پهنه‌بندی رطوبت نسبی استان سیستان بلوچستان با استفاده از تصاویر سنجنده MODIS

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه آب و هواشناسی، دانشکده علوم انسانی، دانشگاه محقق اردبیلی، اردبیل، ایران

چکیده

هدف این پژوهش ارائه روشی بر مبنای الگوریتم­های جهانی و تجربی جهت برآورد رطوبت نسبی در استان سیستان و بلوچستان است. بدین منظور از تصاویر ترا مودیس و از محصولات (MOD05, MOD07) مربوط به بازده زمانی 10 ساله (1 ژانویه 2009 تا 31 دسامبر 2018) در شرایط بدون ابر به‌عنوان داده­های منتخب استفاده شد. برای اعتبار سنجی لایه­های به‌دست‌آمده (دمای نزدیک سطح زمین، فشار سطح زمین، آب قابل بارش TPW و رطوبت نسبی)، داده­های ایستگاه زمینی و رادیوساند مورداستفاده قرار گرفت. مقدار R2 و REMS لایه‌های ثبت‌شده از سنجنده و داده­های زمینی قابل‌ قبول بودند و داده­های سنجده هم‌خوانی مناسبی با اندازه­گیری­های ایستگاه­های زمینی داشتند. نتایج به‌دست‌آمده حاکی از این هستند که عامل ارتفاع نقش تعیین‌کننده‌ای در فرا سنج دما دارد. حداقل مقدار آب قابل بارش، 6 میلی­متر در مناطق خاش، میر جاوه و سراوان در فصل سرد سال و حداکثر آن با 49 میلی­متر در مناطق ساحلی در فصل گرم سال ثبت‌شده است. میزان متوسط رطوبت نسبی در فصل سرد سال در کل استان در حالت تعادل قرار دارد ولی در فصل گرم سال از حالت تعادل خارج می‌شود که در سواحل دریای عمان بالای 60 درصد و در مرکز استان (خاش، میر جاوه و زاهدان) کمتر از 10 درصد است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Relative Humidity Zoning of Sistan-Baluchestan Province Using MODIS Satellite Images

نویسندگان [English]

  • Masiholah Mohammadi
  • behrouz sobhani
Department of Climatology, Faculty of Humanities, University of Mohaghegh Ardabili, Ardabil, Iran
چکیده [English]

The purpose of this research is to present a method based on global and experimental algorithms for estimating relative humidity in Sistan and Baluchestan province. For this purpose, Terra MODIS images and products (MOD05, MOD07) of 10-years (1-Jan-2009 to 31-Des-2018) under cloudless conditions were used as selected data. To validate the obtained layers (near ground surface temperature, ground surface pressure, total perceptible water, TPW, and relative humidity), the ground station and the radio sound data were used. The R2 and REMS values of the recorded layers from the sensor and the ground data were acceptable and the sensed data were in good agreement with ground station measurements. Results show that the altitude factor play an important role in temperature measurement. The minimum amount of TPW has been recorded to be 6 mm in the Khash, Mir Java and Saravan regions in the cold season and the maximum amount of TPW has been recorded to be 49 mm in the coastal areas in the warm season. The average relative humidity in the province is in equilibrium in the cold season, while it is out of equilibrium in the hot season, so that it is above 60% on the coast of Oman and less than 10% in the central province (Khash, Mir Java and Zahedan).

کلیدواژه‌ها [English]

  • Zoning
  • Relative Humidity
  • Sistan and Baluchestan
  • Experimental Algorithm
  • MODIS Measurement
Alijani, B. (2008) Iran's Weather (8th Ed). Tehran. Payam Noor University. (In Farsi)
Alizadeh, A. (2015) Principles of Applied Hydrology (40th Ed). Imam Reza University Press. (In Farsi)
Bayat A., Mashhadizadeh Maleki S. (2019) Analysis of temporal and spatial correlation between perceptible water vapor retrievals from AIRS satellite sensor and 29 synoptic station measurements in Iran. Researches in Geographical Sciences, 19 (53), 19-32. (In Farsi).
Haji gholami, H., Mobasheri M R., Rahimzadegan M. (2017) Producing atmospheric pressure profile based on Hydrostatic hypothesis and using MODIS termal images. Journal of researches in Geographical Sciences, 4 (4), 21-32. (In Farsi)
Bani Hashem, T., Hajbi, B., Behroozian, A.R. (1998) General Meteorology, Universit  Publishing Center. (In Farsi)
Hayden, C. M. (1988) GOES-VAS simultaneous temperature-moisture retrieval algorithm. Review of. Journal of Applied Meteorology, 27, 705-733.
Ji, D., Shi, J. (2014) Water vapor retrieval over cloud cover area on land using AMSR-E and MODIS. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(7), 3105-3116.
Kaufman, Y. J., Gao, B. C. (1992) Remote sensing of water vapor in the near IR from EOS/MODIS, IEEE Transaction on Geosciences and Remote Sensing, 30, 871–884.
King, M. D., Kaufman, Y. J., Menzel, W. P., Tanre, D. (1992) Remote sensing of cloud, aerosol, and water vapor properties from the Moderate Resolution Imaging Spectrometer (MODIS). Review of IEEE Transactions on Geoscience and Remote Sensing, 30 (1), 2-27.
Li, J., (1994) Temperature and water vapor weighting functions from radiative transfer equation with surface emissivity and solar reflectivity. Review of. Advances in Atmospheric Sciences, 11 (4), 421-426.
Maghrabi, A., Al Dajani, H. (2013) Estimation of precipitable water vapour using vapour pressure and air temperature in an arid region in central Saudi Arabia. Journal of the Association of Arab Universities for Basic and Applied Sciences, 14(1), 1-8.
Mather, P.M. (1999) Computer Processing of Remotely Sensed Images. 2nd Edition, John Wiley & Sons
Merrikhpour, M.h., Rahimzadegan, M. (2019) Evaluation and Comparison of the Of the MODIS and AMSR2 Total Precipitable Water Vapor Algorithm Over Lands in the Western Part of IRAN. Journal of Iran-Water Resources Research, 14 (5), 327.-338. (In Farsi)
Mousavi Baigi, M., Ashraf, B. (2011) Weateher & Climate in Agriculture, Ferdowsi University of Mashhad Pres. (In Farsi)
NASA Website. (2016). Available at: https://ladsweb.nascom.nasa.gov.
NASA Website. (2019). Available at: http://modis.gsfc.nasa.gov/about.
Nilsson, G., Gradinarsky, L. (2006) Water Vapor Tomography Using GPS Phase Observations: Simulation Results, Ieee Transactions On Geoscimnce And Remote Sensing, 44, 2927-2941.
Peng, G., Li, J., Chen, Y., Norizan, A. P., & Tay, L (2006)High-resolution surface relative humidity computation using MODIS image in Peninsular Malaysia. Chinese Geographical Science, 16(3), 260-264.
Pour Bagher, S. M., Askari, Q., Momenzadeh, H., Manzl, P (2009) Radio Rainwater Calculation Using MODIS Satellite Data in Joe Gorganrood, Journal of Water Science Research,(1) 55-49. (In Farsi)
Rahimzadegan, M. (2013) Improvement of algorithms for extraction of local atmospheric temperature and moisture profiles using MODIS images, Ph. D. dissertation, K.N. Toosi University of Technology. (In Farsi)
Rahimzadegan, M., Mobasheri. M.R. (2013) Preparation of atmospheric temperature and humidity isopleths maps using thermal bands of MODIS satellite images. Journal of the Earth and Space Physics, 39 (3), 159-176. (In Farsi)
Seemann, S. W., Borbas, E. E., Li, J., Menzel, W. P., Gumley, L. E. (2006) MODIS Atmospheric Profile Retrieval Algorithm Theoretical Basis Document (version 6). University of Wisconsin-Madison.
Smith, W. L., Woolf, H. M., Revercomb, H. E. (1991) Linear simultaneous solution for temperature and absorbing constituent profiles from radiance spectra. Review of. Applied optics. 30 (9),1117-1123.
Zhou, F.-C. (2016) An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data. Advances in Meteorology.