@article { author = {Yamani, M and Jedari Eyvazi, J. and Jahadi, M}, title = {The Investigation of Flood Flows in Madarsoo River In the Catastrophic Floods, 2001 & 2002}, journal = {Physical Geography Research}, volume = {42}, number = {72}, pages = {-}, year = {2010}, publisher = {University of Tehran}, issn = {2008-630X}, eissn = {2423-7760}, doi = {}, abstract = {Introduction Catastrophic floods are exceptional phenomena that usually return periods longer than the other floods commonly do. The severe hydrological events that on August 2001 and 2002 occurred in Madarsoo river Basin produced extreme floods in the number of sub-basins and the main watercourse. Madarsoo river basin is a sub-basin of Gorganrood in Golestan province. This paper focuses on the types of flood that flow in this basin. These floods had important changes in morphology of Madarsoo basin. Because of the floods, about 300 passengers and residents died in the region and within a few hours important changes were created in the basin landscape. The discharge and the severity of this flood compared to the mean annual flood, and also to the maximum size of instantaneous discharge recorded in five decades for the Basin, were exceptional. The measures such as intensity, the sudden flood phenomenon and what has been left there, such as many pieces of stone with over 1 meter in diameter in the bottom and the sides of the river channels and surface of the fans are reasonable. On the other hand, some injuries on the trees as well as the long-term return periods placed these floods in the group of catastrophic floods. The return period of these floods has been calculated to be about 55 years to 200 years. Materials and Methods The methods used in this research are Descriptive-Analytic and causal researches. This research has been conducted using descriptive- analysis. The research tools were mainly topographic maps (scale 1:50000 and 1:100000), Geology maps and satellite images with high resolution (Quick Bird of 2004 and IRS 1998) and field work tools such as GPS were used. A lot of information in the field working and observations and measurements were collected as well as the previous studies. To check the conditions before the flood, aerial photographs (scale 1:55000 in 1955 and scale 1:20000 in 1975 and IRS images in 1998 with digital resolution analysis and software) were used for comparison. For digitalizing and transferring the data and also the required measures, ARC View and ARCGIS softwares were used. Analyzing the data is performed with argument methods and inference with correlation between related variables. The analysis of geologic layers, faults, drainages, the slope and the old zoning of landslides were used as original data. Finally, the analysis of the tools of data analysis was conducted using cases through the comparison of two variables and their influence on floods that raised the problem of research. Then, the method of the occurrence of torrential flow of Madarsoo River (in Golestan forest) in the form of a basin and data hydrometer station using hydrologic models is classified. Results and Discussion Occurrence of heavy rainfall in Madarsoo Basin on one of the driest months in 2001 and 2002 (September) increased the water volume pressure and created instable slopes on hills in forested areas of Golestan National Park. This problem caused large amounts of slippery material and old unstable material to move and to flow down the slopes, and this phenomenon could carry large pieces of stone and trunks of the trees. Within the semi-arid basin, the extensive formation of marl and conglomerate makes many Gullies and causes their development. The Creation of the material through intense rainfalls increased in these areas and it has led to the development of Gullies. As a result, the range based on the current review of 75 sub-basins was a little more separated, and then all of them were classified as general in the second group. 42 sub-basins were caused by normal flood. These floods in their own beds directions did not cause any main geomorphologic changes; while 33 sub-basins very heavy streams. Also most small basins densely covered by vegetation were caused by normal flood; while in 19 small basins in Golestan forest range of materials flow has occurred. The recent catastrophic floods in Madarsoo basin had many geomorphic effects and made many changes. One of these effects is the original river bed being intensively profound by erosion. For the determination of the profound disruption of the bed, we took several profiles through the bed river and the status was compared to the status before the flood. The measurements on the profiles show the amount of profundity to be at least 3 meters and maximum 12 meters. For clarifying the factors contributing to the current occurrence of basin materials studied, the flow path length and the area of fan deposits at the end of it were measured by size. The measurements of the basin level with current materials indicated that 56% of the occurrence is in basins smaller than 5 kilometers. 28% of the basins had an area of 5 to 20 kilometers and 9% had an area of over 20 kilometers. These studies show that basins smaller than 5 kilometers have the highest frequency of occurrence. Conclusion The results show that numbers of small and steep sub-basins were invaded by debris and hyper concentrated Flows. To get the results, these sub-basins can be divided to 75 small basins. 42 of these experienced the water floods, 3 sub-basins invaded hyper concentrated flows and 30 of them invaded the debris flows. The debris and hyper concentrated flows volume and peak discharges are much more than the water floods that are usually estimated by traditional risk management on mountainous basins. This is one of the most important reasons for the failures in many of the flood control plans.}, keywords = {Catastrophic floods,debris flow,floods,Golestan forest,Madarsoo River}, title_fa = {انواع جریان‌های سیلابی رخ‌داده در رودخانه مادرسو (در اثنای سیلاب‌های کاتاستروفیک مرداد‌ماه سال‌های 1380 و 1381)}, abstract_fa = {سیلاب‌های شدید مردادماه سال‌های 1380 و 1381 حوضة رودخانه مادرسو از نظر نوع جریان با سیلاب‌های عادی تفاوت‌های زیادی داشته است، به طوری که تغییرات عمده‌ای را در ریخت‌شناسی (مورفولوژی) حوضه ایجاد کرده است. این پژوهش با استفاده از روش‌های توصیفی‌ـ تحلیلی و ابزارهایی چون عکس‌های هوایی، تصاویر ماهواره‌ای، نقشه‌های توپوگرافی و زمین‌شناسی منطقه و اندازه‌گیری‌های حاصل از برداشت‌های میدانی و عکس‌های زمینی به بررسی و تقسیم‌بندی انواع جریان‌های سیلابی وقوع‌یافته در رودخانة مادرسو (جنگل گلستان) پرداخته است. تجزیه و تحلیل در قالب روش حوضه‌ای و داده‌های ایستگاه هیدرومتری با استفاده از مدل‌های هیدرولوژیک و سرانجام تطبیق آنها با یافته‌های روی زمین انجام پذیرفته است. نتایج نشان می‌دهد که از تعداد 75 زیرحوضة واقع در حوضه‌های تنگراه و جنگل گلستان، قیزقلعه و دشت، حدود 42 زیرحوضه دچار جریان‌های سیلابی معمولی شده است، در حالی که 3 زیرحوضه با جریان‌های بسیار غلیظ و 30 زیرحوضه نیز با جریان‌های مواد مواجه بوده‌اند. مسئلة مهمی که مورد تأکید قرار گرفته، این است که حجم جریان‌های بسیار غلیظ، جریان‌های مواد، جریان‌های چوبی و دبی‌های آنها، بسیار بزرگ‌تر از جریان‌های سیلابی معمولی است. بدیهی است که در برنامه‌ریزی‌های آتی برای طراحی هر سازه‌ای در مسیر رودخانه، باید این مسئله پیش‌بینی شود.}, keywords_fa = {جریان مواد,جنگل گلستان,رودخانة مادرسو,سیلاب کاتاستروفیک,سیلاب معمولی}, url = {https://jphgr.ut.ac.ir/article_21575.html}, eprint = {https://jphgr.ut.ac.ir/article_21575_4e7b07709b053e10bf73d079801bc268.pdf} } @article { author = {Khoshhal, J and Rezai, A and Yasari, T}, title = {Modeling of Various Developmental Stages in One Spring Safflower by Temperature and Day Length}, journal = {Physical Geography Research}, volume = {42}, number = {72}, pages = {-}, year = {2010}, publisher = {University of Tehran}, issn = {2008-630X}, eissn = {2423-7760}, doi = {}, abstract = {Introduction Safflower is an annual, broad leaf oil seed crop of the family compositae adapted chiefly to dry land. Safflower is originally a cold season and long day crop. It is believed to have originated in southern Asia and is known to have been cultivated in China, India, Iran and Egypt almost from prehistoric times. During the middle ages, it was cultivated in Italy, France and Spain and soon after discovery of America, the Spanish took it to Mexico and then to Venezuela and Colombia. Safflower was originally grown as the flowers that were used in making red and yellow dyes for clothing and food preparation. Today also safflower can be cultivated for oil, foots medicinal purpose and cosmetic products. The planted area has reached 795118 ha and resulted in 731425 tons of production in the world during 2004. Planted area in Iran is about 6000 ha with 1 ton seed yield per ha. The highest planted areas in Iran belong to Isfahan, Khorasan and Yazd provinces respectively. Plant development can be defined as a programmed qualitative change in the plant form, which leads plant to maturity, and researchers call it the phases of development or phenology. Plant development is different from plant growth, because plant growth is the result of photosynthesis process during which dry matter accumulates. Water, nitrogen and photosynthetic matters affect growth and development. Under irrigated conditions, all factors except climatic elements can be controled. Thus, only the climatic elements can change the growth and the development of plants and in this case, temperature and day length have the main role. Materials and Methods Field experiments were conducted in 2006-2007 and 2007-2008 at the Kaboutar Abad Agricultural Research Station, to model the response of Arak variety to day length and temperature changes in different planting dates. Developmental rate of each stage was estimated using the inverse of developmental duration as the dependent variable and various temperature variables derived from daily maximum (Tmax), minimum (Tmin) and mean (Tmean), day length (DL) and the combination of these variables as the independent variables in stepwise regression models. A step of the regression was considered appropriate if the highest R2 was accompanied by the significant (R}, keywords = {Day length,Developmental Stages,modeling,Safflower,temperature}, title_fa = {مدل‌سازی مراحل نمو یک رقم گلرنگ بهاره، با استفاده از درجه حرارت و طول روز}, abstract_fa = {برای ارزیابی تأثیر‌پذیری طول مراحل مختلف نمو گلرنگ رقم اراک، از تغییرات طول روز و دما و مدل‌سازی سرعت نمو در دوره‌های مختلف نمو، آزمایش‌هایی با بهره‌گیری از تاریخ‌های مختلف کاشت طی سال‌های 86-1385 و 87-1386 در مزرعه تحقیقات کشاورزی کبوترآباد اصفهان انجام گردید. برای تخمین سرعت نمو طی هر مرحله، عکس طول هر مرحله به عنوان متغیر تابع و متغیرهای حرارتی، طول روز و حاصل‌ضرب متغیرهای حرارتی با متغیرهای طول روز به عنوان متغیر مستقل در رگرسیون مرحله‌‌ای مورد استفاده قرار گرفتند. مرحله‌ای از رگرسیون به عنوان مدل مناسب انتخاب گردید که ضریب رگرسیون و ضریب تشخیص آخرین جزء آن حداقل در سطح احتمال 10 درصد معنی‌دار باشد و حداکثر ضریب تشخیص کل را داشته باشد. تعداد روز از کاشت تا سبز شدن، سبز شدن تا رویت طبق، سبز شدن تا رسیدگی و گل‌دهی تا رسیدگی از تاریخ‌های کاشت تأثیر پذیرفت. با افزایش دما، طول مراحل نمو کاهش یافت. طول دوره سبز شدن تا رؤیت طبق بیشترین تأثیر را از طول روز پذیرفت و با افزایش آن کاهش یافت. درجه حرارت حداقل تنها متغیری بود که وارد مدل شد و به تنهایی حدود 76 درصد تغییرات سرعت سبز شدن رقم اراک را توضیح داد. حدود 84 درصد تغییرات سرعت نمو در طول دوران سبز شدن تا رویت طبق به‌وسیله حاصل‌ضرب درجه حرارت حداکثر در طول روز، توجیه گردید. بخش عمده واریانس سرعت نمو این رقم طی دوران سبز شدن تا رسیدگی به‌وسیله حاصل‌ضرب مربع میانگین حرارت در مربع طول روز و به میزان حدود 66 درصد توضیح داده شد. حاصل‌ضرب میانگین دما در طول روز، توان چهارم، دوم و اول درجه حرارت حداقل متغیرهای بعدی بودند که وارد مدل شدند و روی هم حدود 80 درصد تغییرات سرعت این دوره را بیان کردند. توان چهارم درجه حرارت حداقل تنها متغیری بود که سرعت نمو مرحله گل‌دهی تا رسیدگی را به میزان حدود 55 درصد توضیح داد.}, keywords_fa = {دما,طول روز,گلرنگ,مدل‌سازی,مراحل نمو}, url = {https://jphgr.ut.ac.ir/article_21576.html}, eprint = {https://jphgr.ut.ac.ir/article_21576_03bf95b9f0d926266dbbab1b0ec5a33f.pdf} } @article { author = {Azizi, Gh and Faraji Sabokbar, H.A and Abaspour, R.A and Safarrad, T}, title = {The Model of the Spatial Variability Precipitation in the Middle Zagros}, journal = {Physical Geography Research}, volume = {42}, number = {72}, pages = {-}, year = {2010}, publisher = {University of Tehran}, issn = {2008-630X}, eissn = {2423-7760}, doi = {}, abstract = {Introduction The relationship between topography and precipitation in order to estimate the type and amount of precipitation in mountainous areas has always been of great importance for climatologists. In most of researches done based on regression model, the independent parameters such as elevation, slope, aspect, longitude and latitude have been used and the rule of distance to describe the spatial variability has been neglected while the mentioned parameter has a determining rule in spatial variability of precipitation; as an example, Marquinez et al (2003; 2) used the distance from coast line of Cantabrian in northern Spain as an independent variable to describe the spatial variability of precipitation in mountainous areas. Materials and Methods In the present work, the significant relation between precipitation and parameters of elevation, slope, aspect, longitude, latitude, distance from west baseline and distance from ridge axe has been considered using the multivariate regression model. In fact, the west baseline is the furthest west line of the case-study (located on the borders of Iran and Iraq) where the air masses arrive and the distance from their is a criterion for keeping away from humidity sources and the distance from ridge axe is considered as a distance from the high part of the mountain axis as a function of raising of air masses. The area under study is divided by homogenous areas via precipitation variability. The area under study in this research is the mountainous area of western Iran located in the central Zagros. 269 precipitation recording stations, including the meteorology organization (synoptic, climatology and rain gauge stations) and rain gauge stations related to the Ministry of Power have been used and after converting the data of Power Ministry to A.D dates( because the mentioned organization has not used A.D dates) all of the stations that have a complete data between 1995 -2004 were selected (in the present work a complete statistical period of ten years has been used to prevent the errors of the stations with no data). Results and Discussion There are some assumptions in each multivariate regression model where assuming them being correct, the regression results are valid; otherwise the model should be substituted by another one. The assumptions are (Esmailian 2006; 230): • The errors mean is zero e.g. • Although the variance of errors is passive, it is constant e.g. • The co-variances of errors of i and j are zero e.g. • The three mentioned assumptions are equivalent with Considering the accuracy of the mentioned assumptions in a linear regression model, we should pay attention to the assumptions of normality of residuals and consider the constancy of variance. To investigate normality of the residual, Kolmogorov-Smirnov(K-S) Test histogram P-P and Q-Q can be used. The invariability of the variance of residual can be investigated using the scatter plot. In addition there are two or more independent variables in multiple regressions; therefore, two tests are needed to identify their significance; namely, a regression equation significance test at the first stage and a test for the significance of each of the partial coefficients at the next stage. In this study, in order to test the significance of the regression, T statistic was used and the autocorrelation in noise was tested using Durbin-Watson (D-W) -the test is based on first order autocorrelation error (cited in Khezri; 2009, 100). The normality of dependent variables was investigated using K-S test and in order to explore the significant relationship between the independent variables (slope angle, aspect, elevation, longitude, latitude, distance from west baseline and distance from ridge axe) and dependent variables, the Pierson correlation was used. Adjusted coefficient of determination (R2) in this model indicates that about 0.57 of precipitation variability in mountainous central Zagros can be explained using the independent variables in this model. Meanwhile taking into account the significance level of each variable and with regard to comparing them with error level of 0.1, it was confirmed that the coefficients of longitude, latitude, elevation, distance from ridge and slop angle are significant at 0.99. Equation precipitation after assessing the validation of the regression model for the studied area was calculated as follows: Where X is the longitude, Y is the latitude, Dr is the distance from ridge axe, S is the slop angle, H is the elevation and P is the logarithm of the precipitation. Conclusion The results of this study showed that topographies have a mechanical effect on the entered air masses and strengthen them when they are rising. The amount of precipitation increases as the elevation increases, but it should be considered that the maximum precipitation is not coinciding upon the ridge axe. Based on average of profiles, windward in both western and eastern regions is wetter than in the upwind section. In order to model spatial variability, the recent study used the distance from ridge axe and the distance from west baseline for the first time in Iran. Due to having no statistical significance for the distance from west baseline variable, it is not suggested to be used for the next researches that are aimed to model spatial variability of precipitation. With regard to the significance of distance from the ridges variable (99 %), it is suggested that researchers utilize the variable in future studies for modeling the spatial variability of precipitation in Zagros and especially central Zagros.}, keywords = {Central Zagros.,Digital Elevation Model,modeling,Multivariation regression,Special analysis}, title_fa = {مدل تغییرات مکانی بارش در زاگرس میانی}, abstract_fa = {ارتباط بارش و ارتفاع به‌منظور برآورد میزان و نحوة تغییرپذیری بارش در مناطق کوهستانی، همواره از موضوعات مورد توجه اقلیم‌شناسان بوده است. در این تحقیق سعی شده است از طریق مدل رگرسیونی، بارش منطقة زاگرس میانی مدل‌سازی گردد. تمام داده‌های موجود بارندگی منطقة مورد مطالعه ـ اعم از سازمان هواشناسی (سینوپتیک، کلیماتولوژی و باران‌سنجی) و وزارت نیرو ـ گرد‌آوری شد، که پس از تبدیل داده‌های وزارت نیرو به تاریخ میلادی، کل ایستگاه‌هایی که دارای دادة کامل بین سال‌های 1995 تا 2004 بودند انتخاب شدند. بدین‌منظور بارندگی به عنوان متغیر وابسته و ارتفاع، شیب، جهت شیب، طول و عرض جغرافیایی، فاصله از خط مبنای غربی، فاصله از خط‌الرأس به عنوان متغیرهای مستقل در نظر گرفته شدند. دو متغیر فاصله از خط مبنای غربی و فاصله از خط‌الرأس‌ها تاکنون مورد استفاده قرار نگرفته‌اند. مدل‌سازی از طریق متغیرهای مستقل معنادار انجام پذیرفت و با تقسیم منطقه به دو بخش رو به باد و پشت به باد و همچنین ترسیم نیمرخ‌های طولی بارش و ارتفاع، عمود بر خط‌الرأس‌ها، نحوة تغییرپذیری مکانی بارندگی بررسی گردید. بدین ترتیب مشخص شد که با وجود هماهنگی نسبی بین بارندگی‌ و ناهمواری، هستة بیشینة بارندگی بر محور مرتفعِ ناهمواری‌ها منطبق نیست. نتایج تحقیق نشان می‌دهد که رابطة معناداری بین فاصله از خط‌الرأس و بارش وجود دارد و این موضوع در تحقیق مورد بررسی قرار گرفته است. با توجه به معنی‌داری این متغیر (در سطح 99 درصد)، پیشنهاد می‌گردد در پژوهش‌های آتی برای مدل‌سازی تغییرات مکانی بارش در زاگرس و به‌ویژه زاگرس میانی، از این متغیر استفاده شود. همچنین به‌دلیل معنی‌دار نبودن متغیر مستقل فاصله از خط مبنای غربی، استفاده از آن در سایر پژوهش‌های مرتبط با مدل‌سازی تغییرات مکانی بارش در زاگرس میانی پیشنهاد نمی‌شود.}, keywords_fa = {تحلیل فضایی,رگرسیون چندمتغیره,زاگرس میانی,مدل رقومی ارتفاع,مدل‌سازی}, url = {https://jphgr.ut.ac.ir/article_21577.html}, eprint = {https://jphgr.ut.ac.ir/article_21577_7064caa89dafc03050cc637338c93706.pdf} } @article { author = {Khosravi, M and Poodineh, M.R}, title = {A Survey on Climatic Impacts of Gonu Tropical Cyclone (June2007) in Southeast of Iran}, journal = {Physical Geography Research}, volume = {42}, number = {72}, pages = {-}, year = {2010}, publisher = {University of Tehran}, issn = {2008-630X}, eissn = {2423-7760}, doi = {}, abstract = {Introduction A tropical cyclone (TC) is a synoptic-scale to mesoscale low-pressure system over tropical or subtropical waters with organized convection and definite cyclonic surface wind circulation. Tropical cyclones are massive storms formed in tropical waters, capable of producing violent winds, flooding, and heavy amounts of rainfall. They have significant impacts on the weather and climate of tropical countries. (Riehl, 1979). Thus, the trend of their frequency and intensity in the North Indian Ocean is very important for the maritime regions of South Asia(Singh etal,2000:11). Most of the severe cyclones of the North Indian Ocean are formed during November and May and strike the coasts of India and Bangladesh (Islam and Peterson, 2008). In June 2007, the Middle East was taken by a rare tropical cyclone that skirted the coasts of Oman and made landfall in Iran. The tropical Cyclone Gonu was formed in the Arabian Sea and traveled northwest towards Oman, intensifying as it tracked across the open waters. Gonu was the strongest recorded tropical cyclone in the Arabian Sea on 3rd of June in a category of 5 hurricanes on the Saffir-Simpson Hurricane Scale (Paterson, 2007). It weakened as it approached the Arabian Peninsula, though it retained the equivalent of category 1 status while very closely passing Sur and Muscat in Oman, and then declined over the Gulf of Oman to the tropical storm status before making landfall in Iran. The aim of this paper is to evaluate the climatic impacts of Gonu TC in southeast of Iran (Sistan & Baluchestan). In June 2007, during the Gonu activity from birth to destroying, some significant variations occurred in both the surface and lower and middle levels of the atmosphere of the region. Materials and Methods For the analysis of the Gonu TC mechanism and storm tracks ,the satellite images of MODIS sensor (Terra and Aqua satellites) and the Meteosat 7 satellite products from NRL(The Naval Research Laboratory) of Monterey Marine Meteorology Division have been used (NRL, 2008). Also the daily climatic data of meteorological stations of the region were analyzed. The reanalysis dataset was created through the cooperative efforts of the United States National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) to produce relatively high-resolution global analyses of atmospheric fields over a long time period (Kalnay et al, 1996). For this study, we used these data from the onset to destruction of Gonu TC. (2-9 June, 2007). For this event, surface conditions of the middle and upper atmosphere during the main event days (2, 9 June, 2007) are considered to determine the influences of the Gonu on the climate conditions of the region. The synoptic maps for anomalies of pressure, Geopotential heights, air temperature, specific humidity, vertical velocity (Omega), sea level pressure, precipitation and wind direction and velocity have been analyzed. Results and Discussion The results of the daily composite maps showed that with the increasing force of Gonu, the axis of subtropical high pressures in the lower levels of atmosphere migrated to the east, and in the mid levels they moved to the north. This replacement prepared the atmospheric condition for an intense convection and heavy precipitation. From the 7th to the 9th of June, precipitation in major weather stations of region was reported. The maximum amount of precipitation was in Nikshahr (144mm). Chabahar, Saravan, khash, Iranshahr and Zahedan have received some amounts of precipitation during the life of Gonu cyclone. The minimum pressure in the eye of cyclone is calculated to be about 898hp using the images of Metosat satellite and a dipole pattern was prevailed over the region that the max pole (+5hp) was located over Pakistan and the min pole with -4.5hp anomaly was prevailed over the southeast of Iran. The SLP in Chabahar station from 999.5hp in 6th of June increased to 1004hp in June 7th.The Geopotential height in 85hp on June 5th showed a -40m negative anomaly in the east of Oman Gulf and Makran coastline that indicated the northward migration of Subtropical High Pressure (STHP). On June 6th this anomaly increased to -60m. The surface air temperature decreased in most of the stations. In 500HP level the temperature anomaly of up to 8°c occurred and in 850hp, -8°c anomaly was calculated over the region. These anomalies caused severe condensations in 850hp and the release the latent energy in 500hp level. In Chabahar, the wind velocity increased up to double the normal average. The winds with with over 50 knots speed dominated over the northern parts of Oman Gulf and huge waves attack the coastline and the height of some waves was reported to be over 6 meters. The vertical velocity (Omega) maps in 5th of June showed maximum vertical motions over the east and southeast of Oman Gulf. In June 6th these conditions dominated over both the lower and the middle levels of atmosphere which indicated the severe convective activities. By the injection of the moist air from the sea surface to the region in June 6th, the humidity increased 30% in comparison with the normal periods and extended to north of Kerman and southern Khorasan provinces. Conclusion The results of daily composite maps showed that with the increasing force of Gonu, the axis of subtropical high pressures in the lower levels of the atmosphere migrated to the east, and in the mid levels they moved to the north. This replacement prepared the atmospheric condition for an intense convection and heavy precipitation. The maximum amount of precipitation was in Nikshahr (144mm). The omega equation maps confirm the ascending motions over the atmosphere of the region during 4–7 June. Increasing of an intense vertical motion in 500hp level indicated a huge and deep convection over the region. The temperature negative anomalies in the surface (because of the intense cloudiness) and in the 850hp level (caused by vigorous condensation of severe humid air convection) are very important. Most of the stations have shown temperature anomalies of about -10°C and in the 850hp level and also about -8°C in comparison with the normal climatology, but in the 500hp level, because of the release of water vapor latent energy, positive temperature anomalies of about 10°C have occurred. The variation of velocity and directions of the sustained wind, synchronized with the activity of Gonu over the region, caused a significant variation in winds in comparison with normal conditions. Over the past decades, the frequency of tropical cyclones in the North Indian Ocean has been registered as significant increasing trends during the months of May and June which account for maximum number of intense cyclones. Based on this trend in the future, the occurrence of such storms in the northern coastlines of Gulf of Oman are more possible.}, keywords = {Convection.,Gonu,Gulf of Oman,Sistan & Baluchestan,Tropical cyclone}, title_fa = {تحلیلی بر تأثیرات اقلیمی سیکلون حاره‌ای گونو (خرداد 1386) بر جنوب شرق ایران}, abstract_fa = {در خرداد ماه 1386 طی فعالیت گونو از تولید تا اضمحلال، برخی تغییرات معنی‌دار در سطح زمین و سطوح پایینی و میانی جوّ منطقه رخ داد. هدف این مقاله ارزیابی تأثیرات اقلیمی سیکلون حاره‌ای گونو بر نواحی جنوب شرق ایران به‌خصوص سیستان و بلوچستان است. برای این منظور داده‌های اقلیمی ایستگاه‌های هواشناسی اصلی منطقه و همچنین داده‌های آنالیز مجدد مراکز NCAR/NCEP وابسته به مرکز ملی هوا و اقیانوس‌شناسی امریکا (NOAA) مورد تحلیل قرار گرفت. تصاویر سنجنده‌های ماهواره متئوست 7 و ماهواره‌های ترا و اگوا (سنجنده مودیس) در باندهای مرئی، مادون قرمز و ترکیبی طی دوره حیات سیکلون گونو دریافت گردید و به‌منظور دستیابی به نتایج و تأیید آنها مورد تفسیر قرار گرفت. نتایج حاصل از نقشه‌های ترکیبی نشان داد که با افزایش قدرت گونو، محور مراکز پُرفشار جنب‌ حاره‌ای در سطوح پایینی جو به سمت شرق، و در سطوح میانی به سمت شمال جابه‌جا شده است. این جابه‌جایی شرایط را برای همرفت شدید و بارش سنگین مهیا ساخته است. حداکثر بارش در نیک‌شهر (144 میلی‌متر) گزارش شده است. نقشه‌های اُمگا حرکات صعودی شدید را بر فراز جوّ منطقه طی روزهای 14 تا 17 خرداد تأیید کرد. افزایش حرکات قائم شدید در سطح 500 هکتوپاسکال همرفت شدید و عمیقی را بر روی منطقه نشان داد. ناهنجاری‌های منفی درجه حرارت در سطح زمین (به دلیل ابر آلودگی شدید) و در سطح 850 هکتوپاسکال به علت چگالیدگی قوی ناشی از همرفت بسیار شدید هوای مرطوب، اهمیت فراوان دارد. بسیاری از ایستگاه‌های منطقه ناهنجاری دمایی در حدود 10- درجه سلسیوس را ثبت کرده‌اند و در سطح 850 هکتوپاسکال هم در حدود 8- درجه سلسیوس در مقایسه با شرایط نرمال اقلیمی ناهنجاری وجود داشته است؛ اما در سطح 500 هکتوپاسکال به علت آزاد شدن انرژی نهان ناشی از بخار آب، ناهنجاری‌های مثبت در حدود 10 درجه سلسیوس به وقوع پیوسته است. تغییرات در سمت و سرعت بادهای با تداوم، همزمان با فعالیت گونو بر روی منطقه باعث تغییرات معنی‌داری در آنها در مقایسه با شرایط نرمال اقلیمی گردید.}, keywords_fa = {خلیج عمان,سیستان و بلوچستان,سیکلون حاره‌ای,گونو,همرفت}, url = {https://jphgr.ut.ac.ir/article_21578.html}, eprint = {https://jphgr.ut.ac.ir/article_21578_90a1288aade5f1937402db71bff64676.pdf} } @article { author = {Omidvar, K and Kianfar, A and Asgari, Sh}, title = {Zoning the Flood-Producing Potentials of Konjancham Basin}, journal = {Physical Geography Research}, volume = {42}, number = {72}, pages = {-}, year = {2010}, publisher = {University of Tehran}, issn = {2008-630X}, eissn = {2423-7760}, doi = {}, abstract = {Introduction Geometric Characteristics of watersheds are very important in study and assessment of floods. They play the most significant role in hydrologic assessment of the missing data on watersheds. Watershed diversity in our country is a major obstacle to the correct assessment of flood forecasting in terms of climatic conditions, vegetation, soil, geology and lack of hydrometric stations. Flood is a natural phenomenon which nations adopted as an inevitable event. However, flood event, size and frequency result from several changing factors in terms of climatic, natural and geographical conditions in areas. This is why the relation between rainfall and runoff is noticeably different in every basin. Not only every basin but also every sub-basin has its unique conditions which must be independently discussed. Since at present we can’t change atmospheric elements in order to prevent these harmful phenomena, we should seek any alternative and solution on the earth and especially in watershed basins. In this regard, areas that have high potentials in creating floods should be identified. Therefore, the first step to reduce flood danger is flood managing in its origin, that is, watersheds. Certainly, we need to identify flood-producing areas within the basin because it isn’t possible to perform executive and reparatory operations across the basin due to the large extent and spread of the watersheds, and even if it isn’t studied precisely, peak debit can be intensified by changing the synchronization of peak debit in sub-basins. At present, the flood phenomenon in our country is the result of disturbing natural balance and geographical conditions (physical and morphological) in flood-producing areas rather than the incidence of heavy precipitation, which is why common rainfalls cause flowing floods. Factors like vegetation wastage due to improper knowledge of present resources management, lack of places for it in great policy makings and economical conditions dominant on this scope and overusing natural capacities of existing resources provided conditions under which occasionally we see flood-producing and its destructive effects and losing millions of tons of rich soil. Therefore, one of the main challenges in managing our country and Ilam province is to relatively reduce and control flood dangers, and one of the approaches in reducing flood damage is zoning the flood-producing potentials of watersheds. Materials and Methods In this study, we used topography maps 1:50000 of Armed Forces Geographical Organization, geological map 1:250000, vegetation Atlas, land use, area soil and the studies done in the basin level and multi-variable statistical methods of factor analysis and cluster analysis by SPSS software and Arc GIS software package. We obtained rainfall statistics from Ilam province Weather Bureau and Iran Meteorology Organization and obtained debit statistics from the Ministry of Power (Tamab). In this research, Konjancham watershed was classified into 29 sub-basins. In view of the objectives of this study, the maximum instant debit, daily rainfall, date of basin floods during the statistical period of 1995-2007 were selected. And for other indexes used in this study, at first we calculated the effective indexes in producing flood like geometric variables, physiographic, permeability and climatic variables for Konjancham watershed sub-basins by Arc GIS software. Then they were analyzed using statistical factors and cluster analysis methods by SPSS statistical software. Results and Discussion In this study, Konjancham watershed in Ilam province is divided into 29 sub-basins and the intensity of flood producing of sub-basins is classified into five classes. Considering the purposes of this study, instant peak flow rate, daily rainfall and the date of basin floods during statistical period of 1995-2007 are selected. Using Arc GIS software, we calculated 28 geometric, physiographic, permeability and climatic parameters such as area, perimeter, length and slope of the main stream, length and slope of the watershed, concentration time, form of coefficient and precipitation variables, vegetation canopy, CN, flow rate and etc.. Statistical methods of cluster and factor analysis were used to determine the flood potential in the sub-basins of Konjancham watershed and the data for 28 sub-basins variables were processed by SPSS statistical software and summarized in the form of 5 major factors (form, stream, slope, drainage and runoff) and finally, the flood producing potentials zoning map was drawn in five levels: low, moderate, relatively low, relatively high and high. In addition, qualitative variables effective in occurrence of flood have been descriptively analyzed within Konjancham river sub-basins. Conclusion The results indicate that the form factor with specific value of 9.75 is the most important factor in the studied basin flood production. Factors like stream, slope, drainage and runoff with specific values of 6.55, 3.45, 2.51 and 2.26 respectively are grouped into the next ranks in terms of priority. Then according to the factor score, the region was divided into 5 parts including high, relatively high, moderate, relatively low and low flood producing, and as a result, the zoning map of flood producing potentials was drawn in GIS for sub-basins and a descriptive analysis of qualitative variables effective on flood occurrence was done in Konjancham river basin.}, keywords = {Cluster Analysis,factor analysis,Flood producing,Konjancham Watershed,zoning}, title_fa = {پهنه‌بندی پتانسیل سیل‌خیزی حوضه آبریز کنجانچم}, abstract_fa = {ویژگی‌ هندسی آبخیزها در مطالعات و برآوردهای سیلاب بسیار مورد توجه است. این مشخصه در حوضه‌های فاقد آمار مهم‌ترین نقش را در برآوردهای هیدرولوژی دارد. تنوع آبخیزهای کشور به لحاظ شرایط اقلیمی، پوشش گیاهی، خاک و زمین‌شناسی و نبود ایستگاه‌های هیدرومتری، مسئله اساسی در عدم برآورد صحیح پیش‌بینی‌های سیلاب است. در این تحقیق، حوضه آبریز کنجانچم در استان ایلام به 29 زیرحوضه تقسیم شده و برای هر زیرحوضه 28 پارامتر ژئومتری، فیزیوگرافی، نفوذپذیری و اقلیمی ـ مانند مساحت، محیط، طول و شیب آبراهه اصلی، طول و شیب حوضه، زمان تمرکز، ضریب شکل و متغیر بارش، تاج پوشش گیاهی، CN، دبی‌ـ با استفاده از نرم‌افزار ArcGIS محاسبه شده است. برای تعیین پتانسیل سیل‌خیزی زیرحوضه‌های حوضه آبریز کنجانچم از روش‌های آماری تحلیل عاملی و تحلیل خوشه‌ای استفاده شد، به گونه‌ای که داده‌های 28 متغیر زیرحوضه‌‌ها به‌وسیله نرم‌افزار SPSS پردازش گردیدند و در قالب 5 عامل اصلی (شکل، آبراهه، شیب، زهکشی و رواناب) خلاصه‌سازی شدند. نتایج به‌دست آمده بیانگر این است که عامل شکل با مقدار ویژه 75/9 مهم‌ترین عامل در سیل‌خیزی حوضه مورد مطالعه به‌شمار می‌آید. عوامل آبراهه، شیب، زهکشی و رواناب به ترتیب با مقدار ویژه 55/6، 45/3، 51/2، 26/2 به ترتیب اولویت در رتبه‌های بعدی قرار می‌گیرند. سپس براساس امتیاز عاملی منطقه مورد مطالعه به 5 دسته سیل‌خیزی زیاد، نسبتاً زیاد، متوسط، نسبتاً کم و کم‌ تقسیم ‌گردید و سرانجام نقشه پهنه‌بندی پتانسیل سیل‌خیزی زیرحوضه‌ها در محیط GIS ترسیم شد.}, keywords_fa = {پهنه‌بندی,تحلیل خوشه‌ای,تحلیل عاملی,حوضه آبریز کنجانچم,سیل‌خیزی}, url = {https://jphgr.ut.ac.ir/article_21579.html}, eprint = {https://jphgr.ut.ac.ir/article_21579_ec570133e0f29271900f9dcd188f850e.pdf} } @article { author = {Abassi, F and Habibi Nokhandan, M and Goli Mokhtari, L and Malbousi, Sh}, title = {Climate Change Assessment over Iran in the Future Decades Using MAGICC-SCENGEN Model}, journal = {Physical Geography Research}, volume = {42}, number = {72}, pages = {-}, year = {2010}, publisher = {University of Tehran}, issn = {2008-630X}, eissn = {2423-7760}, doi = {}, abstract = {Introduction In the recent years, a CSG (Climate change Scenario Generators) model was developed and made a simple model for climate change that is called MAGICC and a scenario of climate information which organizes production that is called SCENGEN. M and SCENGEN models are divided into two main parts: parts that assess the climate change issued by the spreading circulation of green house gases (MAGICC) to organize sets of simple models. (Harvey et aL, 1997, 50) Magicc is not the GCM model, but it can simulate using GCM in several areas in the world (Wigley et al 2002, 2690). MAGICC can predict the annual average of ground temperature and mean annual sea surface temperature of spreading green house gases and CO2. This part includes the observation of climatic data and outputs of general circulation at atmospheric models that users can consider and assess in different situations. There are different couple of models that are mixed at the software Network, and users can use this network to change the concentration of CO2 and the mean temperature of ground and sea surface, to appoint climate circulation scenarios of CO2, CH4, N2O (PFC, HFC, HCFC).This model is used by IPCC in different assessment . Users can edit and update their scenarios into their models. Scenarios show base data of general circulation atmospheric model and global observation data of Europe, South Asia, America, and southern Africa. SCEGEN model has been developed in several years. Scenario of green house gases and SO2 can change by Magicc and SCENGEN and as well as the temperature of the ground and sea surface. Materials and Methods There are some limitations for modeling the climate in future decades using dynamically-developed models. Here we have used Magicc-Scengen statistical model, which uses ECHAM4 and HADCAM2 models data. In this model, Iran is divided into 9 parts and the precipitations and temperatures have been simulated for the decades of 2000, 2025 and 2075. Climate change scenarios have monthly, seasonal and yearly time scales. This model can use 16 GCM data. In this paper, calculations have been done on the basis of ECHAM4 and HADCAM2 outputs. Temperature and precipitation were analyzed during: 1986 to 2015 (2000 decade), 2011 to 2040 (2025 decade) 2036 to 2065(2050 decade), 2090 (2075 decade) and 2086 to 2115 (2100 decade) Results and Discussion mean precipitation The results of downscaling from HADCM2 data show that mean precipitation will reduce during the future decades. In contrast to the other decades, the largest decrease will happen during 2100 decade (figure 1) The largest decrease of precipitation is related to Is92D, which is about 6 percent. Precipitation will increase during the future decades in Mazandaran, Golestan, North khorasan, North of khorasan Razavi, Tehran, parts of Gillan, Ghazvin and Markazi. The largest increase in precipitation will happen in north east and east of khorasan Razavi province. We do not have a remarkable precipitation change on southern and eastern coasts of the Caspian sea. Also precipitation will decrease in southern and south-eastern provinces, parts of Sistan-O-Bluchestan, and kerman, bushehr, south Fars. The different changes of precipitation during the future decades are shown at figure 1. The results show that precipitation has increased and the highest precipitation will happen in the decade of 2100. On the basis of WKE450 and IS92E Scenarios, change in precipitation will occur at about 13.3 and 29.1 percent. The Results indicate that precipitation will decrease in the future decade in Mazandaran, Golestan, North of Khorasan, Parts of Khorasan Razavi north parts of Markazi, Tehran, parts of Gillan, Ghazvin and Markazi and the largest decrease of precipitation will happen on the southern and eastern coasts of Caspian sea, Markazi, Ghazvin, Semnan, Golestan, parts of Gillan and Mazandaran. In these provinces, precipitation will decrease about 9 to 18 percent. Precipitation will increase in sistan- O-Bluchestan, Hormozgan, Kerman, Fars, Bushehr, South- Khorasan, Yazd, Esfehan, Tehran, Kerman, Parts of Semnan, Southern parts of khorasan Razavi and Markazi, Persian Gulf plateau of Iran, and Oman sea. Certainly the highest precipitation will happen in Oman sea and Persian Gulf. The changes of precipitation with different scenarios are shown in figure 2. Mean Temperature The Whole mean temperatures were estimated and compared to the base data, the data of temperatures and the general circulation atmospheric model. (Figures 3 and 4). Mean Temperature has increased and the maximum increase will happen in 2100 decade. The results show the increase of temperature over Iran. On the other hand, we will have an increase of temperature of about 0.4 to 3 degrees in the HADCM2 model and of 5 to 4 degrees in the ECHAM4 model in the future decade; the maximum change in the temperature will happen at about 4.4 to 5.3 degrees in 2100 decade. Increases of temperature will occur in south of khorasan, Yazd, Esfehan, parts of khorasan razavi, Semnan, Tehran, Markazi, Ghazvin and Gillan, Hormozgan ,Sistan o Baluchistan, Kerman and Fars. The largest increase will occur in Fars, Isfahan, Bushehr, Mazandarn, Tehran, Yazd, Semnan , Ghazvin, Gillan and Markazi. Conclusion According to the results of the Hadcm2 model, precipitation will decrease about 2.5 percent, but in the ECHAM4 model, in the same period of time, raining will decrease about 19.8 percent. The Hadcm2 model forecasted that precipitation will increase in Mazandaran, Golestan, north of khorasan, Semnan, Tehran and parts of Gillan, but will decrease in Kerman, Hormozgan, Bushehr, south of Fars and parts of Sistan- O - Baluchestan and according to ECHAM4, precipitation will increase in these areas. This model has predicted that the temperature increases about 3 to 3.6 (2100 decade). We suggest that using the general circulation model for precipitation and its assessment during the future decade over Iran is necessary.}, keywords = {climate change,General Circulation Mode ECHAM4,HadCM2,Iran,Magicc-Scengen}, title_fa = {ارزیابی تأثیر تغییر اقلیم بر دما و بارش ایران در دهه‌های آینده با کمک مدل MAGICC-SCENGEN}, abstract_fa = {در این مقاله شرایط اقلیم ایران در دهه‌های 2000، 2025، 2050، 2075 و 2100 با استفاده از خروجی دو مدل گردش عمومی جو HadCM2 و ECHAM4 و با در نظر گیری 18 سناریوی انتشار IPCC، مدل‌سازی شده است. از مدل MAGICC-SCENGEN برای ریزمقیاس‌نمایی داده‌های با قدرت تفکیک کم خروجی مدل‌های گردش عمومی استفاده شد. در این تحقیق به بررسی و مقایسه نتایج دو مدل HadCM2 و ECHAM4 پرداخته شده است. بر این اساس، نتایج مدل HadCM2 حاکی از کاهش بارش‌های ایران تا دهه 2100 به میزان 5/2 درصد است، در حالی‌که برای دوره مشابه در مدل ECHAM4 بارش‌های کشورمان به میزان 8/19 درصد افزایش یافته است. تحلیل منطقه‌ای نتایج مدل HadCM2 نشان می‌دهد که در دهه‌های آینده استان‌های مازندران، گلستان، خراسان شمالی، شمال خراسان رضوی و سمنان، تهران و بخش‌هایی از گیلان و قزوین با افزایش بارش مواجه خواهد شد، در حالی‌که مدل ECHAM4 برای مناطق مذکور کاهش بارش را پیش‌بینی کرده است. همچنین مدل HadCM2 برای نواحی جنوب شرق کشورمان شامل استان‌های هرمزگان، کرمان، بوشهر، جنوب فارس و بخش‌هایی از سیستان و بلوچستان کاهش بارش را پیش‌بینی کرده است، اما در مدل ECHAM4 مناطق مذکور در دوره مشابه با افزایش بارش مواجه خواهند بود. براساس بررسی‌های به عمل آمده، نتایج هر دو مدل بیانگر افزایش دمای تمامی استان‌های کشورمان در دهه‌های آینده است. این دو مدل تا دهه 2100 به‌طور میانگین افزایش دمای 3 تا 6/3 درجه سانتیگراد را برای کشورمان پیش‌بینی می‌کنند، که در این دو مدل توزیع مکانی افزایش دما با هم مطابقت دارند.}, keywords_fa = {ایران.,تغییر اقلیم,مدل گردش عمومی جو HadCM2 و ECHAM4}, url = {https://jphgr.ut.ac.ir/article_21580.html}, eprint = {https://jphgr.ut.ac.ir/article_21580_72ea64e8680c5a1e05a22b7e86aad6ab.pdf} } @article { author = {Ranjbar SaadatAbadi, A and Mohammadian, L}, title = {Study of Mean Pressure Patterns Based on Different Levels of Occurrence of CO Pollutant in Tehran for the Summer and Autumn Seasons}, journal = {Physical Geography Research}, volume = {42}, number = {72}, pages = {-}, year = {2010}, publisher = {University of Tehran}, issn = {2008-630X}, eissn = {2423-7760}, doi = {}, abstract = {Introduction Tehran is one of the growing cities of the world with special features; Alborz Mountains range in the north of the city and arid region in the south. It has rapidly grown in the last decades. It is also situated in a basin area, partially surrounded by mountain ranges which make it prone to acute severe air pollution episodes. Air pollution in large cities due to the increase of population growth by increasing the industrialization progress, has created problems for many residents. Tehran is one of the polluted cities in the world. Very high traffic, high energy consumption and complicated topographic and atmospheric stable systems have led Tehran to be considered as one of the world's polluted cities. The surface wind field is important for pollution dispersion and cyclonic conditions, producing moderate to strong westerly flows, are most effective in producing non-severe pollution conditions as dispersion and transport of pollutants. Vertical temperature gradients play an important role in the vertical distribution of pollutants. An inversion acts to limit the vertical mixing of pollutants, which allows concentrations to happen. Nocturnal inversions trap emissions released during overnight hours close to the ground. This reduces the possibility of pollutants being diffused vertically through suppression of the atmospheric boundary layer mixing height. Materials and Methods In the present study, in order to determine mean pressure patterns based on CO concentration levels of pollutants, initially based on data PSI of Tehran Air Quality Control Company of Tehran Municipality is taken. Gridded sea level pressure (SLP) and 500-hpa geopotential height data from the National Center for Environmental Prediction-National Center for Atmospheric (NCEP-NCAR) 6-year Reanalysis data were used to the synoptic classifications. These data analyzed at 00 UTC were prepared for the 10 pressure patterns based on the levels of carbon monoxide pollutant in Tehran (Table 3). Daily averages for each group of summer and autumn seasons from 2001 to 2006 were obtained for a large region (10°N-60°N, 0°E-80°E). The PSI data that are available since 1999 show that during 9 years (1999-2007), there have been 883 days of unhealthy air quality conditions in Tehran and it has been very unhealthy (Table 1). In the 6-year statistical period (2001-2006) a greater number of unhealthy days were selected. Considering that the unhealthiest days in Tehran were usually in the months of summer and fall, reportedly nearly 647 unhealthy days have occurred during 6 years (Table 2). Results and Discussion According to the featured synoptic patterns ruling on the summer and autumn months in Tehran, these months can provide the most potential air pollution. The results indicate that the mean pressure patterns are as follows: A –Mean Pressure patterns for summer settlement with the following characteristics reduce potential air pollution in Tehran (air quality index in clean and healthy condition is placed): 1 – Elongate east toward Azorse high pressure, pressure systems strengthen northern Caspian Sea, expanding ridge of high pressure on the south and southwest of the Caspian Sea area and southern Alborz 2 -The strong pressure gradient in the southwestern areas of the Caspian Sea and the west of Tehran 3 – Zonal flow in mid troposphere with strong contour gradient over the area of study B - Mean Pressure patterns for summer settlement with the following characteristics increase the potential air pollution in Tehran (air quality index in unhealthy and very unhealthy situation is placed): 1 - limited expansion of the eastward Azorse high pressure weaken the high pressure system on the Caspian Sea and decrease the pressure gradient in the southwestern Caspian Sea and over the studied area 2 - Strengthening and expansion of the thermal low pressure system over north east of Iran, east and south east of the Caspian Sea 3 – Strengthening and expansion of the deep ridge of subtropical heights in the middle atmosphere from the south to the north of the Caspian Sea and very unhealthy conditions in the North Aral lake C - Mean pressure patterns for fall settlement with the following characteristics reduce potential air pollution in Tehran (air quality index in clean and healthy condition is placed): 1 – elongate to westward the Siberian high pressure 2 – Strengthening of the ridge of high pressure with the strong pressure gradient in the southwest of the Caspian area and northern strip of Iran 3 - Prevailing the strong zonal flow or passing trough in the mid troposphere with severe contour gradient over the area under study D - Mean Pressure patterns for fall settlement with the following characteristics increase the potential air pollution in Tehran (air quality index in unhealthy and very unhealthy situation is placed): 1 – weakening of the ridge of high pressure system over the Caspian Sea and extensively decrease of the pressure gradient on the studied area and the Caspian Sea area 2 – prevailing thermal low pressure system in the northeast of Iran and also southeast and east of the Caspian Sea 3 – strengthening and expansion of the ridge in the middle troposphere from the southwest of Iran to the east of the Caspian sea and Tehran area located on the east of ridge axis where convergence upper flow is generally located Conclusion The summer seasonal synoptic patterns compared with the fall seasonal synoptic patterns for each group of Table 3 show that in both seasons synoptic patterns are associated with unhealthy conditions and severe pollution episodes in Tehran and have similar characteristics that may not be quite equal. The most important features of these similarities, are creating the thermal low pressure system in the south-east of the Caspian Sea and expansion of the ridge of high pressure from the south west of the Caspian Sea to some parts of the centre of Iran and southern Alborz mountains that are associated with deep ridge in the mid troposphere on these regions. The high pressure system is weakened on the north Caspian Sea and to strengthen and expand the thermal low pressure over the northeastern of Iran, southeastern and eastern parts of the Caspian Sea and reduced pressure gradient is also accompanied. Also in the mid troposphere, Strengthening and expansion ridge on the Tehran area and higher geographical latitudes provided suitable conditions for the occurrence of severe pollution episodes in Tehran. In both seasons (summer and fall), if high pressure system strengthens on the Caspian sea and pressure gradient increases in the southwest of the Caspian sea and also with these meteorological conditions coupled with zonal flow associated with strong contour gradients in mid troposphere, the potential of air pollution in Tehran reduces.}, keywords = {Air pollution,CO pollutant concentration,Mean synoptic patterns,Tehran.}, title_fa = {مطالعه میانگین الگوهای همدیدی براساس رخداد غلظت‌های مختلف آلاینده CO در فصول تابستان و پاییز در تهران}, abstract_fa = {تهران یکی از شهرهای آلوده جهان است. تردد بسیار زیاد خودرو در کلان‌شهر تهران، همراه با وجود کارخانجات متعدد و موقعیت خاص جغرافیایی‌ آن، سبب شده است که آلودگی هوا از چالش‌های جدی زیست‌محیطی و شهرنشینی در تهران محسوب شود. مهم‌ترین آلاینده گازی‌شکل در تهران، گاز خطرناک منواکسید کربن (CO) است. در این مقاله، ابتدا غلظت آلاینده گاز CO طی دوره آماری 2006-2001، برای ماه‌های تابستان و پاییز به پنج گروه مختلف طبقه‌بندی شد. سپس با استفاده از داده‌های روزانه تحلیل مجدد مرکز محیطی (NCEP) در ساعت 00UTC و به‌صورت روزانه برای شش‌ماه از سال، میدان‌های فشار سطح دریا و ارتفاع ژئوپتانسیل 500 میلی‌باری در نقاط شبکه‌ای برای هر گروه تهیه گردید. آن‌گاه نقشه‌های میانگین هر یک از پنج گروه مورد بررسی قرار گرفت. نتایج حاصل از بررسی این الگوها نشان دادند که میانگین الگوهای همدیدی در زمانی که شاخص استاندارد آلودگی هوای تهران در شرایط پاک و سالم است، تفاوت عمده‌ای با شرایط ناسالم و بسیار ناسالم دارد. استقرار سامانه پرفشار بر روی خزر، عبور ناوه‌ها و یا استقرار جریان‌های مداری تراز میانی جو سبب کاهش آلاینده‌های هوای تهران می‌گردد، در حالی‌که استقرار کم‌فشار حرارتی در بخش‌های جنوب شرقی دریای خزر و زبانه پرفشار در جنوب رشته کوه البرز همراه با تقویت پشته ارتفاعی تراز میانی جو شرایط لازم را برای افزایش پتانسیل آلودگی هوای تهران فراهم می‌آورد. این شرایط برای الگوهای تابستانی و پاییزی در حالت کلی مشابه است، هرچند که الگوهای همدیدی روی ایران در تابستان و پاییز تفاوت‌های اساسی دارند.}, keywords_fa = {آلودگی هوا,تهران,غلظت آلاینده CO,میانگین الگوهای هواشناسی همدیدی}, url = {https://jphgr.ut.ac.ir/article_21581.html}, eprint = {https://jphgr.ut.ac.ir/article_21581_548034fed37782aa40e8fdf71817a3f2.pdf} } @article { author = {Salahi, B}, title = {Statistical and Synoptic Analysis of Characteristics of Thunderstorms in Ardabil Province}, journal = {Physical Geography Research}, volume = {42}, number = {72}, pages = {-}, year = {2010}, publisher = {University of Tehran}, issn = {2008-630X}, eissn = {2423-7760}, doi = {}, abstract = {Introduction Thunderstorms are one of the most important natural hazards which cause human annihilations every year in addition to destroying of many agricultural productions throughout the world. Recognizing the synoptic conditions of the creation of thunderstorms can be useful to predict the occurring times and to take the necessary actions when confronting this phenomenon. Since thunderstorms have occurred in the province of Ardabil especially in the spring & summer seasons, paying attention to them seems important. Materials and methods In this research, we have tried to use the data from the synoptic stations of thunderstorms occurrence days of Ardabil, Meshkin-Shahr, khalkhal & Pars-Abad with the statistics arrangement of 2, 11, 19, 21 years. After making sure of the correctness of the used data, analyzing the characteristics of the data statistics & determining the kinds of seasonal and monthly statistical distribution of the days of thunderstorms is done. In addition to statistical analysis, we used the trend of time series (trend line or order of 6 polynomials) in order to determine the time fluctuations & study the phenomenon. Monthly classification of the days along with thunderstorms is also done by multivariate method and cluster analysis method. For vividness and explanation of thunderstorms and showers, the condition of sea level pressure, 500 geopotential heights and the columnar perceptible water of 26 May 1985 is analyzed as a sample. As this day has involved the occurrence frequency of thunderstorms among others, it has been selected as the representative day. Results and Discussion The results indicate that in the synoptic stations of Ardabil, Meshkin-Shahr and khalkhal, the frequency occurrence of thunderstorms belongs to the month of May and to June in the station of Pars-Abad. In the stations of Ardabil, Pars Abad & Meshkin-Shahr, the least coefficient of variance belongs to the month of May and to April in the station of khalkhal. In the whole seasons and months, the thunderstorms skewness is positive, but the kurtosis of thunderstorms is different in the stations considered. The standard derivation of warm months is more than the cold ones. Monthly thunderstorms dendrogram in the investigated stations indicated that these storms form 3 clusters in the whole stations. Time fluctuations models and trend line or order of 6 polynomial thunderstorms of studied stations in the spring season and once a year showed that in the stations of Ardabil, khalkhal and Meshkin-Shahr, the thunderstorms occurrence has a rising trend. This trend is reduced in Pars-Abad station. The representative of thunderstorms occurrence in the investigated annual and seasonal limits showed that the most thunderstorms occurrence frequency, is in the spring & summer seasons. The situation of the spring thunderstorms occurrence from the characteristics of the statistics is more similar to the annual situation. This is of high significance for the occurrence of thunderstorms in this reason. The amount of coefficient of variance of thunderstorms occurrence indicates more constancy and less fluctuations of thunderstorms occurrence in springtime rather than in the other seasons. The correlation of good process of trend line and order of 6 polynomials of thunderstorms in spring & once a year indicates that the spring season exploits more than the other seasons. The process of the rising of the line of thunderstorms occurrence in summer is stronger than in the autumn. The accounted coefficient of correlation between spring & summer thunderstorms occurrence frequency has a close correlation with the annual degree. From the viewpoint of seasonal frequency, the good correlation between spring and summer, and spring and autumn is also observed here. Conclusion The range of the frequency of the accordance of thunderstorm occurrence in Ardabil synoptic station with probability distribution of 3- parameter weibull is the indication of thunderstorms parameter of this station with probability distribution of 3- parameter weibull in 95% confidence levels for the season of spring. Consideration of synoptic maps of sea level pressure, 500 geopotential and perceptible water of the representative day of May 26, 1985, showed that on this day, the condition of the sea level and upper atmosphere levels are suitable for the occurrence of the phenomenon of thunderstorms; as on the sea level, the Isobaric patterns show the suitable conditions for transmitting of the moisture of Caspian Sea to Ardabil province. In 500 mb geopotential level also, the arrangement of upper divergences of trough settled in east European & south of Turkey causes the creation of instable conditions for the creation or forming of thunderstorms on this day. Regarding the occurrence of thunderstorms in west north of Iran, especially in the province of Ardabil, it is necessary to have & perform the necessary schedules for confronting this phenomenon. In order to do so, it is necessary to have suitable arrangements & programs for future. Probably the assurance of agricultural & animal husbandry productions can be one of the useful ways.}, keywords = {Ardabil Province,Cluster Analysis,Linear and polynomial trend,synoptic analysis,Thunderstorms}, title_fa = {بررسی ویژگی‌های آماری و همدیدی طوفان‌های تندری استان اردبیل}, abstract_fa = {طوفان‌های تندری از مهم‌ترین بلایای طبیعی‌اند که همه‌ساله علاوه بر نابود کردن مقدار زیادی از محصولات کشاورزی، سبب تلفات انسانی زیادی در سراسر دنیا می‌شوند. در این مقاله، از داده‌های روزهای وقوع طوفان‌های تندری ایستگاه‌های سینوپتیک اردبیل، مشکین‌شهر، خلخال و پارس‌آباد ـ که به ترتیب دارای آمار 29، 11، 19 و 21 ساله بودند ـ استفاده شده است. پس از اطمینان از صحت داده‌های مورد استفاده، اقدام به تجزیه و تحلیل ویژگی‌های آماری داده‌ها و تعیین نوع توزیع آماری ماهانه و فصلی روزهای دارای طوفان‌های تندری گردید. از روش تجزیه مؤلفه روند سری‌های زمانی (روند خطی یا پلی‌نومیال درجه شش) برای تبیین نوسان‌های زمانی طوفان‌های تندری استفاده شده است. برای تبیین و توجیه همدیدی رگبارها و طوفان‌های تندری، شرایط هم‌فشاری سطح زمین، هم‌ارتفاع سطح 500 هکتوپاسکال و ستون آب قابل بارش روز 26 مه 1985 به عنوان نمونه، مورد تجزیه و تحلیل قرار گرفته است. نتایج بررسی‌ها نشان دادند که در ایستگاه‌های سینوپتیک اردبیل، مشکین‌شهر و خلخال، بیشترین فراوانی وقوع طوفان‌های تندری متعلق به ماه مه و در ایستگاه سینوپتیک پارس‌آباد، متعلق به ماه ژوئن است. درخت خوشه‌بندی طوفان‌های تندری ماهانه در ایستگاه‌های مورد مطالعه، نشان داد که این طوفان‌ها در تمامی ایستگاه‌ها سه خوشه مشابه را تشکیل می‌دهند. مدل‌های نوسانی زمانی و روند خطی و پلی‌نومیال درجه شش طوفان‌های تندری فصل بهار و سالانه نشان دادند که در ایستگاه‌های اردبیل، خلخال و مشکین‌شهر، وقوع طوفان‌های تندری دارای روندی افزایشی است و در ایستگاه پارس‌آباد روندی کاهشی دارد. همخوانی نسبتاً خوب روند خطی و پلی‌نومیال درجه شش بهاری و سالانه وقوع طوفان‌های تندری، مبین بیشتر بودن سهم فصل بهار از طوفان‌های تندری نسبت به میزان سالانه است. فراوانی وقوع طوفان‌های تندری ایستگاه سینوپتیک اردبیل با تابع توزیع احتمال ویبول سه پارامتری در سطح اطمینان 95 درصد تطابق دارد. بررسی نقشه‌های همدیدی روز نماینده نشان دادند که در این روز، شرایط سطح زمین و سطوح بالای اتمسفر برای وقوع پدیده طوفان تندری مناسب است.}, keywords_fa = {استان اردبیل.,تحلیل خوشه‌ای,تحلیل همدیدی,روند خطی و پلی‌نومیال,طوفان‌های تندری}, url = {https://jphgr.ut.ac.ir/article_21582.html}, eprint = {https://jphgr.ut.ac.ir/article_21582_e4a5dc90865059cf1e47f9dc9a4275dc.pdf} }