pollution, Carbon Monoxide, AIRS, Remote Sensing, Iran.
Dr Hassan Lashkari, Miss Neda Esfandiari,
Volume 7, Issue 2 (8-2020)
Volume 7, Issue 2 (8-2020)
Abstract
Identification and synoptic analysis of the highest precipitation linked to ARs in Iran
Abstract
Atmospheric rivers (ARs) are long-narrow, concentrated structures of water vapour flux associated with extreme rainfall and floods. Accordingly, the arid and semi-arid regions are more vulnerable to this phenomenon. Therefore, this study identifies and introduces the highest precipitation occurred during the presence of ARs from November to April (2007-2018). The study also attempted to demonstrate the importance of ARs in extreme precipitation, influenced areas and identifies the effective synoptic factors. To this end, integrated water vapour transport data were used to identify ARs, and documented thresholds applied. AR event dates were investigated by their daily precipitation, and eventually, ten of the highest precipitation events (equivalent to the 95th percentile of maximum precipitation) associated with ARs were introduced and analyzed. The results showed that most ARs associated with extreme precipitation directly or indirectly originated from the southern warm seas. So the Red Sea, the Gulf of Aden and the Horn of Africa were the major source of ARs at the time of maximum IVT occurred. Synoptically, seven AR events formed from the low-pressure Sudanese system and three events from integration systems. The subtropical jet was the dominant dynamic of the upper troposphere, which helped to develop and constant of ARs. Moreover, the predominant structure of jets had a meridional tendency in Sudanese systems, while it was a zonal orientation in integration systems. The intense convective flows have caused extreme precipitation due to the dominance of strong upstream flow besides having the highest moisture flux. The station had the highest precipitation has been located in the eastern and northwestern region of the negative omega field or upstream flows.
Keywords: Identification and synoptic analysis, highest precipitation, Ars, Iran.
Dr Hasan Lashkari, Mrs Mahnaz Jafari,
Volume 8, Issue 1 (5-2021)
Volume 8, Issue 1 (5-2021)
Abstract
Synoptic Patterns that Determine the Trajectory of Precipitation Systems of Sudanese Originntroduction
Introduction
Precipitation as an important climatic element has many irregularities and fluctuations. Iran, especially its southern half, has significant precipitation fluctuations. Several atmospheric systems are involved in the formation of precipitation in this region from of Iran. Sudanese system is one of the most important precipitation systems in Iran. This system, in different synoptic conditions, enters Iran from different input sources and passes through Iran in different ways.
The important and influential role of Sudan's low pressure on precipitation in Iran, especially in the southern part of the country, has been repeatedly demonstrated in numerous studies. But the formation and its expansion have received little attention. These reasons have led to the consideration of the position of Sudan's low-pressure synoptic expansion as an influential factor in the southern half of Iran precipitation. Therefore, the position of the expansion of this important climatic system has been investigated separately in the precipitation of the three regions south west, south middle and south east.
Materials and Methods
Two categories of data were used for this study. These data include daily precipitation data from the Iranian Meteorological Organization and the ERA interim gridded data include Sea Level Pressure (SLP) and the Geopotential Height of the 700 HP atmospheric level of the ECMWF. Second category data with horizontal resolution of 0.5 × 0.5° degrees during 1997-2017 statistical period were prepared.
To achieve the purpose of the study, the southern half of Iran was first divided into three regions: South-West, South-Mid and South-East. After extracting daily precipitation of the selected stations in all three geographic regions, a total of 142 precipitation systems was identified by applying the required criteria. From this number of precipitation systems, respectively, were obtained in the south west 107, south middle 19 and southeast 16, respectively. Then, the source of precipitation systems was extracted using the atmospheric lower level maps. Subsequently, the central core and zone of the first closed curve around the Sudanese low pressure were extracted separately for each group. The main axis of the Sudanese low-pressure trough are also drawn on all rainy day. Finally, the model or pattern of atmospheric circulation in the precipitation systems of the regions is presented separately.
Results and Discussion
The purpose of this study was to determine the position of the central core and the pattern of expansion of the first closed curve around the Sudanese system and the Sudanese system trough in precipitation in each of the three regions of the southern half of Iran. Since the arrangement of precipitation systems may vary in different months of the year, depending on the general atmosphere of the atmosphere, the position of the core, the pattern of expansion of the low-pressure trough and the trough of 700-hPa atmospheric level is analyzed separately each month.
In the synoptic pattern of systems, entering from the south west of Iran, the Arabian Subtropical High Pressure with the southwest-northeast direction is located in the eastern half of the Arabian Peninsula and west of the Oman Sea. In this pattern, the troughs are generally north-south. As a result, the rainfall intensity and intensity of precipitation systems, entering the south west of Iran are higher than the other two routes. The focal point of troughs this route is between 30 to 40° east (Eastern Mediterranean). In systems with South-Mid route, the Arabian Subtropical High Pressure has slightly shifted southward and found a northeast-southwest axis. In this pattern, the Mediterranean troughs are generally northeast-southwest. This pattern causes precipitation in the eastern half of the Iran. Or at least no precipitation in the northwest and west of the Iran.
The synoptic pattern of precipitation systems that enter Iran from the southeast is somewhat more complex. In this pattern, the Arabian Subtropical High Pressure has an unusual eastward shift. So that it is based in India. The troughs of this path showed two completely opposite patterns. In some systems, the troughs in the southwest-northeast direction with the orbital inclination, covers the whole of Saudi Arabia and southern Iran. On the contrary, in some systems the troughs stretch quite opposite to the first group, the northwest-southeast direction.
This asymmetry in the expansion of the troughs should be traced to the general topography of the Tibetan Plateau and the circulation pattern of caused by the presence of the Tibetan anticyclone. Basically Mediterranean troughs are disrupted in their usual eastward displacement after a longitude of 60 degrees. As you can see, the Sudanese low-pressure troughs for the South-East Route lack structural discipline and coordination.
Conclusion
The results of this study show that the location and pattern of expansion of the first closed curve around low pressure in different precipitation months and systems of the three zones do not differ significantly in location. Rather, it is the most important system in determining the direction of Sudanese systems, the Arabian Subtropical High Pressure and the pattern of expansion of the eastern Mediterranean trough. In the synoptic pattern of systems, entering from the south west of Iran, the Arabian Subtropical High Pressure with the southwest-northeast direction is located in the eastern half of the Arabian Peninsula and west of the Oman Sea. In this pattern, the troughs are generally north-south. In systems with South-Mid route, the Arabian Subtropical High Pressure has slightly shifted southward and found a northeast-southwest axis. In this pattern, the Mediterranean troughs are generally northeast-southwest. The synoptic pattern of precipitation systems that enter Iran from the southeast is somewhat more complex. In this pattern, the Arabian Subtropical High Pressure has an unusual eastward shift. So that it is based in India. The Sudanese low-pressure troughs for the South-East Route lack structural discipline and coordination. This asymmetry in the expansion of the troughs should be traced to the general topography of the Tibetan Plateau and the circulation pattern of caused by the presence of the Tibetan anticyclone.
Keywords: Synoptic Patterns, Sudanese Low Pressure system, Eastern Mediterranean Trough, Southern Half of Iran, Arabian Subtropical High Pressure.
Alireaz Salehipour Milani,
Volume 8, Issue 3 (12-2021)
Volume 8, Issue 3 (12-2021)
Abstract
Analyzing and Monitoring of Light Pollution in Iran Using Night Light Satellite Data (1997 to 2013(
Introduction
Light pollution generally refers to an unplanned increase in artificial lighting and the consequent change in light levels is not guided (Lu, 2002). Light pollution is called standard pollution at an inappropriate time or place and is said to be annoying and polluting the environment and the night sky.Studies show that excessive exposure to artificial light, especially in the dark hours of the night, can be considered as light pollution and adversely affect the environment and humans. Studies show that excessive exposure to artificial light, especially in the dark hours of the night, can be considered as light pollution and adversely affect the environment and humans. The exponential growth of population and the rapid rate of urbanization and industrialization in Iran has significantly increased the amount of artificial light at night and increased the amount of light pollution. There are various tools for assessing night light variations, including operational linear satellite scanning data for the Meteorological Defense Satellite Program (DMSP / OLS). This data not only helps in assessing the severity of light pollution but can also be used as a tool for risk management and high-risk zoning and susceptibility of this pollution. This study attempts to analyze the spatio-temporal pattern of light pollution in Iran.
Material and method
This study was conducted at national and provincial level. DMSP / OLS night light images were used as data for this study. The data were downloaded from the National Geophysical Data Center (NGDC) Office of the National Oceanic and Atmospheric Administration (NOAA). The brightness in these images reflects the night light in residential areas of DMSP / OLS night optical illumination from six satellites (F10, F12, F13, F14, F15 and F16) and the spatial resolution of these images is 850 meters. The calibrated digital data of the DMSP / OLS satellite are digital numbers (DN) of each pixel between zero and 63 and were therefore classified into 6 classes in order to better analyze the images was used. Classes with digital numbers (DN) less than 1 are as areas without luminosity, 1/12/4 with very low luminance, 12/24/4/8/8 with low luminosity, 24/37/2/2 with Moderate luminosity, 37 / 49-2 / 37 high brightness and 49-6 / 63 high brightness areas. The rate of change of digital number (DN) at the national and provincial levels, as well as the percentage and area of each class in each time period, and the rate of change in each class over the period 1991 to 2001, 2001 to 2004, 2004 to 2006, 2006 to 2011, 2011 to 2013. In order to investigate the effect of human factors on night light changes, the relationship between night light and relative population density at country and provincial level and its variation over time periods were studied and statistical relationship between them was calculated.
Discussion and Results
The three provinces that occupy most of the area with the most glare in the provinces are: Tehran with 2621 square kilometers, Khuzestan with 2214 square kilometers (Figure E2), 3- Isfahan with 1891 sq. Km. In addition, the lowest luminosity area belongs to the three North Khorasan provinces (95 km2), South Khorasan (118 km2) and Ardabil province (127 km2). Have earned their own. mong the provinces of the country, DMSP / OLS Satellite and Satellite Provinces in 2013 are the most glare-free region of the country, covering an area of about 168002 km, followed by Kerman provinces with 161800 km and Yazd with 121491 sq km is next in rank. The highest relative density of the country was observed in Tehran provinces (654 people / km2), Alborz (270 people / km2), respectively.
This high relative density of population in these two provinces has increased the amount of artificial light produced so that Tehran province accounts for the highest percentage of night light area with very high brightness (8.8%) in 1996 and a total of 0.5%. 46% of the province is in the range of light with very low, low, medium, high and very high brightness, and the rest of the province lacks brightness at night, which accounts for the least percentage of night light in the country. Is. Alborz province has the second highest relative density of population in the year 1996 and at the same time after Tehran province has the highest brightness of light with 5/16.
Conclusion
The results of this study show that the amount of night light in the country has been steadily increasing from 1996 to 2013, and the percentage of the area with very low brightness has increased by 25.8%, for the low brightness area (111.8%). , Increased in the region with moderate luminosity 142.5%, in high luminosity region (140.2%), and in high luminosity region 156.8%, which could be a warning for the spread of light pollution in the country.. In 2013, the two provinces of Tehran, Alborz and Tehran provinces had the highest amount of artificial light in terms of area and percentage of the area with high brightness at night, and Khuzestan, Bushehr, Fars and Isfahan provinces. There are other provinces that rank next.
Keyword: Artificial Night Light, DMSP/O Satellite, Light Pollution, Iran
Introduction
Light pollution generally refers to an unplanned increase in artificial lighting and the consequent change in light levels is not guided (Lu, 2002). Light pollution is called standard pollution at an inappropriate time or place and is said to be annoying and polluting the environment and the night sky.Studies show that excessive exposure to artificial light, especially in the dark hours of the night, can be considered as light pollution and adversely affect the environment and humans. Studies show that excessive exposure to artificial light, especially in the dark hours of the night, can be considered as light pollution and adversely affect the environment and humans. The exponential growth of population and the rapid rate of urbanization and industrialization in Iran has significantly increased the amount of artificial light at night and increased the amount of light pollution. There are various tools for assessing night light variations, including operational linear satellite scanning data for the Meteorological Defense Satellite Program (DMSP / OLS). This data not only helps in assessing the severity of light pollution but can also be used as a tool for risk management and high-risk zoning and susceptibility of this pollution. This study attempts to analyze the spatio-temporal pattern of light pollution in Iran.
Material and method
This study was conducted at national and provincial level. DMSP / OLS night light images were used as data for this study. The data were downloaded from the National Geophysical Data Center (NGDC) Office of the National Oceanic and Atmospheric Administration (NOAA). The brightness in these images reflects the night light in residential areas of DMSP / OLS night optical illumination from six satellites (F10, F12, F13, F14, F15 and F16) and the spatial resolution of these images is 850 meters. The calibrated digital data of the DMSP / OLS satellite are digital numbers (DN) of each pixel between zero and 63 and were therefore classified into 6 classes in order to better analyze the images was used. Classes with digital numbers (DN) less than 1 are as areas without luminosity, 1/12/4 with very low luminance, 12/24/4/8/8 with low luminosity, 24/37/2/2 with Moderate luminosity, 37 / 49-2 / 37 high brightness and 49-6 / 63 high brightness areas. The rate of change of digital number (DN) at the national and provincial levels, as well as the percentage and area of each class in each time period, and the rate of change in each class over the period 1991 to 2001, 2001 to 2004, 2004 to 2006, 2006 to 2011, 2011 to 2013. In order to investigate the effect of human factors on night light changes, the relationship between night light and relative population density at country and provincial level and its variation over time periods were studied and statistical relationship between them was calculated.
Discussion and Results
The three provinces that occupy most of the area with the most glare in the provinces are: Tehran with 2621 square kilometers, Khuzestan with 2214 square kilometers (Figure E2), 3- Isfahan with 1891 sq. Km. In addition, the lowest luminosity area belongs to the three North Khorasan provinces (95 km2), South Khorasan (118 km2) and Ardabil province (127 km2). Have earned their own. mong the provinces of the country, DMSP / OLS Satellite and Satellite Provinces in 2013 are the most glare-free region of the country, covering an area of about 168002 km, followed by Kerman provinces with 161800 km and Yazd with 121491 sq km is next in rank. The highest relative density of the country was observed in Tehran provinces (654 people / km2), Alborz (270 people / km2), respectively.
This high relative density of population in these two provinces has increased the amount of artificial light produced so that Tehran province accounts for the highest percentage of night light area with very high brightness (8.8%) in 1996 and a total of 0.5%. 46% of the province is in the range of light with very low, low, medium, high and very high brightness, and the rest of the province lacks brightness at night, which accounts for the least percentage of night light in the country. Is. Alborz province has the second highest relative density of population in the year 1996 and at the same time after Tehran province has the highest brightness of light with 5/16.
Conclusion
The results of this study show that the amount of night light in the country has been steadily increasing from 1996 to 2013, and the percentage of the area with very low brightness has increased by 25.8%, for the low brightness area (111.8%). , Increased in the region with moderate luminosity 142.5%, in high luminosity region (140.2%), and in high luminosity region 156.8%, which could be a warning for the spread of light pollution in the country.. In 2013, the two provinces of Tehran, Alborz and Tehran provinces had the highest amount of artificial light in terms of area and percentage of the area with high brightness at night, and Khuzestan, Bushehr, Fars and Isfahan provinces. There are other provinces that rank next.
Keyword: Artificial Night Light, DMSP/O Satellite, Light Pollution, Iran
- Shiva Gharibi, Dr Kamran Shayesteh,
Volume 8, Issue 3 (12-2021)
Volume 8, Issue 3 (12-2021)
Abstract
Application of Sentinel 5 satellite imagery in identifying air pollutants Hotspots in Iran
Shiva Gharibi1, Kamran Shayesteh2
1- PhD Student of Environmental Science, Malayer University, Malayer, Iran.
2-Assistant professor, Department of Environmental Sciences, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran
k.shayesteh@malayeru.ac.ir
Extended abstract
1- Introduction
Today, poor air quality is one of the most important environmental problems in many cities around the world. Air pollution can have a devastating effect on humans, plants, organisms, and human assets, and efforts are being made to anticipate and analyze the amount of distribution and transmission of air pollutants in order to minimize the adverse effects on air quality and climate. Among the most important air pollutants are (CO), (SO2), (NO2), (O3) and aerosols (AI). Numerous studies have been conducted on the monitoring of these pollutants based on information and statistics from pollution monitoring devices, but the use of satellite images in the field of monitoring and measuring pollutants has been limited. Due to the increasing growth of these pollutants, in this study, an attempt has been made to identify the average spatial concentration of the most important air pollutants as the actual sources of pollution on the scale of Iran from October 2018 to December 2019. Also, identifying the most polluted centers in Iran based on the average of 5 pollutants is another goal of this study. Therefore, the aim of this study is to demonstrate the ability of Sentinel satellite to monitor air pollutants, and the ability of GPW images to produce a population density map for the first time on an Iranian scale.
2- Methodology
Using the Python programming language in the Google Earth Engine program environment, various products related to CO, SO2, NO2, O3 and AI pollutant images, obtained from Sentinel-5 satellite images during the study period and in the scale of Iran, were obtained for monitoring of air pollutants and determination of pollutants focuses. The output variable is defined as a set of images based on the time filter (2019) and the spatial filter (Iran borders). The output of the average concentration of pollutants for each month is calculated separately and annually in these filters. Then, the spatial map of the average concentration of pollutants in the Arc map software was analyzed and statistical information related to the average concentration of these pollutants was processed by SPSS statistical software. To determine the hotspots in terms of all pollutants, the raster location map of each pollutant was classified using the Jenks algorithm. In order to identify the share of provinces and counties, the amount of pollutants was also analyzed by spatial statistics in GIS environment and using the Zonal Statistics command based on the defined administrative boundaries. The G statistic was used for Cluster analysis, and in order to identify Hot Spots and Cold Spots, Getis-Ord Gi statistic (Gi) was used in GIS environment.To determine the population of each province, the latest census information of Iran as well as satellite images related to the fourth version of Gridded Population of World (GPW) product were used. Finally, The Moran index was used to determine the pattern of pollutants distribution and the spatial autocorrelation.
3- Results
Spatial output from the processing of Sentinel-5 satellite images during the study period for identifying air pollution centers in Iran showed that the highest levels of nitrogen dioxide were recorded in the majority of cities in Tehran and Alborz provinces and then in the centers of other provinces. In the case of carbon monoxide, the highest rate is in Tehran and the coasts of the Caspian Sea and Khuzestan, and coastal areas of Bushehr and Hormozgan provinces. The highest amount of ozone is in the northern parts of the provinces of West and East Azerbaijan, Ardabil, Gilan, Mazandaran, Golestan and Northern Khorasan. Most of the dust was in the southern, eastern, southeastern and central provinces of Iran. The highest amount of sulfur dioxide pollutants is recorded in Tehran and then in the provinces of Khuzestan, Kerman, Hormozgan, Bushehr, Markazi, Qom, Isfahan and Khorasan Razavi. Provincially, the highest share of nitrogen dioxide is in the provinces of Tehran, Alborz, Qazvin and Qom. The highest provincial share of carbon monoxide is in Khuzestan, Gilan and Mazandaran provinces. The highest share of dust is in the southeastern provinces, including Sistan and Baluchestan, the highest share of sulfur dioxide is in Khuzestan province, and the highest share of ozone pollution is in the coastal provinces of Caspian Sea. Compliance of the average 5 pollutants with Google Earth images showed that the contaminated areas are located in the cities of Abadan, Imam Khomeini Port, Mahshahr Port and Ahvaz (Khuzestan Province), Tehran, Pakdasht (Tehran Province) and Assaluyeh Port (Bushehr Province). The results of comparing the average concentrations of pollutants in different seasons showed that there was no significant difference between CO, NO2 and O3 pollutants in different seasons, but suspended particles and aerosols in winter and autumn seasons have a significant difference with the amount of this pollutant in spring and autumn. Also, SO2 pollutant in autumn had lower concentrations than other seasons. The results of clustering analysis to determine the status of significant spatial clusters showed that the data are in the confidence range and have spatial auto-correlation and cluster distribution pattern.
4- Discussion & Conclusions
According to Sentinel-5 satellite images, most of the pollution centers in Iran are related to petrochemical industries and refineries, which are located in the cities of Abadan, Imam Khomeini port, Mahshahr port and Ahvaz (Khuzestan province), Assaluyeh port (Bushehr province) and common pollutants. By these centers are NOX, SO2, CO, suspended particles and aerosols. Also, other centers (Tehran, Pakdasht in Tehran province) are located in the most populous urban areas of, which have been identified as hotspots in high production of NO2 and CO, due to high population and urban traffic. Due to the higher population density of Tehran and Pakdasht than other cities in Iran, air pollution can be more important in these cities. Therefore, the use of satellite imagery to monitor Iran's air pollutants and the location of hotspots can be very cost-effective and time-consuming.
Keywords: Air Pollution Monitoring, Sentinel, Satellite Imagery, Polluted Hotspot, Moran’s Index.
Seyed Ali Badri, Siamak Tahmasbi, Bahram Hajari,
Volume 8, Issue 3 (12-2021)
Volume 8, Issue 3 (12-2021)
Abstract
Investigation of Temperature and Precipitation Changes in the Seymarreh Basin by Using CMIP5 Series Climate Models
Abstract
Panel reports on climate change suggest that climate change around the world is most likely due to human factors. Temperature and precipitation are two important parameters in the climate of a region whose variations and fluctuations affect different areas such as agriculture, energy, tourism and so on. Seymareh basin is one of the most significant sub-basins of Karkheh. The purpose of this study is to predict the impact of climate change on precipitation and temperature of the Seymareh Basin in 2021-2040 period. These effects were analyzed at selected stations with uncertainties related to atmospheric general circulation models (GCMs) of CMIP5 models under two scenarios of RCP45 and RCP85 through LARS-WG statistical model. Then the uncertainties of the models and scenarios were investigated by comparing the monthly outputs of the models by the coefficients of determination coefficient (R2) in the forthcoming period (2021-2040) with the base period (1980–2010). The root mean square error (RMSE) calculations presented the best model and scenarios for generating future temperature and precipitation data.
The Seymareh catchment is the largest and the main Karkheh sub-basin that covers parts of Kermanshah, Lorestan and Ilam provinces. The length of the largest river at the basin level to the site of the Seymareh Reservoir Dam is approximately 475 km, and the area of the basin is 26,700 km2. Geographic coordinates of the basin are from 33° 16 ́ 03 ̋to 34°59 ́ 29 ̋north latitudes and 46°6 ́9 ̋to ̋ 5 ́ 0 ° 49 Eastern longitudes, minimum basin height 698 m at the dam outlet and its maximum height 3,638 m. It is on the western highlands of Borujerd.
The information used in this study was obtained from the Meteorological Organization of the country. For this study, three synoptic stations of Kermanshah, Hamadan and Khorramabad, which had the highest statistical records and had appropriate distribution at basin level, were used. These data included daily and monthly temperature and precipitation information, and sunshine hours.
The LARS-WG fine-scale exponential model was proposed by Rasko et al., Semnoff and Barrow (1981). We used daily data at stations under current and future weather conditions. In order to select the best GCM model from the models mentioned above, minimum temperature, maximum temperature, precipitation and sunshine data were entered daily in the base period (1980–2010) and data were generated for five models under two scenarios of RCP45 and RCP85 for the period 2040–2021. The data were generated in 100 random series and the mean of required variables (minimum temperature, maximum temperature and rainfall) were extracted monthly in the period 2021-2040. Then, root mean square error (RMSE) and determination coefficient (R2) were used to evaluate the performance of the models and compare the results.
To ensure the models' ability to generate data in the coming period, computational data from the model and observational data at the stations under study should have been compared. The capability of the LARS-WG model in modeling the minimum temperature, maximum temperature, and radiation at the stations under study was completely consistent with the observed data. The model's ability to exemplify rainfall was also acceptable, however the highest modeling error was related to March rainfall.
By comparing the observed and produced data including monthly average precipitation, minimum and maximum temperatures through five mentioned models with their indices, the best model and scenario for future fabrication were determined. The results of this comparison showed that among the available models, HADGEM2-ES model under RCP 4.5 scenario had the best result for precipitation and HADGEM2-ES under RCP 8.5 scenario predicted the best result for maximum temperature. Determining the best model, precipitation data, minimum temperature and maximum temperature produced in the selected models and scenarios were analyzed to investigate the climate change temperature and precipitation for the future period.
The results of this study indicated that due to the wide range of output variations of different models and scenarios, by not taking into account the uncertainties of the models and scenarios can have a great impact on the results of the studies. It was also found in this study that the LARS-WG exponential model was capable of modeling precipitation data and baseline temperature in the study area, so that the radiation data, minimum and maximum temperatures were completely consistent with the data.
The observations are consistent and the models' ability to predict rainfall is very good and acceptable manner. In investigating the uncertainties caused by atmospheric general circulation models and existing scenarios, the best model to predict precipitation in the study area is HADGEM2-ES model under RCP 8.5 scenario, the best model for temperature estimation model HADGEM2-ES under RCP scenario No. 4.5.
The overall results of this study revealed that the average precipitation in the basin will decrease by 4.5% on average, while the minimum temperature will be 1.5° C and the maximum temperature will be 2.17° C. The highest increase will be due to the warmer months of the year. Notable are the disruptions of rainfall distribution and the high temperatures will have significantly negative consequences than rainfall reduction.
- : Climate Change, Climate Scenarios, Uncertainty, LARS-WG, Seymareh.
Hossein Asakereh, Seyed Abolfazl Masoodian, Fatemeh Tarkarani,
Volume 8, Issue 4 (3-2022)
Volume 8, Issue 4 (3-2022)
Abstract
Introduction
Geographical situation of Iran is a place for interacting many physical and human processes which lead to specific precipitation climatology in the country. The month to month variation of precipitation is one of the features which the precipitation climatology may reflect due to tempo - spatial characteristics. In fact, monthly distribution of precipitation is one of precipitation normal features building up the climate structure. In order to recognize this fundamental characteristic three following questions have been raised:
1) Have the month to month distribution of precipitation changed over recent four decades?
2) How is the pattern of relationship of month to month distribution of precipitation and spatio - topographical variables?
3) Is it possible to find a spatial pattern for decadal changes of precipitation of month to month distribution?
Data and Methods
In order to find a responses for the abovementioned questions the distribution of month to month precipitation and its decadal changes was considered by adopting coefficients of variations (CV) for 46 years (1970-2016) and using the third version of Asfazari dataset. The relationship of precipitation data and spatio-topographical variables calculated based on regression techniques. Moreover, the spatial pattern considered by using cluster analysis. The CV calculated as follow:
here
،
، 
are ith raw's and jth column's CV, standard deviation, and monthly mean, respectively. CV and its relationships with spatio-topographical variables were calculated in two temporal scale, for whole the under investigation period (1970-2016) and in decadal period for four decades (1977-1986, 1987-1996, 1997-2006, 2007-2016).
Discussion
The results of current study proved that the month to month different in precipitation amounts have had spatial variations, whilst the temporal trends is not statistically significant. In addition, the minimum, maximum, and consequently, the range of values also the averages have not experienced significantly changes. However, the region experiencing the same values of precipitation illustrated oscillatory behavior. Accordingly, the decadal variations have happened in different areas. Although the there have been statistically significant relationships between monthly CV and spatio - topographical factors, the correlations were low. Based on cluster analysis, we found 5 regions according to CV and its anomalies in compares with normal CV for all under investigation period. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.
Results
Precipitation is known a chiastic and complicated climate element. One of chiastic behaviors which precipitation shows in its different time - scale behavior is its month to month distribution among a given year. In current research the decadal variation of above-mentioned behavior among recent four decades and the variation of its relationships and the spatio - topographical features , as parts of climate structure of the country, have investigated in details.
Our finding illustrated that the month to month different in precipitation amounts have had tempo - spatial variations, whilst the temporal long - term trends is not statistically significant. Moreover, the values of minimum, maximum, and consequently, the range of month to month CV also the decadal averages have not experienced significantly changes over four under study decades. However, the region experiencing the same values of precipitation depicted oscillatory behavior. consequently, the decadal variations have happened in different areas. Although there have been statistically significant relationships between monthly CV and spatio - topographical variables, the correlations were not considerably high. Based on cluster analysis technique, we found 5 regions according to CV and its anomalies in compares to normal CV for all under study decades. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.
KeyWords: Iran precipitation, Month to month changes in precipitation, Inter annual variation of precipitation, Precipitation anomaly, Spatial analysis of precipitation
Kaveh Mohammadpour,
Volume 8, Issue 4 (3-2022)
Volume 8, Issue 4 (3-2022)
Abstract
Application of multivariate techniques in-line with spatial regionalization of AOD over Iran
Introduction
Models, satellites and terrestrial datasets have been used to detect and characterize aerosol. Nontheless, micoscale classification using remote sensing parameters considers as a deficiency. Thus, regionalizion and modeling aerosol without regard to political boundaries or a specific stations over Iran demonstrates the spatial distribution of simple AOD structures.
Materials and methods
Present study attempted to simulate and detect homogeneous areaes of aerosol in Iran using AOD (areosol optical depth) datast at 550 nm across Iran. Among the eigen techniques, principal component analysis (PCA) is the most applicable and controversial classification applied as multivariate analysis approach. In the line of the target, PCA, S-Mode separate the AOD subgroups with similar correlations. In the mode, m time series apply to each n station or grid points as a variable in the analysis, which is the territory of the region or geographical area. Mathematically, if the input data column in the Z matrix is applied as mathematical variables and the Z matrix has n points in the time series and m is the time step, then in the Zs decomposition has 3654×9985. In addition, the scree test and North's rule were used to cut-off the principal components and to select the number of appropriate special vectors to be kept.
Results and Discussion
For the study purpose, 85 percentaile of loadings were used to determine AOD areas over Iran. Using the method, the spatial patterns of Iran's aerosolshave been divided into six subregions, which are the major centers affected by the AOD. These major AOD hotspots affect by AOD extermes that are originated from aerosol surrounding sources. So that, the geographical location of sources areas have caused the northeastern atmosphere of Iran to be influenced by severe storms originating from the Karakum Desert. The same is correct concerning the East and Southeast regions. While, the intensification and transfer of aerosol from the Sistan plain to the south is increased AOD load over southeast Iran. Moreover, this study revealed a set points associated with distinguishing spatial differences between the west-northwest and southwest regions as well as central region that have not addressed in previous studies because of focus on ground-based observations. Also, the method illustrated that formation of the identified regions are a function of the volume, growth, and spread of aerosol particles resulting from the source regions in the Middle East. Finally, the classification techniques converting dynamic phenomenon such as aerosol into simpler structures presented a interpretable understanding of the geographical distribution of the phenomenon.
Conclusion
The present study identified the spatial patterns of AOD hotspots into six distinct regions including northeast, west-northwest, southeast, southwest, central and eastern Iran affected by the aerosol as well as major centers or high gradient areas. In addition, the present study not only supported by previous studies, but also it make sense a regionalization that was neglected by former studies, whileseperated the boundaries of the AOD areas without considering provincial boundaries. Overall, the classification techniques, PCA, simplified a dynamic phenomenon such as aerosol into a simpler and illustrated geographical and interpretable understanding of the spatial distribution of the phenomenon.
Keywords: Aerosol Optical Depth (AOD), Multivariate Techniques, Regionalization, Iran
Mr Alireza Sadeghinia, Mrs Somayeh Rafati, Mr Mehdi Sedaghat,
Volume 8, Issue 4 (3-2022)
Volume 8, Issue 4 (3-2022)
Abstract
Introduction
Climate change is the greatest price society is paying for decades of environmental neglect. The impact of global warming is most visible in the rising threat of climate-related natural disasters. Globally, meteorological disasters more than doubled, from an average of forty-five events a year to almost 120 events a year (Vinod, 2017). Climate change refers to changes in the distributional properties of climate characteristics like temperature and precipitation that persist across decades (Field et al., 2014). Because precipitation is related to temperature, scientists often focus on changes in global temperature as an indicator of climate change. Valipour et al. (2021) reported the mean of monthly the global mean surface temperature (GMST) anomalies in 2000–2019 is 0.54 C higher than that in 1961–1990. Many studies have been done on climate change in Iran. These studies have mostly studied the mean and extreme temperature trends (Alijani et al., 2011; Masoudian and Darand, 2012). In general, the results of previous studies showed that the statistics of mean, maximum and minimum air temperature in most parts of the Iranian plateau have increased in recent decades. Also, the increase of minimum temperature is greater than maximum temperature.
A review of the research background shows that we need to understand more about regional climate change in Iran. Therefore, present study performs the climate change of 14 extreme temperature indices using multivariate statistical methods at the regional scale.
Data and methodology
Historical climate observations including daily maximum and minimum temperature were obtained from the Iranian Meteorology Organization for the period 1968 to 2017 at 39 stations. In this paper, 14 extreme temperature indices defined by ETCCDI were analyzed. The indices are as follows: (1) Annual maxima of daily maximum temperature (TXx); (2) Annual maxima of daily minimum temperature (TNx); (3) Annual minima of daily maximum temperature (TXn); (4) Annual minima of daily minimum temperature (TNn); (5) Cold nights (TN10p); (6) Cold days (TX10p); (7) Warm night (TN90p); (8) Warm day (TX90p); (9) Frost days (FD); (10) Icing days (ID); (11) Summer day (SU); (12) Tropical nights (TR); (13) The warm spell duration index (WSDI) and (14) the cold spell duration index (CSDI). The extreme temperature indices were extracted using R software environment, RclimDex extension. The Mann–Kendall Test and Sen’s Slope Method was employed to assess the trends in 14 extreme temperature indices. To identify homogeneous groups of stations with similar annual thermal regimes, Principal Component analysis (PCA) and Clustering (CL) was applied. Pearson correlation coefficient was used to investigate the relationship between height and trend slope.
Result
All the extreme temperature intensity indices (TXx, TNx, TXn, and TNn) showed increasing trends during 1968 to 2017. The increasing trends of TXx, TNx, TXn, and TNn were 0.2, 0.3, 0.44, and 0.5 ° C per decade, respectively. These results indicated that the extreme warm events increased and the extreme cold events decreased. The average of the extreme temperature frequency indices over Iran showed that the frequency of warm night (TN90p) and warm day (TX90p) significantly increased with a rate of 6.9 and 4.2 day per decade, respectively. Also, the frequency of cold night (TN10p) and cold day (TX10p) significantly fell with a decrease rate of 3.8 and 3.8 day per decade, respectively. The frequency of warm nights (TN90p) was higher than that of warm days (TX90p). The result indicated that the trend of nighttime extremes were stronger than those for daytime extremes. The average of frost days (FD) and icing days (ID) indices over Iran showed decreasing trends during 1968 to 2017 with rates of 3 and 1.1 d per decade, respectively. While, the averaged of summer days (SU) and tropical days (TR) indices over Iran showed increasing trends with rates of 4.4 and 6.4 day per decade, respectively. The warm spell duration index (WSDI) indices showed a clear increase, with a rate of 2.1 per decade. In contrast the cold spell duration index (CSDI) showed a significant decrease, with a rate of 1.7 per decade. In general, the cold indices displayed decreasing trends, whereas the warm indices displayed increasing trends over most of Iran. Pearson correlation coefficient between height and Sen’s Slope was estimated to be equal to -0.62 (p < 0.01). In general, the results of this study showed that there is a negative correlation between the elevation factor and the Sen’s Slope of warm extreme indices. That is, as the altitude decreases, the Sen’s Slope increases. Therefore, the stations located in low altitude have experienced stronger increasing trends than in high altitude. The area of Iran was classified into four clusters using PCA and CL methods. Cluster 1 has experienced the strongest increasing trends. The average height of cluster 1 is 535 meters. Approximately 38% of the studied stations were located in cluster 1. Cluster 2 showed a moderate heating trends. 33% of the stations were located in cluster 2. Most of the stations of cluster 2 are located in the northwest and west of Iran. Cluster 3 showed a weak increasing trends compared to clusters 1 and 2. The stations of cluster 3 did not show a special geographical concentration and were scattered in all parts of Iran. 18% of the studied stations are located in cluster 3. The stations of Cluster 4, have experienced weak decreasing trends, which was different from the other three clusters
Conclusion
In this study we analyzed the climate change of extreme temperature indices in Iran. The result showed that the frequency of warm nights, warm days, summer days and tropical days increased. Also, the frequency of cold nights, cold days, Frost days and icing days decreased. The warm spell duration index showed a clear increase. In contrast the cold spell duration index showed a significant decrease. In general, the extreme warm events increased and the extreme cold events decreased over most of Iran. There is a negative correlation between the elevation factor and the Sen’s Slope of extreme warm indices (R = -0.62). Therefore, the stations located in low altitude have experienced stronger increasing trends than in high altitude. The area of Iran was classified into four clusters using PCA and CL methods. Cluster 1 has experienced the strongest increasing trends. The average height of cluster 1 is 535 meters. Therefore, the most heating have occurred in Low-lying areas of Iran. Cluster 2 and Cluster 3 showed a moderate and weak heating trends, respectively. The stations of Cluster 4, have not experienced clear trends.
Key words: climate change; Extreme temperature; clustering; Iran
Sharifeh Zarei, Bohloul Alijani, Zahra Hejazizadeh, Bakhtiar Mohammadi,
Volume 8, Issue 4 (1-2021)
Volume 8, Issue 4 (1-2021)
Abstract
In this research, the most important synoptic patterns of widespread snowfall in the western half of Iran have been investigated. For this purpose, the data of current weather code and snow depth of 36 synoptic stations during the statistical period of 1371-1400, for the months of October to March, were received from the Meteorological Organization of the country. In order to investigate wide snowfalls, the days when more than 70% of the studied area saw snowfall at the same time were extracted as a wide day. In order to perform synoptic-dynamic analysis of wide snowfalls in the western half of Iran, the classification method using cluster analysis was used and maps of representative days were drawn, including atmospheric temperature, moisture flux, geopotential height, tovai, front formation, jet stream, omega index, and orbital and meridian wind data. Trend analysis was also performed using the Mann-Kendall test. The results showed that 4 models justify the widespread snowfall in the studied area in the best way. According to the results in all the models, at sea level, the collision of cold and dry air of northern latitudes with warm and humid air of southern latitudes has caused the formation of frontal fields in the western half of Iran. At the level of 500 hectopascals, the intensification of the meridional currents in the western winds caused the creation of closed centers and as a result the flow changed in the direction of the westerly winds, and the location of the western half of Iran in the east of Naveh Al-Aghti and Sardchal has provided the necessary conditions for air to rise. Also, there was no trend in the number of snow days in the western half of Iran at the significant levels tested. But; The number of snow days has been decreasing over time. In general, it can be concluded that due to the warming of the earth and climate change, the number of snowy days has decreased and these changes have led to a significant shortening of the snow season.
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