per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
1
18
10.22059/jphgr.2014.50616
50616
Full length article
ارزیابی اثر ترکیب کانیشناسی واحدهای سنگی تودۀ نفوذی الوند بر مقاومت رخنمونها در برابر هوازدگی و فرسایش
An Assessment about the Effect of Mineralogical Composition of Alvand Pluton Rock Units on Outcrops Resistance
against Weathering and Erosion
حسین بختیاری
moghimi_ir@yahoo.com
1
ابراهیم مقیمی
emoghimi@ut.ac.ir
2
محمدرضا ثروتی
rezasarvati@yahoo.com
3
دانشجوی دکتری ژئومورفولوژی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران، گروه جغرافیای طبیعی
استاد گروه جغرافیای طبیعی، دانشکدۀ جغرافیا، دانشگاه تهران
دانشیار دانشکدۀ علوم زمین، دانشگاه شهید بهشتی
تودۀ نفوذی الوند، یکی از بزرگترین تودههای نفوذی در کمربند دگرگونی سنندج ـ سیرجان است. این مقاله به ارزیابی اثر ترکیب کانیشناسی واحدهای سنگی بر مقاومت آنها در برابر هوازدگی و فرسایش پرداخته است. این کار با ارائۀ یک روش پیشنهادی، یعنی استفاده از نمودار QAPF انجام گرفته است. در این روش با توجه به قرارگیری کانیهای کوارتز و فلدسپاتوئیدها در دو قطب مخالف نمودار و نقش تعیینکنندۀ آنها در مقاومت رخنمونها، ابتدا سطح نمودار QAPF به ده محدوده تقسیم و ارزشگذاری شد که ارزش هر محدوده بهصورت نسبی، معرف تأثیر ترکیب کانیشناسی بر مقاومت سنگهای داخل آن در برابر هوازدگی و فرسایش است. سپس درجه مقاومت رخنمون واحدهای سنگی توده نفوذی الوند تعیین و ضمن طبقهبندی در چهار گروه، نقشۀ پهنهبندی مربوطه تهیه شده است. با تعیین درجه مقاومت کانیشناسی رخنمون واحدهای سنگی، میتوان نقش ترکیب کانیشناسی را بهصورت یک متغیر کمّی در تحلیلهای ژئومورفولوژیکی برای تبیین فرم و فرآیندهای حاکم بر ناهمواریها مورد توجه قرار داد.
IntroductionIn general, strength of rocky outcrops is associated with two factors, feature lithology thatincludes mineralogical composition, texture and rock Structure and environmental factors that isthe area stones are located in (Hafezy moghadas, 2011, 229 after Ulusay, 1994). Themineralogical composition determines sensitivity of rocks against physical, chemical andbiochemical attacks (Mahmoodi, 2010). Rocks because of containing different minerals showvarious stability against the degradation factors (Nikoodel, 2011). This is the first time researchto use classification system of in geology for naming rocks to determine the degree of resistanceof the stones against weathering and erosion.MethodologyThe Alvand Pluton is one of the largest intrusive masses in Sanandaj- Sirjan metamorphic zone(Sepahi, 2008).The exposed area of this mass are approximately 362.92 square kilometers(excluding Quaternary deposits). Alvand Plutonism was started from middle Cretaceous andcontinued till early Tertiary (Paleocene) (Sepahi & Moeen vaziry, 2000).Alvand pulotonic rocks have been marked on the geological map (Tuyserkan and∗E-mail: moghimi_ir@yahoo.com Tel: +98 91243927902 Physical Geography Research Quarterly, 46 (1), Spring 2014Hamadan1:100,000 scale) in 100 limited areas with 8 different symbols. That usually has lightgrey to white color and fine to coarse grains (2-5mm in diameter). About 9 square kilometers ofcordierite andalousites and cordierite hornfelses (metamorphic rocks) in the 23 areas withdifferent extent are over the surface of porphyroid granite which mostly matches top heights(especially Heights Gavboreh). This shows diapirism in placement of the mass.In this research, library and field observation have been used as the methods of datacollection, (sampling and observation) and the research method has been descriptive andanalytical. For evaluating the effect of mineralogical composition of the Alvand pluton rock onoutcrop resistance some steps have been taken. In next step, the classification was proposed bythe International Union of Geological Sciences (IUGS), and diagram (QAPF)1 associated withit, was selectedwith range diagram, according to the mineralogical composition. Numericalvalues are determined for the degree of outcrop resistance of each area against weathering anderosion. In order to determine the degree of Alvand pulotonic outcrops resistance we havespecified surface of QAPF diagram. The resistance specified as numerical value is ranged from1 to 10 classes started from foidolites with least degree of resistance and with ratio of decreasingF and P and increasing A and Q. It is the most sensitive igneous rocks against chemicalweathering considering mineralogical composition. Thus, quartz-rich granitic-rocks are in 9areas and finally quartzolit (silexite) which is the most resistant intrusive igneous rock againstweathering.To test the proposed method, 10 types of Alvand pulotonic rocks which gathered by Zarianet al., 1972 with Modal analysis method was studied and selected by using diagram QAPF forresistance range. In addition, finding equivalent name in classification system of IUGS, thedegree of the resistance against weathering and destruction in terms of mineralogicalcomposition is given in.Results and DiscussionNaming Alvand plutonic rock units on geological maps is based on IUGS classification. Thus,based on provided method, relative strength of the rock outcrop in terms of the effects ofmineralogical composition on the resistance against weathering and erosion have been identifiedand presented in Table 1. Specific degree of resistance for Alvand plutonic rock units arepresented on Table 4. Rock units of this mass can be classified in four groups, the least ofresistance is related to Olivine gabbro outcrops with 2 degree which cover 14.8% of the massarea.The most resistant rock outcrops are the unit pegmatitic granite, pegmatic- aplite granite,tourmalin granite and granite bearing garnet with a resistance degree of 8. Among other unitsthis later covers just 3.15% of surface area. Degree resistance was determined for different rockunits in Alvand pluton and it shows 6 degree resistance differences between them.Thisdifference can be affected by weathering and differential erosion between different units.Average weighted degree rock units outcrop resistance of Alvand in terms of mineralogical1. Q = Quartz, A= Alkali Feldspar, F= Feld spathoids, P= Plagioclase.Physical Geography Research Quarterly, 46 (1), Spring 2014 3composition is obtained for total mass about 6.59. It shows resistence of the mineralogicalcomposition of the outcrops and the results can be found in relation to high percentage of quartzand alkali feldaspar, and the approximate homogeneity in mineralogical composition of the rockmass. In order to determine the applicability of the results obtained from the proposed method ingeomorphological and hydrological analyses, the Digital Elevation Model (DEM) of Alvandpluton was provided.ConclusionIn this paper, the effect of mineralogical composition of Alvand plutonic outcrops against theweathering and erosion with the numeric range 1-10 and using QAPF diagrams have beendetermined. In this method, Surface of QAPF diagram between Q and F has been divided intoten areas with in numerical range of 1-10. The range of values represents the effect of themineralogical composition on degree of resistance of outcrops of rock units. According todegree resistance designated for Alvand pluton rock units in terms of the effects, this mass canbe classified in four groups.In this classification the least resistance is related to Olivine gabbrooutcrops with degree resistance of 2 and the most resistant rock outcrops with resistance degreeof 8 are the units including pegmatitic granite pegmatitic– aplite granite, tourmaline granite, andgranite bearing granite. According to average weighted degree granitic outcrop resistance ofAlvand in terms of mineralogical composition, the degree is obtained 6.59for total mass..Determining resistence of Alvand rock units in quantitative mineralogical composition and theproperties of texture and structure characteristics can be used for geomorphological analysis andexplanation of predominant form over Alvand mass.
https://jphgr.ut.ac.ir/article_50616_e2e0857cc2511edcbd273ba52b40b71e.pdf
تودۀ نفوذی الوند
رخنمون
ترکیب کانیشناسی
درجۀ مقاومت
نمودار QAPF
Alvand Ploton
Mineralogical Composition
Outcrops
QAPF Diagram
Resistance Degree
per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
19
42
10.22059/jphgr.2014.50617
50617
Full length article
طبقهبندی الگوهای سینوپتیکی بارشزا در سواحل دریای خزر
Synoptic Classification Models of Precipitation in the Coastel Areas of the Caspian Sea
ام السلمه بابایی فینی
f_babaee@pnu.ac.ir
1
ابراهیم فتاحی
ebfat2002@yahoo.com
2
استادیار گروه جغرافیا، دانشگاه پیام نور
دانشیار پژوهشکدۀ هواشناسی
با توجه به ارتباط تنگاتنگ الگوهای گردش جوی و عناصر اقلیمی، میتوان پدیدههای فرین آبوهوایی، مانند سیل و خشکسالی و دورههای خشک و تر را به تغییرات الگوهای گردش جوی نسبت داد. برای طبقهبندی الگوهای سینوپتیکی بارشزا، دادههای گردآوریشدۀ میانگین روزانۀ تراز 500 هکتوپاسکال و فشار سطح دریا طی دورۀ آماری 2008-1950 مورد استفاده قرار گرفت و برای ارزیابی نقشۀ الگوهای بارش، دادههای مجموع بارش روزانه طی دورۀ آماری 2008-1960 جمعآوری شدند. با استفاده از روش تحلیل مؤلفههای اصلی، همۀ روزهای مورد مطالعه را به هجده گروه تقسیمبندی شدند و پس از آن، نقشههای ترکیبی تراز 500 هکتوپاسکال و فشار سطح دریا برای هر یک از تیپهای هوا تهیه شد. برای ارزیابی رابطۀ الگوهای گردش جوی بر احتمال وقوع بارش و شدت بارش، شاخص PI مورد استفاده قرار گرفت. نتایج پژوهش حاضر نشان داد، الگوهای گردش جوی 4CP، 5CP، 12CP، 1CP و 15CP، جزء الگوهای بارشزای شدید و فراگیر و الگوهای گردش جوی 7CP، 13CP، 16CP، 17CP و 18CP، جزء الگوهای بارشزای ملایم هستند. از نظر توزیع فراونی سالانه، الگوهای گردش جوی 3 CP، 5 CP، 13CP و 15CP در سرتاسر سال و الگوهای گردش جوی 2CP، 6CP و 10CP در فصل تابستان، فعالیت دارند.
IntroductionAtmospheric circulation patterns play the main role in the natural phenomenon occurring on theearth, especially in temperate regions. Some atmospheric circulation patterns cause wet periodsand others cause low water and dried periods. Thus, because the annual occurrence of droughtand wet events result from the general circulation of the atmosphere, recognizing atmosphericcirculation patterns are explained, to some extent, for the possibility of evaluating thesephenomena before occurance. Studies show that the floods and droughts phenomenan areinfluenced by atmospheric circulation patterns. Given the close relationship between thepatterns and climatic elements, we can also attribute the extreme climatic events, such as floodsand droughts, and dried and wet periods, to changes in atmospheric circulation patterns. In thisstudy, from average daily data balance of 500 and the sea level pressure over the period 1960 to2008 at two degrees intersection of the reconstructed data setshave been used. The selectedrange covers all systems affecting the area under study during the year. This range consists of408 cells from 20 to 60 degrees in north latitude and 10 to 70 degrees in east longitude. Totaldaily rainfall data from selected synoptic stations over the statistical period 1960-2008 wereused to assess the role of the patterns in rainfall. Many climate scientists dealing with variableswith different scale or large volumes of data employ reduction variable and data strategy byprincipal component analysis (PCA), (Gadyial, S. and R. N. Lyengar 1980, Kalkstein. S. et al.1998).∗E-mail: F_babaee@pnu.ac.ir Tel: +98 9123180576Physical Geography Research Quarterly, 46 (1), Spring 2014 5MethodologyFactor analysis is a statistical technique that establishs a especial relationship among a largenumber of variables that are seemingly unrelated. It is under a hypothetical model and gathersall the variables in the similar groups. This method retains significant and main components inthe same groups and reduce the variables. One of the results of factor analysis is to reduce datadimension. Computational steps of the main component analysis is as follows:a) The data and variables Selection. b) The second stage of a data matrix p × n formationwhere n is the number of days and p is the number of variables. In the third stage since theselected meteorological variables of the unit are different (For example, C, hPa, meters persecond, and so on), a correlation matrix was used as input for the main component analysis.Data correlation matrix are calculated according to the following formula. The fourth step isused to determine the number of factors by Catel test. Loadings matrix was calculated in thefifth stage. Loadings show the relationship between the factors and the primary variables.The relationship between atmospheric circulation patterns and rainfallTo evaluate the relationship between atmospheric circulation patterns and rainfall, the followingindex is applied. This index defines the conditional probability of rainfall occurnece and rainfallintensity in a circulation pattern. The index defines a measure of the relative share of the patternrainfall in total. Where ni is the number of days with i patterns and Ri is the total rainfall duringthat days and n is the number of days in the period of the study. If PI<1.Or even much smaller than the unit, the weather or type pattern i does not greatly affect thearea rainfall. Thus, an increase in the frequency of occurrence of such a pattern, reduces rainfalland subsequently, causes drought in a region. If the PI in the statistical method is greater thanthe unit, then chance of rain (probability of precipitation) also increase and wet periods will beprevailed. For example, precipitation takes place when weather is wet and there is an acsendingfactor, these conditions are provided by atmospheric circulation patterns.Results and DiscussionIn this study, using PCA and clustering, eighteen circulation patterns according to the sea levelpressure and 500 hPa level atmospheric condition have been identified over the study area. Theresults of this study show that there are significant differences in the arrangement of patterns,the weather type frequency and the way they move towards the study region. The PI index is aappropriate criterion to evaluate the Conditional probability of rainfall and rainfall intensity. Ifthe PI index calculated for a wheather type much smaller than unit, wheather type does not playa role in precipitation of that station or region. Therefore, an increase in the frequency ofoccurrence of such a pattern in a period reduces rainfall and makes the drought events in thatregion.ConclusionDue to the PI index and the annual frequency distribution of atmospheric circulation patterns,the results can be summarized as follows. Atmospheric circulation patterns of CP1, CP4, CP5,6 Physical Geography Research Quarterly, 46 (1), Spring 2014CP12, and CP15 are part of the patterns leading to heavy and pervasive precipitation.Atmospheric circulation patterns of CP7, CP13, CP16, CP17, and CP18 are part of the patternsleading to moderate precipitation. Atmospheric circulation patterns of CP2, CP8, CP9, CP10,and CP11 are part of the patterns leading to drought, Atmospheric circulation patterns of CP3,CP6, and CP14 are part of the patterns leading to drought. In terms of the annual frequencydistribution, atmospheric circulation patterns of CP3, CP5, CP13, and CP15 are active in allseasons of the year, atmospheric circulation patterns of CP2, CP6, and CP10 are active insummer, atmospheric circulation patterns of CP1, CP8, CP9, CP11, CP12, CP14, CP16, CP17,and CP18 in winter, spring and fall and atmospheric circulation patterns of CP7 is active in thespring and fall.
https://jphgr.ut.ac.ir/article_50617_878a7cd6704adde64b7c439470558059.pdf
الگوهای گردش جوی
تحلیل مؤلفههای اصلی
خوشهبندی
سواحل جنوبی دریای خزر
شاخص PI
atmospheric circulation patterns
Clustering
North Caspian Sea
PI Index
Principal component analysis
per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
43
58
10.22059/jphgr.2014.50618
50618
Full length article
شواهد رسوبی تغییرات اقلیمی در دریاچۀ زریبار طی دورۀ هولوسن
Sedimentary Evidence of Climate Changes in Holocene, Zeribar Lake
مهران مقصودی
maghsoud@ut.ac.ir
1
منصور جعفربیگلو
mjbeglou@ut.ac.ir
2
امید رحیمی
omidrahimi@ut.ac.ir
3
دانشیار گروه جغرافیای طبیعی، دانشکدۀ جغرافیا، دانشگاه تهران
دانشیار گروه جغرافیای طبیعی، دانشکدۀ جغرافیا، دانشگاه تهران
دانشجوی دکتری جغرافیای طبیعی، دانشگاه محقق اردبیلی
مغزۀ ٦٨٨ سانتیمتری بهدستآمده از طریق چاهپیمایی و استفاده از مغزهگیر پیتکورر روسیه از دریاچۀ زریبار، واقع در استان کردستان، مورد تجزیهوتحلیلهای رسوبشناسی، شامل دانهبندی قرار گرفت. تعداد سه نمونه در مؤسسۀ تحلیل شتابندۀ ال. تی. دی (IAA) ژاپن، بهروش رادیوکربن ١٤ (AMS) تعیین سن شد. نتایج بهدستآمده از مطالعات و تحلیل دادهها، شرایط آبوهوایی گرم و مرطوب، افزایشِ بارشهای بهاری و میزان رطوبت قابل دسترس، افزایشِ سطح و عمق آب دریاچه، همراه با شرایط آب کاملاً شیرین را در٦٨٧۰ تا ٨٩۵۰ و ۳١٧۰ تا ۵۵۰۰ سال قبل نشان داد. همچنین حاکمیت آبوهوایی گرموخشک، کاهش در میزان بارش و رطوبت قابل دسترس، وقوع خشکسالی، پایینرفتگی سطح آب دریاچه و کاهش عمق آن طی۵۵۰۰ تا٦٨٧۰ و ١۳۰۰ تا ۳١٧۰ سال قبل و وجود تغییرات نامنظم در سطح آب دریاچه در اواخر هولوسن در ١۳۰۰تا ۳١٧۰ سال قبل، در نتیجۀ تغییرات بارشی، سرریزهای اتفاقی دریاچه و فعالیتهای انسانی است. همچنین میزان نرخ متوسط رسوبگذاری در دریاچه، طی دورۀ هولوسن برابر با ٩۵/0 میلیمتر در سال محاسبه شد و حاکی از نرخ رسوبگذاری ملایم در طول دورۀ هولوسن است.
IntroductionLakes are very interesting sedimentary environments for study of ancient climate changes in theenvironments and lake level changes. Lake Zeribar is situated in the province of Kurdistan, inthe Zagros Mountains in three kilometers north-west of Marivan. The main purpose of thisresearch is to study grain-size sediments accumulated in Zeribar lakes in order to check thewater level fluctuations, climatic and environmental changes during the Holocene. Grain-size ofthe lake sediments is mainly controlled by the distance of the core site from the shoreline, thekinetic energy of the lake circulation and the source of the sediments (Lerman, 1978). Thesediments sorting principle states that the grain size of lake sediments becomes finer and finerfrom the shore to the center, and sediment belts of different grain-size can be distinguished.Lake Zeribar sediments, providing a record of climatic variations more than 40,000 years long,have been the subject of multidisciplinary investigations reported in several publications(among others: plant macrofossils by Wasylikowa, 1967, 2005; diatoms by Snyder et al., 2001;stable isotopes by Stevens et al., 2001). However, sediments of the lake have not yet beenanalyzed for grain-size, whereas it could reveal important information about the lake history andsedimentary process-geomorphology.∗E-mail: maghsoud@ut.ac.ir Tel: +98 91239060198 Physical Geography Research Quarterly, 46 (1), Spring 2014MethodologyA 6.88 m long core was extracted from the west part of the lake by a standard chamber corer,the Russian corer, 50 cm in length and 5 cm in diameter.Sediments were sampled at an interval of 1-10 cm. All samples were split into halves andweighed. One half was wet-sieved using a 63 m diameter sieve. The >63 m fraction (sand andgranule) was dried and weighed for sand and granule content. The other half was analyzed formineral type. The <63 m fraction was analyzed using a laser diffraction particle size analyzer(Micro tec A-22, Analysette 22 ) which utilizes grain-size range, 0.001-2 mm. Samples weretreated with 30% H2O2 to remove organic matters. The samples were further dispersed via 10minutes of exposure in an ultrasonic bath just before size analysis. For the purpose of particlesizespecification, the following scale used by Folk and Ward (1957) was adopted; granule:>2mm, sand: 2000-63 m (-1 to 4), silt: 63-3.9 m (4-8), and clay: 3.9-0.24 m (8-12).Radiocarbon dating of the sediments was performed for three bulk sediments using astandard Accelerator Mass Spectrometer (AMS) method at the Institute of Accelerator AnalysisLtd, Japan. The 14CAMS dates were calibrated to years AD and calendar years BP usingOxCalv.4.1 (Bronk Ramsey, 2009) and IntCal09 (Reimer et al, 2009).Results and DiscussionBased on the patterns of long-term fluctuations in median, mean and mode sample diameterscombined with the percentages of the clay: (<2 m), silt: (2–63 m) and sand: (>63 m) sizefractions, frequency curves, and lithology, the whole sediment record is divided into 4subdivisions as A (688-528 cm, 8950-6870 calyr BP), B (528–423cm, 6870-5500 calyr BP), C(423–244 cm, 5500–3170 calyr BP), and D (244–100 cm, 3170–1300 calyr BP) as describedbelow, separately.During phase A (688-528 cm, 8950-6870 cal BP) the percentage content of silt increases to~74.8%, while the content of sand decreases to ~6.33%.During phase B (528–423 cm, 6870–5500 calyr BP), the percentage of sand (average=14%)increases sharply while the percentage of silt (average=67.18%) decreases. The relatively highcontent of sand likewise implies a low lake level, which reflects effective moisture in the wholedrainage.During phase C (423–244 cm, 5500–3170 calyr BP) the percentage content of silt increasesto ~77.4%, while the content of sand decreases to ~5.4% indicating high effective humidity andmoisture in Lake Zeribar. The high and stable content of silt and fine components in thesediments indicates that lake-level reaches its highest value in the Holocene at this time.During phase D (244–100 cm, 3170-1300 calyr BP), the content of sand (average=10.5%)increases while the content of silt (average=69.86%) decreases. Several cycles in grain-size maybe related to centennial climate cycles. The high content of the coarse component suggest lakelevellowering.Physical Geography Research Quarterly, 46 (1), Spring 2014 9ConclusionThe grain size data and descriptive statistics (mean, standard deviation, kurtosis, and skewness)showed various degrees of fluctuations in both short and long terms. Changes in climate andlake size appear to be the main factors affecting the variability in the grain-size distribution,properties, and type of minerals. The results of the data analysis suggests the existence of warmand wetter climate, increased spring rains, episode of higher lake water level, existence of freshwaterconditions, prevailing high-energy condition, dominance of erosional processes, seasonalsupply of detritus, inflows strength and dominance of chemical weathering about 8950-6870and 5500-3170 calyr BP. The results indicate the existence of dry climate, reduced rainfall,occurrence of drought, lake-level lowering, prevailing low-energy condition, absence ofseasonal supply of detritus, conditions of tidal changes, and dominance of physical weatheringabout 6870-5500 and 3170-1300 calyr BP. It can be suggested that during the late Holocene3170-1300 calyr BP variations of water-level occurred irregularly, as the results of precipitationchanges, occasional lake overflows, and perhaps human activities.
https://jphgr.ut.ac.ir/article_50618_60b8ac5a5f49507d34e34db64547eb5e.pdf
تغییرات اقلیمی
دریاچۀ زریبار
رسوبهای دریاچهای
ژئومورفولوژی دیرینه
climate change
Lake Sediments
Lake Zeribar
Palaeogeomorphology
per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
59
76
10.22059/jphgr.2014.50619
50619
Full length article
مطالعۀ الگوی دمای سطوح فیزیکی در شرایط جوی متفاوت
Study on Physical Surface Temperature Patterns in Different Weather Conditions
علی اکبر شمسی پور
shamsipr@ut.ac.ir
1
قاسم عزیزی
ghazizi@ut.ac.ir
2
مصطفی کریمی احمدآباد
mostafakarimi.a@ut.ac.ir
3
معصومه مقبل
moghbel@ut.ac.ir
4
استادیار دانشکدۀ جغرافیا، دانشگاه تهران
دانشیار دانشکدۀ جغرافیا، دانشگاه تهران
استادیار دانشکدۀ جغرافیا، دانشگاه تهران
دانشجوی دکتری اقلیمشناسی، دانشکدۀ جغرافیا، دانشگاه تهران
الگوی رفتاری دمای سطوح در طول شبانهروز و نیز در شرایط آبوهوایی گوناگون در محیطهای شهری، شاید در زمینۀ مدیریت و برنامهریزی شهری کارآمد باشد. در این پژوهش، روند تغییرات دمای اندازهگیریشدۀ چهار پوشش آسفالت، سیمان، خاک و سنگ، در محدودۀ ایستگاه هواشناسی ژئوفیزیک در شرایط جوی گوناگون واکاوی شد. با توجه به ارتباط بین دمای سطح و دمای هوا، مدل رگرسیونی محاسبۀ دمای سطوح با دمای هوا انتخاب و دمای برآوردشده با دمای اندازهگیریشده در ایستگاه، واسنجی شد. نتایج روشهای آماری نشان داد اختلاف دمای کمینه و بیشینۀ سطوح (به جز آب بهدلیل تأثیر تبخیر) در شرایط آفتابی، حدود 30 درجۀ سلسیوس است؛ در حالیکه اختلاف آنها در شرایط بارانی، ابری و بادی، بهترتیب به حدود 6، 10 و 20 درجۀ سلسیوس میرسد. همچنین، در شرایط جوی همراه با بارندگی، علاوهبر وقوع کمترین دامنۀ دمایی، رفتار دمایی سطوح نسبت به یکدیگر نیز دچار تغییر میشود. نتایج مدل رگرسیونی نشان داد که بیشترین همبستگی بین میانگین دمای هوا و میانگین دمای سطوح وجود دارد. براساس ضرایب همبستگی و ضریب کارایی ناش ـ ساتکلیف، رابطۀ رگرسیونی مورد استفاده برای تخمین میانگین دمای سطوح، از کارآیی مناسبی برخوردار است.
IntroductionMaterials and surfaces with different thermo-physical properties provide variety of temperaturepatterns and temporal changes. Analyzing thermal behavior of the different land covers is one ofthe significant factors to determine urban microclimates. Urban land covers have usually hightemperature. This can potentially increase the intensity of urban heat island effect and buildingcooling energy consumption and also change energy balance and heat fluxes in these areas.Therefore, regarding to the impact of surface temperature on changes of surrounding aircomponents and formation of Urban Heat Islands (UHI), the main objectives of this study areincluding identification of the circadian pattern of surface temperature in different weatherconditions and providing the best regression model to estimate surface temperature using airtemperature.MethodologyTo determine the surface temperature patterns of different land covers such as Asphalt, Soil,Cement and Stone, three data loggers along with four Platinum Resistance Thermometers(PT100 sensors) were installed in Geophysic Weather Station in University of Tehran.∗E-mail: Shamsipr@ut.ac.ir Tel: +98 9126024199Physical Geography Research Quarterly, 46 (1), Spring 2014 11Therefore, temperature of these land covers was recorded hourly during the November 2012.Furthermore, meteorological data including air temperature (°C), relative humidity (%),precipitation (MM), and cloudiness (Okta) were gathered from Geophysic Weather Station.Then, circadian temperature pattern of different land covers were selected to be analyzed in sixdays of November with different weather conditions (Sunny, Cloudy, Rainy conditions).Finally, the best regression model for predicting daily mean surface temperature was providedusing air temperature. In addition, two statistical methods such as Nash-Sutcliffe efficiencycoefficient and correlation coefficient were used for determining the efficiency of the regressionmodel in estimating the different land covers surface temperature.Results and DiscussionAccording to the results, it can be concluded that in sunny and cloudy conditions surfacetemperature of all land covers increase with sunrise at 6 A.M. (local time) and this trendcontinue until noon so that, maximum surface temperature occur around 12 P.M. Then, surfacetemperature decreases because of reducing the amount of solar radiation and finally at sunset,the surfaces lose their heat, obtained during the day, as long wave radiation. It is important tonote that in cloudy conditions, the amount of energy absorption during the day and it losesduring the night is less than sunny conditions because of cloud cover existence in the sky andthe effect of the cloud’s albedo. Therefore, in these weather conditions surface temperaturepattern has sinusoidal mode but temperature range (difference between maximum and minimumtemperature) on cloudy conditions is less than sunny conditions due to cloud cover so thatstudying relationship between surface temperature and cloudiness depicted that there is inverserelationship between them and temperature reduces when cloudiness increase. It was alsoillustrated that there is no specific hourly trend in surface temperature in rainy conditions andthere are many variations in surface temperature. Totally, on sunny and cloudy conditions thehighest temperature is related to Asphalt, Cement, soil and Stone, in order. While on rainyconditions Asphalt has the lowest temperature between the studied land covers because of waterflow over the surface. Thus, it can also be concluded that permeability of the surfaces is one ofthe most significant physical properties in the surface temperature behavior. Land covers whichare impermeable (such as Asphalt, Cement and Stone) in rainy conditions show lowertemperature because of the water impact. In addition, reconstructed surface temperature datadisplay that there is a significant correlation between observed and estimated temperature usingdaily mean air temperature, so that correlation coefficient between these two parameters variesfrom 0.98 to 0.97 and is significant at 0.01% level. Moreover, result of Nash-Sutcliffe efficiencycoefficient varies from 0.8232 to 0.9205 which shows proper efficiency of the regression model.ConclusionThe main objective of this study is analyzing surface temperature of different land covers duringthe day/night and different weather conditions and also providing a regression model forestimating the surface temperature in these land covers. Generally, this can be concluded thatdifferent land covers surface temperature is completely a function of their thermal properties in12 Physical Geography Research Quarterly, 46 (1), Spring 2014calm and sunny weather conditions. Some surfaces such as Asphalt and cement which have lessthermal conductivity and high absorbency show the highest surface temperature during the day.While, on rainy conditions both air and surface temperature have many variation because ofcloudiness and precipitation. In such conditions some physical properties like permeability ofthe surfaces play significant role in thermal behavior of land covers. Finally, according to thecorrelation and Nash-Sutcliffe coefficients it is concluded that regression coefficients betweendaily mean air temperature and surface temperature have proper efficiency for calculating dailymean surface temperature.
https://jphgr.ut.ac.ir/article_50619_f2affe2bb400b3a54adea538c48329d5.pdf
الگوی دمای سطوح
پوشش سطحی
شرایط جوی
مدل رگرسیون
land cover
Regression model
Surface Temperature Pattern
Weather Condition
per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
77
92
10.22059/jphgr.2014.50620
50620
Full length article
تحلیل هیدروکلیماتولوژیکی نوسانهای سطح آب دریاچۀ ارومیه
Hydroclimatology Analysis of Water Level Fluctuations in Urmia Lake
دایوش یاراحمدی
yarahmadi.d@lu.ac.ir
1
استادیار گروه علوم جغرافیایی، دانشگاه لرستان
دریاچۀ ارومیه از مهمترین اکوسیستمهای آبی ایران است که تغییر در آن، تأثیرات گستردهای در وضعیت اقلیمی، اقتصادی ـ اجتماعی و هیدرولوژی خواهد گذاشت. برای بررسی ارتباط نوسانهای سطح آب دریاچۀ ارومیه با تغییرات دما، بارش، سطح ایستابی و دبی رودخانهها، سریهای زمانی متغیرهای مذکور طی دورۀ آماری 2010- 1981جمعآوری و تنظیم شد. همگنی و تصادفیبودن دادهها بهکمک آزمون ناپارامتریک ران تست مورد بررسی قرار گرفت. برای بررسی روند تغییرات متغیرها و میزان تأثیرگذاری متغیرهای مستقل بر متغیر وابسته (سطح آب دریاچۀ ارومیه)، از روشهای ناپارامتری من ـ کندال و پارامتری ضریب همبستگی پیرسون و تحلیل رگرسیون استفاده شد. نتایج نشان میدهد که کمابیش30 درصد از تغییرات سطح آب دریاچه با متغیرهای دما و بارش توجیه میشود. مدلهای هیدرولوژی مشخص میکنند که 42 درصد از نوسانات سطح آب دریاچه، ناشی از تغییرات دبی رودخانههای منطقه و سطح ایستابی آبهای زیرزمینی است و افزایش دما بیشتر از کاهش بارندگی در افت سطح آب دریاچۀ ارومیه مؤثر است. این مطالعه نشان داد که جهش و روند افزایشی دما از سال 1993، کاهش بارش و دبی رودخانهها از سال 1994، روند افزایشی ارتفاع سطح ایستابی و روند کاهشی سطح آب دریاچۀ ارومیه با تأخیر چهار ساله، از سال 1998 آغاز شده است.
IntroductionLake Urmia, at the northwestern tip of Iran, is one of the largest permanent hyper saline lakes inthe world and the largest lake in the Middle East. The lake is located between EasternAzerbaijan and Western Azerbaijan, west of the southern portion of the similarly shapedCaspian Sea. It extends as much as 140km from north to south and is as wide as 85km from eastto west during high water level periods. Because of being located in a dry and semi-dry region,this region doesn’t have suitable water resources comparing with global average waterresources. Drought, climatic fluctuations, and shortage and disorder of rainfall cause manyproblems with regard to food and water for people who live in this region. Urmia lake is alsoone the most important and the largest aquatic ecosystems of Iran. The systemic and chainchanges in the lake will lead to great effects on the climate and economic, social and hydrologyconditions. Oscillations of the lake water levels and volume in recent years have attracted manyopinions and created apprehensions.MethodologyGroundwater data, meteorological precipitation and temperature data were obtained from Urmiastation of Meteorology Organization for the period from 1981 to 2010. Then time series wereformed for temperature and precipitation in the form of annual, seasonal, and monthly files. Thetime series of temperature, precipitation, rivers discharges, and water table levels andoscillations of the lake water level were collected and adjusted for the periods 1981-2010. Toinform homogeneity and randomness of data and possibility of any trends in the time series, thenonparametric test was used. In this study, precipitation, river discharges and water tables and∗E-mail: d.yarahmadi@gmail.com Tel: +98 916165428114 Physical Geography Research Quarterly, 46 (1), Spring 2014temperatures were assessed as the independent variable and the water level as the dependentvariable. After reviewing the different parametric and nonparametric tests on the data in thisstudy, we eventually used a multivariable regression parametric test (Y=a+b1x1+b2x2) fortemperature and precipitation and these tests ultimately showed the ability to cover the analysisof data and review of this study.To determine the direction of the trend, type and time of changes based on a Man-Kendallgraphical and statistical test, the following formulas were used: 1)´ ´ ´´2)Results and DiscussionIn this study, the relationship between climatic factors and their effects on the hydrologicalconditions such as the river discharge, water level of Urmia Lake and wells water table werestudied. For presence or absence of relationship between them, the Pearson correlationcoefficient was used. The highest correlation between the water table and lake water level was0.71 which is significant at the level of 0.05. Among the four effective independent variables,the lowest correlation was observed between climate change and the water level of the lake. Thecoefficient for the river discharge and the water table was, respectively, 0.72 and -0.71. ThePearson correlation test shows that linear gradient during the period is significant with timeincreasing. The results indicate that the relationship between the precipitation and water level isnegative and temperature and the water table is positive. The regression gradient line at thescatter plot shows that the precipitation increase raises the water level. The highest annualdecreasing rainfall is -2.56. Increasing temperatures and declining rainfall, snowfall reduction,increasing evapotranspiration and reducing the water as input decreased the water level of thelake. As a result, the lake water level trend was decreasing 0.18 mm in each year. The modeland the regression analysis were calculated due to the delayed effects of climate andhydrological factors interference in each other. The coefficient determination indicates thatother factors remain constant; approximately 0.30 of the dispersion of the observed changes inthe lake water level is justified by temperature and precipitation variations. If we assume thathydrology parameters are constant, we can say that lake water level increases 0.005 meters perone mm rainfall and the lake water increases 1.672 meter per one cm river discharge.ConclusionBy designing a hydrology model, it was determined that 42 percent of water level fluctuations isdue to changes in the river discharge of the region and groundwater and water table. Byexamining regression models, we find that changes in hydrological parameters that are related tohuman factors rather than climatic parameters have the most influential effects on the lake waterlevel fluctuations. The temperature increase affected the lake water level dropping more than thePhysical Geography Research Quarterly, 46 (1), Spring 2014 15rainfall decrease. By examining Man-Kendall graphics, we characterized that leaping intemperature started in 1993. Precipitation and discharge decreasedin1993-1994 and this causedthe rise of the trend water table and reducing of water level in Urmia Lake, happened with afour-year delay which started from 1998.
https://jphgr.ut.ac.ir/article_50620_1788c806101c73fea2c26f0c6c0bad66.pdf
بارش
دبی
دریاچۀ ارومیه
دما
سطح ایستابی
discharge
precipitation
temperature
Urmia Lake
Water table
per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
93
108
10.22059/jphgr.2014.50621
50621
Full length article
ارائۀ یک روش نوین برای ارزیابی ریسک خشکسالی استان فارس با تلفیق داده های ماهانۀ بارندگی ماهوارۀ TRMM و داده های شاخص پوشش گیاهی NDVI سنجندۀ Terra/MODIS
A New Method for Drought Risk Assessment by Integrating the TRMM Monthly Rainfall Data and the
Terra/MODIS NDVI Data in Fars Province, Iran
مهدی عرفانیان
erfanian.ma@gmail.com
1
نسرین وفایی
nvafaei2@gmail.com
2
مهدی رضائیان زاده
mzr0031@auburn.edu
3
استادیار دانشکدۀ منابع طبیعی، دانشگاه ارومیه
کارشناس ارشد رشتۀ آبخیزداری، دانشکدۀ منابع طبیعی، دانشگاه ارومیه
دانشجوی دکتری هیدرولوژی، دانشگاه آبرن، ایالات متحده
این پژوهش با هدف تهیۀ نقشۀ خطر خشکسالی استان فارس با ترکیب روش شاخص خشکسالی هواشناسی SPI و روش آنومالی NDVI انجام گرفته است. ابتدا بهکمک دادههای ماهانۀ بارندگی از 44 ایستگاه استان فارس طی دورۀ آماری 2008-2000، شاخص خشکسالی SPI فصل رشد گیاهان محاسبه شد. سپس نقشههای SPI را با استفاده از روش کریجینگ معمولی تهیه شده و در پنج کلاس از نظر شدت خشکسالی (در هر سال) قرار گرفتند. پس از اعتبارسنجی دادههای ماهواره TRMM، نقشۀ SPI فصل رشد گیاهان در هر سال بهدست آمد. نتایج پژوهش بیانگر انطباق قابل قبول نقشههای SPI دادههای زمینی و SPI مبتنی بر دادههای TRMM است. در مرحلۀ بعد، نقشههای آنومالی شاخص NDVI فصل رشد گیاهان با استفاده از لایههای NDVI سنجندۀ MODIS در دورۀ نُهساله تهیه شد و در پنج کلاس شدت خشکسالی (در هرسال) طبقهبندی شدند. نقشۀ فراوانی خشکسالی از روی نقشههای باینری سالانه (بودن یا نبودن خشکسالی) استخراج شده است. از ترکیب وزنی خطی نقشههای احتمال وقوع خشکسالی دو روش شاخص SPI و آنومالی NDVI، نقشۀ ریسک خشکسالی بهدست آمد. براساس این نقشه، تقریباً بیشتر استان فارس مستعد خشکسالی بوده و خشکسالی با شدتهای مختلف را در دورۀ آماری مذکور تجربه کرده است.
IntroductionDrought monitoring and assessment is usually done through either ground observation orremote sensing. Due to having some limitations, gathering and analyzing ground observationsare a time-consuming and expensive way to approach a precise drought monitoring andassessment. In contrast, remote sensing represents a fast and economic way of monitoring, butan applicable approach needs to be developed. To this end, using satellite sensor data which arecontinuously available provides cost-effective data for a better understanding of the region.They can be used to detect the drought commencement, duration and magnitude. TropicalRainfall Measuring Mission monthly data (TRMM-3B43) and Monthly Normalized DifferenceVegetation Index (NDVI) data of the MODIS on Terra satellite are freely available for thisobjective. The main objectives of the present study, which was carried out in the Fars Province,Iran, were: 1. integrating the satellite data for mapping drought severity classes using theStandardized Precipitation Index (SPI) and the NDVI anomaly maps, 2. creating drought riskmaps, 3. calculating the percentage of drought affected area by drought risk level, 4. showingthe effectiveness of satellite derived drought indices as an indicator for drought assessment, and5. identifying the most drought vulnerable areas of the surveyed region.∗E-mail: Erfanian.ma@gmail.com Tel: +98 9123328494Physical Geography Research Quarterly, 46 (1), Spring 2014 17MethodologyThis research was carried out in Fars Province, Iran. It is located between 5030’ and 5536 Elongitude and from 2703’ to 3142 N latitude and cover an approximate area of 122661 km2.This study aimed to map drought risk area in the Fars Province, by integrating the StandardPrecipitation Index (SPI) and the Normalized Difference Vegetation Index (NDVI) Anomalymethods. As the first step, the growing season-based SPI (April- September) at 44 stations werecalculated for 2000-2008 period using the standard normal distribution. The SPI raster layer (foreach year), was created using the ordinary Kriging method. Then, all SPI maps were reclassifiedinto five drought severity classes. As the second step, NDVI anomaly maps were created for thegrowing season based-NDVI anomaly of MODIS during the same period (9-year period). TheNDVI anomaly map in each year was reclassified into five classes in a similar way. At the nextpart, for both methods, Boolean drought frequency map (presence or absence of drought)derived for each year. The derivation of final drought risk map was done by a simple weightedlinear combination of the drought frequency maps. In this research, another drought risk mapwas created by integrating the NDVI anomaly and the TRMM-based SPI maps to introduce anew remote sensing method.Results and DiscussionThe ground-based SPI method applied for the growing seasons showed that in 2000, 2001, 2005and 2008, some severe droughts occurred whereas the NDVI anomaly resulted in 2000, 2001and 2008. The drought severity maps of TRMM based on SPI method indicated some noticeabledrought occurrences in the Fars Province in 2000, 2005, and 2008 as well. The comparison ofdrought risk maps created by the TRMM-based SPI and the ground-based SPI methods showedthat the majority of the surveyed regions are highly prone to drought occurrence. The TRMMcould predict the monthly rainfall at most of 44 rain-gauge stations. Comparing drought riskmaps, the high and moderate risk classes in the first method contain % 59.58 and % 39.84,while in the TRMM based method, they cover %61.1 and %37.12 of the area, respectively.Before drought risk assessment, it is highly recommended to evaluate the TRMM data for futureevents. The risk maps can be compared with the actual decrease in agricultural products for abetter understanding of the events and their verifications.ConclusionThe method applied in this study showed that almost whole the province is prone to droughtoccurrences. The northern and southern areas of the province were more susceptible to droughtwith different severities during the growing seasons in 2000-2008. It is notable to express thatthere are still some limitations to apply the satellite data for a long period. These might be dataavailability problem with moderate spatial resolution. The TRMM and the MODIS data havebeen available since 2000 and 1998, respectively. Furthermore, the TRMM data calibration andvalidation is required before creating the TRMM-based SPI maps. Despite their shortages, theapplication of remote sensing data for drought risk assessment can still be done as an acceptablemethod in ungauged regions.
https://jphgr.ut.ac.ir/article_50621_bf69485e9bdea41df3bda56ad6b623ff.pdf
آنومالی NDVI
خشکسالی
فارس
MODIS
TRMM
Drought
Fars
MODIS
NDVI Anomaly
TRMM
per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
109
122
10.22059/jphgr.2014.50622
50622
Full length article
بررسی آثار تغییر اقلیم بر میزان بازدید از جزیرۀ هنگام
Investigating the Effects of Climate Change on the Number of Visitors in Hengam Island
اسداله خورانی
khoorani@hormozgan.ac.ir
1
شهربانو منجذب مرودشتی
s_monjazeb@yahoo.com
2
استادیار گروه جغرافیا، دانشگاه هرمزگان
دانشجوی کارشناسی ارشد اکوتوریسم، دانشگاه هرمزگان
هدف از این مطالعه، بررسی تعداد بازدیدکنندگان جزیرۀ هنگام در شرایط تغییر اقلیم طی سالهای 2040-2010 است. برای انجام این پژوهش از دادههای اقلیمی (دما، بارندگی، رطوبت نسبی و ساعات آفتابی) ایستگاه بندرعباس و تعداد بازدیدکنندگان جزیرۀ هنگام استفاده شده است. برای مدلسازی تغییر اقلیم از سناریوهای انتشار A1B، A2 و B1دادههای مدل گردش عمومی جو HADCM3 استفاده شده است که بهکمک مدلLARS-WG5 ریزمقیاس شدهاند. بررسی رابطۀ دما و تعداد بازدیدکنندگان، رابطۀ معکوسی را بین دما و تعداد بازدیدکنندگان جزیرۀ هنگام نشان میدهد؛ بهطوری که با افزایش دما در فصول بهار و تابستان، از تعداد بازدیدها کاستهشده و با کاهش دما در فصول زمستان و پاییز، شمار بازدیدکنندگان افزایش مییابد. نتایج بهدستآمده نشان میدهد که شمار بازدیدگنندگان جزیرۀ هنگام در آینده دچار تغییرات فصلی خواهند شد. افزایش بازدید در دو فصل تابستان و پاییز و کاهش بازدید در فصلهای بهار و زمستان در هر سه سناریوی مورد بررسی، پیشبینی میشود. بهطور کلی در فصل بهار سناریوی A1B، بیشترین و در فصل زمستان سناریوی B1 کمترین روند کاهشی را در پیشبینی بازدیدهای منطقۀ مورد مطالعه داشتهاند. همچنین در فصل تابستان سناریوی A1B بیشترین روند افزایشی و در فصل پاییز سناریوی A2، کمترین روند افزایشی بازدیدها را نشان میدهد.
IntroductionClimate have strong impact on tourism and leisure time. Climate as a natural environmentalfactor plays an important role in tourism development in different regions of the world. Climatechange and global warming, due to increasing greenhouse gases have many effects on procedureof tourism areas. Evaluation of predictions on future climate change can reduce these effects ontourism industry. Unfortunately, despite the obvious importance of climate change on tourism,researchers have paid little attention to this topic until the 1980s. Thus, one of the oldestresearches in this region is the examination about the impacts of carbon dioxide on earthwarming and its effects on tourism (skiing Laavrntyds area) discussed by Boyle and Wall. Thisresearch has been done in Canada in 1980. In this study, climate change phenomenon has beenexamined using two scenarios A and B. The effect of climate change on snow condition, snowcover of the region, and ski industry were examined. The results show that this phenomenon hasimpact on the ski industry and shorten duration of the ski season. It should be noted that amongresearches carried out, a few of the issues of climate change was about the effects of climatechange on tourism activities.In another study, climate change has been investigated according to the GCM andregression models. Then, the effects of climate change on the number of visitors have beeninvestigated using economic models such as travel cost (TCM). In some of these studies suitableconditions of tourism in nowadays and in the future (of climate change) has been determined by∗E-mail: agroclimatologist@gmail.com Tel: +98 9124803242Physical Geography Research Quarterly, 46 (1), Spring 2014 19TCI Index and also effects of time of climate comfort on the number of visitors have beenstudied. The results show that climate change has effects on the number of visitors (Scott et al.,2007; Chotiyaputta and Pongkijvorasin, 2013; Amelung et al., 2007; Hein, 2009; Yu et al.,2010).Few studies on the effects of climate and climate change on tourism have been conducted inIran. In these studies, the relationship between climate impacts and tourism as well as theimpacts of climate change on the tourism industry has been investigated. The results express theclose relationship between climate and tourism activities and the impact of climate change onthe industry (Mohammadi et al., 2008; Ranjbar et al., 2010; Kaviani et al., 2007; Ramezani andAbraham, 2007; Ghaderi, 2010, Bonn, 2010; Ziai et al., 2010; Haji Amini and Ghaffarzadeh,2010; Bakhtiari, 2010). Rainfall and temperature changes and their impacts on tourism wereexamined by Ataee and Fanaee in 2011 in Shiraz. Results of the study indicate that Shirazrainfall and temperature are in two states of without a process and with process, respectively.Temperature process is ascending. This matter could have a major impact on the amount oftourists of this city. Karimi in 2008 have also studies about the relationship between climate andtourism using climate tourism indices such as PET, PMV, SET, ET, and stress pressure indexfor Tabriz City. The purpose of this study is to investigate the effects of climate change on thevisit level in Hengam Island.MethodologyTo achieve the purpose of this research, climatic factors are used as independent variables andthe number of visitors as dependent variable in stepwise multiple linear regression models. Inorder to simulate climate change based on general circulation models (GCMs), LARS-WGdownscaling tool is applied. This stochastic weather generator downscaled the climate ofBandarabass synoptic station by using HADCM3 model and A1B, A2, B1emission scenarios,for 2040.LARS-WG is one of the most popular models for random generation of weather data. Thismodel is used for generating daily rainfall, minimum temperature, and radiation or sunshinehours in a station, for base data and future climate. Table 1-1 represents characteristics of threescenarios used in this study.Table 1. Characteristics of scenarios as used in this studycharacteristics scenarioA1BRapid economic growth, population growth maximum at mid-century and thendeclined, the rapid development of modern technologiesA2Rapid population growth in the world, heterogeneity in economy and in line with theregional growth throughout the worldB1The convergence of the global population, changes in the structure of the economy(Pollutions reduction and introduce clean and efficient technology resources,)20 Physical Geography Research Quarterly, 46 (1), Spring 2014Results and DiscussionThe results show that there is a reverse relationship between temperature and the number ofvisitors in Hengam Island. The number of visitors decrease when temperature rise in warmseasons (spring, summer), and visitors increase with decreasing temperature in the cold season(winter, spring). The results also show that the number of visitors was affected by seasonalchanges in the future. Generally, it is predicted that visits increase in summer and autumnseasons and decrease in spring and winter seasons. The highest visit frequency is predicted forautumn season in the A1B scenario and the lowest belongs to summer in the A2 scenario. Thehighest visit reduction is predicted for spring season in the A1B scenario and the lowestreduction belongs to winter in the B1 scenario.ConclusionThe results show the greatest increasing changes of visits in autumn (according to scenarioA1B) and the smallest increase in summer (according to scenario A2). The main resultsobtained in this study are consistent with similar studies by other researchers. The main resultsare increase of temperature in the regions (Ataee and Fanaei, 2011; Shah Karami, 2007; Abbasiet al., 2010; Massah Bavanat et al., 2010; Babaeian and Najafi Nick, 2010; Ashraf et al., 2011;Abbasi et al., 2010; Azizi and Roshan, 2008; Rahimi and Majd, 2011; Babaeian et al., 2009;Azad Torabi et al., 2010; Babaeian and Kuhi, 2012; Azizi et al., 2008) and (Berrittella et al.,2006; Hein, 2009; Giannakopoulos, 2009; Burki and Elsasser, 2002; Chotiyaputta, andPongkijvorasin, 2013; Yu et al., 2009). But the result is not consistent with the decrease oftemperature in the summer and autumn, which could be due to the specific conditions of eachregion (latitude, location, topography, etc.).
https://jphgr.ut.ac.ir/article_50622_0199cecba778a8bc932d9ad7f679282c.pdf
اکوتوریسم
تغییر اقلیم
جزیرۀ هنگام
مدل رگرسیون خطی
مدلهای GCM
climate change
Ecotourism
GCM Models
Hengam Island
linear regression model
per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
123
136
10.22059/jphgr.2014.50623
50623
Full length article
بررسی نوسان اقلیم در استان فارس با استفاده از جابهجایی نصف النهاری نوار پرارتفاع جنب گرمسیری
Climate Oscillation Assessment by Meridional Displacement of Sub Tropical High Passing over Fars Province
حدیث گل محمدیان
golmohammadianhadis@yahoo.com
1
کارشناس ارشد هواشناسی کشاورزی، دانشکدۀ کشاورزی، دانشگاه شیراز
نوار همگرایی درونگرمسیری (ITCZ) درگذر فصل دارای جابهجایی نصفالنهاری است. تغییر موقعیت ITCZ روی موقعیت نوار پرارتفاع جنب گرمسیری (STH) اثر میگذارد. هدف پژوهش، بررسی نوسان اقلیمی در فارس با مطالعۀ موقعیت پرارتفاع جنب گرمسیری است. دادههای ماهانۀ ارتفاع ژئوپتانسیل سطح 500 میلیبار، از تحلیل مجدد NCEP بهدست آمد و نصفالنهار E°5/52 در نظر گرفته شد. با مشاهدۀ سری نقشههای 500 میلیباری و توجه به امواج غربی و STH، تراز ارتفاعی 5840 متر، بهمنزلۀ مرز شمالی نوار پرارتفاع جنب گرمسیری (NBSTH) مد نظر قرار گرفت و سری زمانی ماهانۀ موقعیت NBSTH بهکمک برنامهنویسی در GrADS ساخته شد. نتایج نشان داد موقعیت NBSTH به اندازۀ 7/2 بهسمت عرضهای جغرافیایی شمالیتر جابهجا شده است، بنابراین سیگنال نوسان اقلیمی در منطقه مشخص شد. این مسئله موجب افزایش دورۀ حاکمیت STH و کاهش دورۀ فصل بارش میشود. موقعیت و جابهجایی NBSTH بیش از اینکه بر میزان بارش مؤثر باشد، روی طول فصل بارش اثر دارد. زمانیکه موقعیت NBSTH از عرض جغرافیایی ایستگاه پایینتر رود، فصل بارش آن ایستگاه آغاز خواهد شد و زمانی پایان میپذیرد که تحت تأثیر پرارتفاع جنب گرمسیری (NBSTH) باشد. نتایج نشان داد طول فصل بارش در آباده شش ماه و نیم، شیراز شش ماه و در لار پنج ماه در سال است.
IntroductionAccording to General Circulation Model (GCM), zonal thermal belts are: 1. Inter- TropicalConvergence Zones (ITCZ) around equator; 2. Sub Tropical High (STH) belt around 30 degreelatitude; 3. Sub Polar Low (SPL) belt around high latitudes. Inter- Tropical Convergence Zonesbelt has meridional migration on the different seasons and its position affects directly thesituation of STH. The STH situation is the most important synoptic climatological pattern inMiddle East and Iran due to changing season. The belt of Inter Tropical Convergence Zone(ITCZ) displaces in meridional path, about 5° over oceans and up to 40° in continents, duringseasons of a year. The position of Sub Tropical High (STH) belt has been also affected by ITCZmovements. STH displacement may change the area covered by westerly Baroclinic Waves(BW) in temperate regions. The Northern Boundary Sub Tropical High (NBSTH) movescoincidently as the northern border of the STH belt. The position of the NBSTH is an importantissue for changing precipitation regime and onset of precipitation events in Fars Province. Thegoal of this research is to determine the position of NBSTH over Fars in monthly scale duringthe period 1948 - 2010, undertaking its meridional displacement.MethodologyDataset of geopotential height in multi levels (monthly scale) was extracted from NCEP/ DOEReanalysis published by NOAA using by GrADS (Grid Analysis and Display System) softwarefor 52.5°E meridian over Fars Province. By consecutive observation of 756 numbers of 500 hPamonthly maps in GrADS scope, 5840 gpm contour was indicated as the NBSTH indicator. It is∗E-mail: golmohammadianhadis@yahoo.com Tel: +98 939657396222 Physical Geography Research Quarterly, 46 (1), Spring 2014because southern area of 5840 gpm contour is almost covered by STH system while thenorthern area occupied by westerlies during monthly round maps. This result agrees withprevious studies. The strip of NBSTH is considered with 20 m width ranging from 5830 gpm to5850 gpm. Monthly time series of NBSTH position (unit: degree of northern latitude) was thendetected using GrADS programming. The non-parametric Mann-Kendall trend test was appliedon time series of NBSTH position in monthly and annual scale.Results and DiscussionResults show that the position of NBSTH is between 10°N and 47.5°N as the most extremes inwinter and summer, respectively. For long term means, the minimum latitude of NBSTH was inaverage observed in January, placed on 18°N zone while maximum is happened in August,crossing 41°N zone during the investigated period. Its meridional displacement then reaches to23° over Iran in average. Moreover, climatic means of Northern Boundary Sub Tropical Highpositions during 1981- 2010 period with respect to 1951 - 1980 period were migratedapproximately 2.7 ° northward. The non-parametric Mann-Kendall trend test was then applied. Itshowed generally raising trends under 0.01 significance level, with 0.07 slope approximationsduring 1948-2010. It demonstrated the signal of climatic variability of atmospheric circulationover Fars. This significant trend may also shorten the period of the rainy season in Fars. Rainyseason of the most stations in Fars may be defined as the period when the NBSTH position goesto the southern zones of the station and consequently subjected to the atmospheric baroclinicstate of westerlies.ConclusionThe more precise results need primitive data in daily scale that suggested for the next step.Nevertheless, it is generally deduced that the lower latitudes of Fars have thus shorter durationof the precipitation seasons. The belt of STH dominates over a zone when the NorthernBoundary Sub Tropical High (NBSTH) position is above latitude the station. Changes inprecipitation regimes are also related to the NBSTH position. The onset of precipitation eventsfor the stations located in the Fars starts climatically later than those located in the north becauseof NBSTH situations. It is also suggested to use time series of NBSTH position as the input ofclimatic prediction models yielding temperature and precipitation. It is suggested that the timeseries of NBSTH position is as the input of climate prediction models yielding temperature andprecipitation as well as drought study. In drought study, agricultural management as well asmassive economical and social programming in Iran seems to be essential due to NBSTHposition.
https://jphgr.ut.ac.ir/article_50623_6caa75b40ac43a6584ccf9af34017d17.pdf
جابهجایی نصف النهاری
فارس
مرز شمالی پرارتفاع جنب گرمسیری (NBSTH)
نوسان اقلیمی
Climate oscillation
Fars
Meridional displacement
Northern Boundary Sub Tropical High (Nbsth)
per
دانشگاه تهران
پژوهش های جغرافیای طبیعی
2008-630X
2423-7760
2014-04-21
46
1
1
21
10.22059/jphgr.2014.50624
50624
چکیده های انگلیسی
English Abstracts
https://jphgr.ut.ac.ir/article_50624_72844585c138b172015c22ee14010b2c.pdf