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پژوهش های جغرافیای طبیعی، جلد ۴۶، شماره ۳، صفحات ۲۹۷-۳۱۰
عنوان فارسی ارتباط بین تیپ الگوهای گردشی تراز دریا، با بارش‌های فراگیر در ایران
چکیده فارسی مقاله در این مقاله ارتباط بین الگوهای جوی تراز دریا با بارش‌های فراگیر در ایران شناسایی شده است. برای این هدف از رویکرد همدید محیطی به گردشی استفاده شد؛ به‎طوری که ابتدا داده‎های بارش روزانۀ 210 ایستگاه همدید از سازمان هواشناسی ایران در دورۀ 1980 تا 2009 گرداوری شد. سپس با روش زمین‎مرجع کریجینگ، داده‎ها با ابعاد 9/5×9/5 کیلومتر میان‎یابی شد و با اعمال شرایطی، 1548 روز بارش فراگیر در ایران به‎دست آمد. در مرحلۀ دوم داده‌های روزانۀ میانگین فشار تراز دریا از سری داده‌های بازکاوی‎شدۀ NCEP/NCAR در 1548 روز مورد نظر برداشت شد. سپس با روش تحلیل مؤلفۀ مبنا (PCA) و تحلیل خوشه‎ای، الگوهای گردشی تراز دریا طبقه‎بندی شدند. درنتیجه پنج تیپ عمده برای بارش‎های فراگیر به‎دست آمد. نتایج نشان داد که بارش‎های فراگیر و سنگین ایران را می‎توان در اثر تقویت سه سامانۀ عمده در تراز دریا شناسایی کرد. این سامانه‎ها پرفشار تبت، پرفشار اقیانوس اطلس شمالی و کم‎فشار ایسلند ـ قطبی هستند. چنانچه این سه سامانه با هم تقویت شوند، گرادیان فشار روی ایران افزایش می‎یابد و با تشکیل یک جو باروکلینیک، بارش‎های فراگیر و سنگینی در ایران رخ می‌دهد که بیشینۀ میانگین آنها روی نواحی مرتفع کوه‎های زاگرس است.
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عنوان انگلیسی The Relationship between Circulation Pattern Types in Sea Level Pressure and Precipitation in Iran
چکیده انگلیسی مقاله IntroductionThe recent developments in computer sciences have considerably affected the application ofnew methods in climatology. Especially these new technologies have increased the usage of thenew methods in climatic classification. The previous classifications were calculated only basedon insufficient number of climatic factors. For example, the well-known classification ofKoppen was based on precipitation and temperature. In contrary to such threshold-basedclassifications, the implementation of multivariate statistical techniques has allowed to classifyclimate without predefined thresholds by grouping individual objects by Jacobeit (2010)methodology. Application of multivariate analysis in climatology is conducted by Yarnal et al(2001). The aim of this paper is to use the classification technique and recognize the circulationpatterns at the sea level and their connection to variability of precipitation in Iran. To obtain acomprehensive view of the precipitation in Iran and its effective factors a number of theresearches are conducted. Many papers have investigated the main circulation and air masses aseffective factors on Iran precipitation. However, there is not an agreement among them and themain disagreement seems to be about the methodology. Khoshhal (1997) using synopticanalysis studied the greater than 100 mm precipitation in coastal area of Caspian Sea. Heshowed that in contrast to the previous studies, the cold advection of the Siberian anticycloneover Caspian Sea is not the main reason for forming the heavy precipitations and these eventsare connected to the entrance and settlement of anticyclone and cyclonic systems. Applying thePhysical Geography Research Quarterly, 46 (3), Fall 2014 7vorticity calculation, Alijani (2003) identified the rainy air masses in Tehran.He concluded thatthe effect of 500 hPa level is stronger than other levels and the cyclonic circulation type createthe heavier precipitations.MethodologyThere are two main approaches in synoptic climatology: the environment to circulation andcirculation to environment approaches. Because of the high variability of precipitation,researchers used the environment to circulation in their studies (Yarnal, 1993). As a result, theenvironment to circulation approach is used in this paper as well. The mean daily precipitationsof synoptic stations of Iran were collected for time period of 1980 - 2009. The distributions ofthese stations are shown in Fig 1. Then the point data were interpolated with cell size of0.057° grid point (5.9􀵈5.9 Km). Totally a number of 46939 cells were calculated and an n 􀵈 pmatrix was created. Where n refers to the days (10958 days) and p refers to the spaces (46939).Using this matrix in daily basis, the Percent area, Mean and maximum precipitation for all areaof Iran were calculated. To eliminate the local precipitation and considering only the extensiveprecipitations, two conditions were defined: the average precipitation of Iran must exceed 1mm, and over 40 percent of Iran area must receive precipitation. Accordingly, a number of 1548days of extensive precipitation in the course of study area were recognized. For explanation ofthe circulation patterns of these events, mean sea level pressure, in a scale of 2.5°􀵈2.5° gridpoint, NCEP/NCAR reanalysis data from 0° to 100° eastern longitude and 10° to 80° northlatitude were collected and a 1548􀵈1189 matrix was created. The Principal ComponentAnalysis (PCA) was used in order to reduce the volume of the matrix. Many researchers haveused the PCA and its application in multivariate analysis.Results and DiscussionThe results of PCA over the extensive rain matrix of Iran are shown at table 1. As it can be seenin the table, a number of 48 eigenvalues greater than one which explained 92% of the totalvariance was obtained. Among these, 15 factors that explained more than 1% of whole thevariance were selected. These factors explained 88% of the total variance. Load factor matrixscore is the matrix that has a 154815 dimension.ConclusionIn this paper, the connection between circulation patterns on sea level and Iran precipitation wasanalyzed by applying environment to circulation approach. For this purpose, the daily grid pointprecipitation with 5.9*5.9 Km dimension obtained 1548 days, with considering a condition thatat least precipitation in Iran must be 1 mm and also 40 percent of Iran area must receive theprecipitation. Sea level pressures of these days were selected for identification of the main typeof the circulation patterns. The (PCA) technique was used for reduction data and with clusteranalysis it obtained 5 main circulation pattern types.The investigation of the relationship between the circulation patterns and the precipitation8 Physical Geography Research Quarterly, 46 (3), Fall 2014events revealed that there are five distinctive precipitation patterns in Iran. These types areincluding:Type 1: Interaction between Sudan low pressure and Siberian anticyclone;Type 2: combination of Mediterranean low pressure -Sudan low pressure and interactionwith Azores and European anticyclone;Type 3: interaction between Sudan low pressure and European high pressure tongue;Type 4: Interaction among Tibet high pressure, Azores high pressure, and polar lowpressure;Type 5: Thermal low pressures and Indian monsoon system.
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نویسندگان مقاله قاسم عزیزی |
دانشیار گروه جغرافیای طبیعی، دانشکدۀ جغرافیا، دانشگاه تهران، ایران
سازمان اصلی تایید شده: دانشگاه تهران (Tehran university)

تیمور علیزاده |
دانشجوی دورۀ دکتری اقلیم‎شناسی، دانشکدۀ جغرافیا، دانشگاه تهران، ایران
سازمان اصلی تایید شده: دانشگاه تهران (Tehran university)

نشانی اینترنتی http://jphgr.ut.ac.ir/article_52133_0727096e2b8ea2e6d1a3114177e1817f.pdf
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