مقايسه پهنه‌هاي بارشي استان سيستان و بلوچستان با استفاده از داده‌هاي ماهواره‌اي و ايستگاه‌هاي زميني

Comparison of the Sistine and Baluchistan Province Precipitation Zones Using Satellite Data and Ground Stations

براي پهنه بندي بارش در استان سيستان وبلوچستان از دو سري داده‌هاي ماهواره (TRMM) با قدرت تفكيك 0/5*5/.0درجه وداده‌هاي145 ايستگاه باران سنجي‌، اقليم شناسي و ايستگاه‌هاي سينوپتيك براي يك دوره12ساله (1378-1390)استفاده گرديد. براي اين تقسيم بندي بر روي هر دو سري داده‌هااز طريق تحليل مولفه‌هاي اصلي وتحليل خوشه‌اي به روش وارداعمال گرديد. با بررسي به عمل آمده بر روي ماتريس بارگويه‌ها و خوشه‌بندي داده‌هاي ايستگاهي استان به سه پهنه كم بارش وسيع،متوسط بارش مكراني و پهنه پر بارش سراواني تقسيم گرديد.نتيجه تحليل مولفه‌هاي اصلي و خوشه‌بندي بارش با داده‌هاي ماهواره (TRMM)،تقسيم استان به سه پهنه پر بارش شمالي، كم بارش مركزي و پهنه متوسط بارش جنوبي مي‌باشد. مقايسه پهنه بندي با دو سري داده مذكور نشان مي‌دهد كه پهنه‌بندي با داده‌هاي ماهواره (TRMM) داراي خطاي بالايي در تقسيم بندي بارشي استان مي‌باشد بطوري كه ناحيه شمالي وغربي استان را كه داراي ارتفاع كم از سطح دريا و فاصله بيشتري از منابع رطوبت مي‌باشند را منطقه‌اي با بيشترين ميزان بارش نشان داده و همچنين ناحيه مركزي كه درآن رشته كوه‌هاي مكران واقع شده و در تابستان از سامانه‌هاي موسمي هند بهره‌مند است را به عنوان كم بارش ترين ناحيه استان معرفي مي‌‎كند. موارد مذكور در پهنه بندي با داده‌هاي باران سنجي لحاظ شده است و اين پهنه بندي مبناي مناسب تري جهت استفاده در برنامه‌ريزي مي‌باشد. نقطه قوت دو پهنه بندي در يكسان بودن رژيم بارندگي مي‌باشد.

Introduction Rainfall is the most variable climatic elements. The changes of Precipitation in the location and the time dimension are large. Climate zoning and spatial resolution similar regions in terms of climate Regional development planning and investment capabilities across the country, including SistanBaluchistan province seems necessary. Materials and methods For zoning Sistan and Baluchestan province of precipitation two series of satellite (TRMM) data With Resolution 0.5 * 0.5 degrees and 145 rain gauge, Climatology and synoptic stations for a period of 12 years (20002011) are used. For this division on the two data series through principal component analysis and cluster analysis the ward method was applied. The monthly precipitation data from stations placed in a matrix of rows and columns of the matrix dimensions of 145 rain stations. In the next step the correlation between annual precipitations measured data and the calculation results in a matrix called the correlation matrix (R) inserted. At Continuation the results of Rotated component Matrix with varimax method As Input Cluster Analysis reused. The procedures were done for both data Series. Satellite (TRMM), Tropical Rainfall Measuring operations, a joint mission of the United States National Aeronautics and Space Agency (NASA) and the Japan Aerospace Exploration Agency (JAXA) is. The Satellite Monitor and study tropical rainfall And How Effect the Precipitation on Global climate. Results and discussion The study performed on Weight matrix and clustering of the stations data, Province divided into three broad zones of Extensive low precipitation, Makran average precipitation and Saravani high precipitation. Analysis of results the principal component analysis and clustering of precipitation with satellite data (TRMM) Province Divided into three zones of the northern high precipitation, central low precipitation and southern average precipitation. Comparison of zoning with two data series Indicates that Zoning with satellite data has a high error in Precipitation division. So that the North West and west of Province Which has a low height above sea level and away from sources of moisture are more Most precipitation in the region shown And the central area where Located the Makran Mountains And Indian summer monsoon system has benefited Defines the area with low precipitation in this province. Conclusion This study compares the Zoning Two Data Series Ground stations and data Sensor Satellite (TRMM) took place. According to Located in this province Close to tropical, Satellite data With Actual data At Zoning rain Province Case Was compared the following results were obtained. 1. Data of Sensor Satellite (TRMM) Relatively large error and use this data Sometimes Results Different from the measured data by Rain stations offers. 2. Best performance, sensor data, satellite (TRMM) in the southern half of the province and the maximum error deviation of the data relative to ground stations in the northern half of the province.