امکان‌سنجی استفاده از محصولات سنجنده مودیس به‌منظور اقلیم‌شناسی آب قابل‌بارش در ایران

نوع مقاله : پژوهشی

نویسندگان

1 استاد، دانشگاه صنعتی مالک اشتر، تهران، ایران

2 دانش‌آموخته دکتری، گروه جغرافیای طبیعی، دانشکده علوم انسانی، دانشگاه تربیت مدرس، تهران، ایران

3 دانش‌آموخته دکتری، گروه جغرافیای طبیعی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران

4 دانش‌آموخته دکتری، گروه ژئودزی، دانشکده مهندسی نقشه‌ برداری، دانشگاه صنعتی خواجه نصیر الدین طوسی، تهران، ایران

چکیده

در این پژوهش به اعتبارسنجی محصولات آب قابل‌بارش سنجنده مودیس بر روی ایران پرداخته شده است. به این منظور داده‌های ماهانه سطح سوم مودیس در بازه زمانی 2003 تا 2015 و داده‌های روزانه سطح دوم، طی ماه ژانویه 2004 و ژوئیه 2008 برای محدوده ایران از وب‌سایت مودیس اخذ شد. سپس داده‌های ماهانه با داده‌های ERA-Interim و داده‌های روزانه با داده‌های رادیوسوند مورد مقایسه قرار گرفت. نتایج این پژوهش نشان می‌دهد که در مقیاس ماهانه، ویژگی‌های داده‌های آب قابل‌بارش مودیس در مقایسه با داده‌های ERA-Interim دارای الگوی فضایی خوشه‌ای‌تر، تغییرپذیری مکانی بالاتر، ارتباط فضایی قوی‌تر با داده‌های ارتفاع و میانگین آب قابل‌بارش سالانه مشابه (24/12 میلی‌متر؛ علی‌رغم اختلاف ماهانه آب قابل‌بارش) می‌باشد. این ویژگی‌ها حاکی از آن است که محصولات سنجنده مودیس، جهت اقلیم‌شناسی آب قابل‌بارش در ایران بسیار کارآمد هستند. همچنین مقایسه آب قابل‌بارش مودیس با داده‌های رادیوسوند در شرایط متفاوت جوی انجام پذیرفت. نتایج نشان داد که در شرایط آسمان صاف و همراه با دید افقی بالا، آب قابل‌بارش حاصل از محصولات مودیس و داده‌های رادیوسوند، ارتباط نزدیکی با یکدیگر دارند (ضریب تعیین=73 درصد در ژوئیه 2008). درحالی‌که ضریب تعیین در طی شرایط ابرناکی و دید افقی پایین (کمتر از 10 کیلومتر) در تمامی ایستگاه‌ها به شدت کاهش می‌یابد (ضریب تعیین=05/0 درصد در ژوئیه 2008). با توجه به این نتایج، صحت آب قابل‌بارش مودیس در مقایسه با داده‌های رادیوسوند وابسته به شرایط جوی می‌باشد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Feasibility of the use of MODIS products for climatology of precipitable water vapor over Iran

نویسندگان [English]

  • Mahdi Modiri 1
  • Mohammad Rezaei 2
  • Mahdi Khazaei 3
  • Reza Arab Sahebi 4
1 Professor, Malek Ashtar University of Technology, Tehran, Iran
2 Ph.D. Graduated, Department of Physical Geography, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran
3 Ph.D. Graduated, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran
4 Ph.D. Graduated, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran
چکیده [English]

Water vapor is the dominant greenhouse gas in the Earth’s atmosphere and, at the same time, highly variable in the atmosphere. Observations of its spatial and temporal variations is a major objective of climate. It is important in several major areas in the atmospheric sciences, on scales from turbulence to synoptic-scale systems, and including cloud formation and maintenance, radiation and climate. The intent of this paper is to demonstrate the ability of MODIS PWV products for use in monthly and daily variability of climatological scales over Iran. Therefore, the results are presented in two sections. The first section compares the long term (2003-2015) Monthly mean MODIS Level 3 and ERA-Interim PWV data sets. The second section validates the level 2 MODIS PWV products by Radiosonde daily data. For a better comparison of MODIS level 2 PWV products with Radiosonde data, we used data from 10 Radiosonde stations over Iran. We consider the sky conditions (cloudiness and visibility) in our comparison.
There are no microwave radiometers (MWR) and Global Positioning System (GPS) sites in Iran hence, in the absence of these data, we used the measurements of Radiosonde and ERA-Interim as reference data for the comparison of the MODIS PWV estimates. These data were obtained at monthly and daily scales. In the first section, long-term (2003- 2015) spatial and temporal characteristics of monthly mean PWV are investigated over Iran. For this, Level-3 MODIS terra (MOD08_M3) products and ERA-Interim data were obtained with the 1-degree resolution for Iran. In the second section, January (as a month with low values of PWV and unstable atmosphere) of 2004 and July (as a month with high values of PWV and Stable atmosphere) of 2008 were selected for comparison of MODIS daily (MOD05-L2) PWV product with Radiosonde data for 10 Radiosonde stations in Iran.
The average annual MODIS and ERA-Interim PWV data are 12.248 and 12.243 mm, respectively.These values are very close to each other. These values are also close to those derived by Asakereh et al. (2015) from NCEP data reanalysis (about 14.3 mm). Also, Ferencz and Pongra (2008) concluded that the ERA-Interim and the MODIS PWV fields are very similar.The maximum and minimum values of PWV for both data sets is observed during July and January, respectively. Tuller (1968) indicated that February and July are the months of highest and lowest precipitable water at most stations. At some, August replaces July, and at a smaller number, January replaces February. Also, our result is the same with the study of Maghrabi & Dajani, (2014) over Saudi Arabia. They reported that the lowest PWV values were in December and January, whereas the highest values were in June and July. They pointed that during warm periods, increases in the temperature and height of constant pressure levels result in an increased capacity for water vapor of the air mass, keeping it away from the saturation point and consequently preserving high PWV values. In contrast, in cold periods, the decrease in the height of constant- pressure levels, reduce the capacity for water vapor of the air mass and facilitates the condensation process, resulting in a decrease in the amount of PWV. The topography is a key factor in the spatial distribution of PWV. PWV from both data sets has a significant negative relationship with the distribution of topography in all months. This means that the concentration of PWV is high in the highland regions and vice versa. During January 2004, the ranges of errors are in the best case 5.53 mm (Tabriz) and in the worst case (Ahwaz) 16.02 mm. In all stations, the coefficient of determinations are negligible. While in the suitable weather condition, RMSE is decreased in all stations. During July of 2008 at many stations such as Zahedan, Kerman and Esfahan cloud cover and visibility condition have been appropriate, while in Bandar Abbas in all days the visibility was poor (less than 5 KM). It seems that the cloud cover and visibility conditions result in the high coefficient of determinations in Esfahan, Kerman and Zahedan (77, 80 and 66%, respectively) and with high error in Bandar Abbas station.
Annual average MODIS PWV and ERA-Interim are close to each other (12.24), in addition, MODIS has a higher negative correlation coefficient with topography compared to ERA-Interim PWV data. This suggests that MODIS level-3 monthly PWV data are valuable for the monthly long-term climatology of PWV over Iran. In daily scale, a comparison of MODIS and radiosonde PWV data in different atmospheric conditions are significantly different. During clear days with appropriate visibility (despite the time lag between two data sets) values of R2 is higher compared to cloudy days with poor visibility. Hence, accuracy of the MODIS PWV data over Iran is strongly dependent on weather conditions.

کلیدواژه‌ها [English]

  • precipitable water vapor
  • MODIS products
  • ERA-Interim
  • Radiosonde
  • Iran
پورباقر، س. م.، عسکری، ق.، مومن زاده، ح. و پاول، م.، 1388، محاسبه آب قابل‌بارش رادیوسوند با استفاده از داده‌های ماهواره‌ای MODIS در جو گرگانرود، فصلنامه تحقیقات علوم آب، 1(1)، 56-49.
صادقی حسینی، س.ع.، حجام، س. و تفنگ ساز، پ.، 1384، ارتباط آب قابل‌بارش ابر و بارندگی دیدبانی شده در منطقة تهران. م. فیزیک زمین و فضا، 31(2)، 21-13.
عساکره، ح. و دوستکامیان، م.، 1393، تغییرات زمانی و مکانی آب قابل‌بارش در جو ایران زمین. تحقیقات منابع آب ایران، 10(1)، 86-72.
علیجانی،ب.، 1392، آب و هوای ایران، انتشارات دانشگاه پیام نور.
مباشری، م.، پورباقر کردی، س.م.، فرج زاده اصل، م. و صادقی، ع.، 1389، براورد آب قابل‌بارش کلی با استفاده از تصاویر ماهواره ای MODIS و داده های رادیوساوند: ناحیه تهران، فصلنامه مدرس علوم انسانی، 14(1)، 126-107.
Albert, P., Bennartz, R., Preusker, R., Leinweber, R., and Fischer, J., 2005, Remote sensing of atmospheric water vapor using the moderate resolution imaging spectroradiometer. Journal of Atmospheric and Oceanic Technology, 22(3), 309-314.
Asakereh, H., Doostkamian, M. and Sadrafshary, S., 2015, Anomalies and cycles of precipitable water over Iran in recent decades. Arabian Journal of Geosciences, 8(11), 9569–9576. http://doi.org/10.1007/s12517-015-1888-2
Bokoye, A. I., Royer, A., O'Neill, N. T., Cliche, P., McArthur, L. J. B., Teillet, P. M., and Thériault, J. M., 2003, Multisensor analysis of integrated atmospheric water vapor over Canada and Alaska. Journal of Geophysical Research: Atmospheres, 108(D15).
Bokoye, A. I., Royer, A., O'Neill, N. T., Cliche, P., McArthur, L. J. B., Teillet, P. M. and Thériault, J. M., 2003, Multisensor analysis of integrated atmospheric water vapor over Canada and Alaska. Journal of Geophysical Research: Atmospheres, 108(D15).
Chen, S.-H., Zhao, Z., Haase, J. S., Chen, A. and Vandenberghe, F., 2008, A Study of the Characteristics and Assimilation of Retrieved MODIS Total Precipitable Water Data in Severe Weather Simulations. Monthly weather review, 136, 3608–3628. http://doi.org/10.1175/2008MWR2384.1
Dupont, J. H., 2008, Parametric model to estimate clear-sky long wave irradiance at the surface on the basis of vertical distribution of humidity and temperature. J. Geophys. Res., 113, D07203.
Ferencz, C. and Pongra, R., 2008, Estimation of vertically integrated water vapor in Hungary using MODIS imagery, 41, 1933–1945. http://doi.org/10.1016/j.asr.2007.06.048.
Gao, B. C. and Kaufman, Y. J., 2003, Water vapor retrievals using Moderate Resolution Imaging Spectroradiometer (MODIS) near‐infrared channels. Journal of Geophysical Research: Atmospheres, 108(D13), 4389-4398.
Gao, B.-C. and Yoram J., K., 1992, The MODIS Near-IR Water Vapor Algorithm Product ID : MOD05 - Total Precipitable Water. Algorithm Technical Background Document, 1–25. Retrieved from Biblioteca_Digital_SPRGao1992_ATBD.pdf
Http://weather.uwyo.edu/upperair/sounding.html.
Kern, A., Bartholy, J., Borbás, É. E., Barcza, Z., Pongrácz, R. and Ferencz, C., 2008, Estimation of vertically integrated water vapor in Hungary using MODIS imagery. Advances in space research, 41(11), 1933-1945.
King, M. D., Kaufman, Y.J., Menzel, W.P. and Tanre, D., 1992, Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer(MODIS). IEEE transactions on geoscience and remote sensing, 30(1), 2-27.
King, M. D., M. W., 2003, Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS. IEEE Transactions on Geoscience and Remote Sensing. IEEE Transactions on Geoscience and Remote Sensing, 41, 442–458.
Li, Z., Muller, J.P. and Cross, P., 2003, Comparison of precipitable water vapor derived from radiosonde, GPS, and Moderate‐Resolution Imaging Spectroradiometer measurements. Journal of Geophysical Research: Atmospheres, 108(D20).
Maghrabi, A. H. and Dajani, H. M. Al., 2014, ScienceDirect Time distribution of the precipitable water vapor in central Saudi Arabia and its relationship to solar activity. Advances in Space Research, 53(8), 1169–1179. http://doi.org/10.1016/j.asr.2014.02.006
Marsden, D. and Valero, F.P., 2004, Observation of water vapor greenhouse absorption over the Gulf of Mexico using aircraft and satellite data. Journal of the atmospheric sciences, 61(6), 745-753.
McGregor, G.R. and Nieuwolt, S., 1998, Tropical climatology: an introduction to the climates of the low latitudes (No. Ed. 2). John Wiley & Sons Ltd.
Mockler, S. B., 1995, Water vapor in the climate system. . Amer.Geophys. Union Special Rep., 50-63.
Ohmura, A. and Wild, M., 2002, Is the hydrological cycle accelerating?. Science, 298(5597), 1345-1346.
Kassomenos, P.A. and McGregor, G.R., 2006, The interannual variability and trend of precipitable water over southern Greece. Journal of Hydrometeorology, 7(2), 271-284.
Prasad, A. K. and Singh, R. P., 2009, Validation of MODIS Terra, AIRS, NCEP/DOE AMIP-II Reanalysis-2, and AERONET Sun photometer derived integrated precipitable water vapor using ground-based GPS receivers over India. Journal of Geophysical Research Atmospheres, 114(5), 1–20. http://doi.org/10.1029/2008JD011230.
Seemann, S.W., Li, J., Menzel, W.P. and Gumley, L.E., 2003, Operational retrieval of atmospheric temperature, moisture, and ozone from MODIS infrared radiances. Journal of applied meteorology, 42(8), 1072-1091.
Sohn, B. J. and Smith, E.A., 2003, Explaining sources of discrepancy in SSM/I water vapor algorithms. Journal of climate, 16(20), 3229-3255.
Sudradjat, A., Ferraro, R. R. and Fiorino, M., 2005, A comparison of total precipitable water between reanalyses and NVAP. Journal of climate, 18(11), 1790-1807.
Thies, B. and Bendix, J., 2011, Satellite based remote sensing of weather and climate: Recent achievements and future perspectives. Meteorological Applications, 18(3), 262–295. http://doi.org/10.1002/met.288
Trenberth, K.E. and Stepaniak, D.P., 2003, Covariability of components of poleward atmospheric energy transports on seasonal and interannual timescales. Journal of climate, 16(22), 3691-3705.
Trenberth, K. E., 1999, Atmospheric moisture recycling: Role of advection and local evaporation. J. Climate, 12, 1368–1381.
Trenberth, K. E., 2004, Manifestations of global climate change on accelerating the hydrological cycle: Prospects for increases in extremes. Proc. Second Int. CAHMDA Workshop on the Terrestrial Water Cycle: Modelling and Data Assimilation across Catchment Scales. Princeton, NJ,, 37–39.
Tuller, S.E., 1968, World distribution of mean monthly and annual precipitable water. Monthly weather review, 96(11), 785-797.
Wagner, T., Heland, J., Zöger, M. and Platt, U., 2003, A fast H 2 O total column density product from GOME–Validation with in-situ aircraft measurements. Atmospheric Chemistry and Physics, 3(3), 651-663.
Wang, H., Wei, M., Li, G., Zhou, S. and Zeng, Q., 2013, Analysis of precipitable water vapor from GPS measurements in Chengdu region : Distribution and evolution characteristics in autumn. Advances in Space Research, 52(4), 656–667. http://doi.org/10.1016/j.asr.2013.04.005.
Wu, P., Hamada, J.I., Mori, S., Tauhid, Y.I., Yamanaka, M.D. and Kimura, F., 2003, Diurnal variation of precipitable water over a mountainous area of Sumatra Island. Journal of Applied Meteorology, 42(8), 1107-1115.