برآورد ماهواره‌ای بخار آب قابل بارش (PWV) در جو ایران و تحلیل همبستگی مکانی آن با فراسنج‌های آب و هواشناختی

نوع مقاله : مقاله پژوهشی

نویسنده

گروه جغرافیا، دانشکده علوم انسانی، دانشگاه زنجان، زنجان، ایران.

چکیده

بخار آب قابل بارش یکی از کمیت‌های مهمِ هواشناسی، فیزیک جو، هیدرولوژی و تغییرات اقلیمی است که برآورد آن در پیش­بینی مقدار بارش، وقوع سیلاب و سایر پارامترهای هیدرولوژیکی مفید می­باشد. امروزه از تصاویر ماهواره­ای به­‌طور گسترده‌ای برای برآورد بخار آب قابل بارش و تحلیل همبستگی آن با سایر فراسنج‌های آب و هواشناختی استفاده می‌شود. هدف از پژوهش حاضر برآورد مقدار بخار آب قابل بارش و بررسی رابطه‌ی آن با شش متغیر اقلیمی از قبیل دما، فشار، رطوبت نسبی، درصد ابرناکی، بارش و سرعت باد در گستره‌ی جغرافیایی ایران با استفاده از داده‌های ماهواره مبنا می‌باشد. داده‌های مورد استفاده با گام‌های زمانی ماهانه و مکانی° 1°×1 در گستره‌ی اقلیمی جو ایران برای دوره‌ی ‌داده‌برداری 2019 – 2003 انتخاب گردید. برای بررسی رابطه‌ی بین بخار آب قابل بارش با متغیرهای اقلیمی، از ضریب همبستگی پیرسون استفاده شد. داده‌های رقومی استخراج شده پس از کنترل کیفی و پیش‌پردازش، توسط نرم‌افزارهای تخصصی از قبیلENVI، ArcGIS و Grads برای ساخت لایه‌های رستری بر اساس مرز جغرافیایی کشور ایران به­کار گرفته‌شد. بر اساس نتایج، میانگین آب قابل بارش در جو ایران mm 7/12 ‌است که در مقایسه با میانگین جهانی (mm 6/21)، کم بودن مقدار آب قابل بارش در جو ایران را نشان می دهد. از سویی دیگر مقدار آب قابل بارش در جو ایران از توزیع زمانی و مکانی همگنی برخوردار نیست. به­طوری که بیش­ترین مقدار آن در ناحیه‌ی ساحلی جنوب و شمال و کمترین مقدار آن بر فراز سلسله جبال زاگرس، بخش‌هایی از شمال شرق و شرق ایران و در اولویت بعدی در نواحی بیابانی ایران مرکزی متمرکز است. میانگین همبستگی آماری (پیرسون) بین pwv با دما (R= %86)، با فشار (R= - %89)، با رطوبت نسبی (R= - %88)، با ابرناکی (R= - %32)،  با بارش (R= - %64) و سرعت باد (R= %67) بوده‌است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Satellite Estimation of Precipitable Water Vapor (PWV) in Iran Atmosphere of Iran and the Analysis of its Spatial Correlation with Meteorological Variables

نویسنده [English]

  • Koohzad Raispour
Department of Geography, Faculty of Humanities, University of Zanjan , Zanjan, Iran.
چکیده [English]

Precipitable Water Vapor (PWV) is one of the most important quantities in meteorology, atmospheric physics, hydrology and climate change studies, which its estimation is useful in predicting precipitation, flood occurrence and other hydrological parameters. Today, satellite imagery is widely used to estimate PWV and analyze its correlation with other meteorological Variables. The objective of this study was to estimate the amount of PWV and to investigate its relationship with six climatic variables such as; temperature, pressure, relative humidity, cloudiness ratio, precipitation and wind speed in the geographical area of Iran using satellite-based data.The proposed data with monthly time steps and 1°*1° spatial resolution were selected in the climatic range of Iran's atmosphere for the period of 2003-2019. Pearson correlation coefficient was used to investigate the relationship between PWV and the above mentioned climatic variables. Digital data extracted after qualitative control and pre-processing were used by specialized software such as ENVI, ArcGIS and Grads to build raster layers based on the geographical boundary of Iran.  According to the results, the average PWV in the atmosphere of Iran is 12.7 mm, which shows a lower amount as compared to the global average (21.6 mm). On the other hand, the amount of PWV in the Atmosphere of Iran does not have a temporal and spatial homogeneous distribution. So that the highest amount of PWV is concentrated in the coastal area of south and north and the lowest amount is concentrated over the Zagros mountain range, parts of northeast and east of Iran and in the next priority in the desert areas of central Iran. The Pearson correlation coefficients between PWV and the meteorlogical variables were 86% for air temperaure, - 89% for pressure, - 88% for relative humidity, - 32% for cloudiness ratio, - 64% for precipitation and  67% for wind speed.

کلیدواژه‌ها [English]

  • Satellite Estimation
  • Precipitable Water
  • AIRS Sensor
  • Pearson correlation
  • Atmosphere of Iran
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