پایش ماهواره‌ای توزیع زمانی- مکانی آب بارش‌شُو در جوّ ایران با استفاده از داده‌های Aqua/AIRS

نوع مقاله : مقاله تحقیقی‌ (پژوهشی‌)

نویسنده

استادیار اقلیم شناسی، گروه جغرافیا، دانشگاه زنجان، زنجان، ایران

چکیده

آب بارش‌شُو یکی از فراسنج‌های مهم در مطالعات هواشناسی و فیزیک ابر است که نقش مهمی در پیش­بینی هوا و بارش دارد. در این مطالعه از داده­های آب بارش‌شُو سنجنده AIRS مستقر بر ماهواره Aqua، با گام­های زمانی ماهانه و مکانی °°1 برای دوره آماری سال­های 2019–2003 استفاده شد. پس از کنترل کیفی و پیش­پردازش داده­های استخراج­شده، از نرم‌افزار­های تخصصی مانند ArcGIS،ENVI  و Grads برای ساخت لایه­‌های شبکه‌ای، برداری و جداول اطلاعاتی بر اساس مرز جغرافیایی کشور ایران استفاده شد. داده­ها رقومی بودند و مقدار عددی آنها برابر میزان آب بارش‌شُو برحسب میلی‌متر (mm) به ازای هر پیکسل یا یاخته بود که برای مشاهدات سالانه، فصلی و سالانه برآورد شد. بر اساس نتایج، میانگین آب بارش‌شُو در جوّ ایران mm 13 ‌است که در مقایسه با میانگین آب بارش‌شُو جوّ جهانی (mm 22)، کم بودن مقدار آب بارش‌شُو را در جوّ ایران نشان می­دهد. از سوی دیگر، میزان آب بارش‌شُو در جوّ ایران توزیع زمانی و مکانی همگنی ندارد به‌طوری­که در میان ماه­های بررسی­شده، بیشترین میزان مربوط به ماه ژولای و کمترین میزان مربوط به ماه ژانویه است. در میان فصول، بیشترین مقدار آب بارش‌شُو در فصل تابستان و کمترین میزان آن در فصل زمستان برآورد شد. به لحاظ مکانی نیز کمترین میزان آب بارش‌شُو بر فراز سلسله جبال زاگرس و بیشترین میزان آن در نواحی ساحلی جنوب و شمال متمرکز است. رفتار آب بارش‌شُو جوّ ایران در طول سری زمانی حاکی از افزایشی بودن روند آن است. روند افزایشی آب بارش‌شُو می­تواند بازخورد افزایش دما در پهنه ایران تلقی شود و بررسی آن از منظر تغییر اقلیم نیز اهمیت دارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Monitoring of Temporal-Spatial Distribution of Precepitable Water (PW) in Iranian Atmosphere Using Aqua/AIRS Data

نویسنده [English]

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

Precepitable Water (PW) which is one of the most important variables studied in meteorology and cloud physics, plays an important role in predicting air and rainfall. In this study, AIRS's sensor Aqua satellite PW data were used with monthly and spatial time steps of 1°´1° for the statistical period of 2003-2019. The AIRS sensor is one of the six Aqua satellite sensors designed to help researchers to investigate change of climate and improve air forecasting. The sensor has a very wide range of resolution, which is tens of times more powerful than similar devices before it. The extracted data, after qualitative control and pre-processing, were used by specialized softwares such as ENVI, ArcGIS and Grads to build raster, vector and information tables based on the geographical boundary of Iran. The data used are numerical and their numerical values are the amount of PW in millimeters (mm) per pixel or cell that was estimated for annual, sesonal and monthly observations. The average PW in the atmosphere of Iran is 13 mm, which is lower than the average PW of the global atmosphere (22 mm). On the other hand, the amount of PW in the atmosphere of Iran does not have a homogeneous time and space distribution. So, among the studied months, the highest amount is related to July and the lowest amount is related to January. Among the seasons, the highest (lowest) amount of PW was estimated in summer (winter). Meanwhile, local factors such as remoteness and proximity to moisture sources, play an important role in the distribution of PW in the atmosphere prevailing in Iran. According to the observations, the prevailed atmosphere over the heights (especially the Zagros mountains) has very low PW concentration, in contrast to the coastal shores of the Persian Gulf, Oman Sea and Caspian Sea. It is because of having huge sources of moisture nutrition in the regions with the highest rainfall in Iran. However, the amount of PW in the atmosphere of Iran is more dependent on topography, distance, and proximity to moisture sources than on latitude (as opposed to global distribution). On the other hand, the PW behavior of the atmosphere of Iran over time, indicates that its trend is increasing. In addition to being a form of feedback on rising temperatures across Iran, the increasing trend of PW is also important in terms of climate change.

کلیدواژه‌ها [English]

  • Precepitable Water
  • AIRS Sensor
  • Temporal-Spatial Distribution
  • atmosphere of Iran’s
بیات، ع.، مشهدی زاده، س.، 1398، تحلیل همبستگی مکانی و زمانی بین بخار آب بارش‌شُو سنجنده AIRS وداده­های 92 ایستگاه سینوپتیک ایران: نشریه تحقیقات کاربردی علوم جغرافیایی، 19(35)، 19-32.
دهقانی، ط.، سلیقه، م.، علیجانی، ب.، 1397، اثر تغییر اقلیم بر میزان آب قابل بارش در سواحل شمال خلیج فارس: نشریه تحقیقات کاربردی علوم جغرافیایی، ۱۸(۴۹)، ۷۵-91.
رسولی، ع. ا .، جهانبخش، س.، قاسمی، ا. ر.، 1393، بررسی ارتباط بین پارامترهای مهم ابر و بارش روزانه در ایران: فصلنامه تحقیقات جغرافیایی، 29(1)، ۲۳-42.
صادقی حسینی، س. ع.، حجام، س.، تفنگ ساز، پ.، ۱۳۸۴، ارتباط آب بارش‌شُو ابر و بارندگی دیدبانی­شده در منطقه تهران: مجلۀ فیزیک زمین و فضا، 31(2)، ۱۳-۲۱.
عساکره، ح.، دوستکامیان، م.، 1394، بررسی نقش عوامل مکانی بر توزیع پراکندگی بیشینه­های آب بارش‌شُو جوّ ایران: مجلهتحقیقات کاربردی علوم جغرافیایی، 15(32)، 7–24.
 عساکره، ح.، دوستکامیان، م.، قائمی، هـ .، 1393، تحلیل تغییرات ناهنجاری­ها و چرخه­های آب بارش‌شُو جوّ ایران: فصلنامه پژوهش­های جغرافیای طبیعی، 46(4)، 435–444.
قاسمی، ا. ر.، ۱۳۹۱، مدل­سازی تغییرات زمانی و مکانی پوشش ابری، با تأکید بر روزهای بارش در ایران: رساله دکتری رشته جغرافیای طبیعی گرایش اقلیم شناسی، دانشگاه تبریز.
محمدی‌ها، ا.، معماریان، م. ح.، آزادی، م.، ریحانی پروری، م.، 1393، بررسی پیش‌بینی­های مدل WRF برای آب بارش‌شو و ارتباط آن با برآورد بارش به کمک داده­های رادار تهران: مجله ژئوفیزیک ایران، 3(22)، 1–13.
نجفی، د.، ۱۳۸۳، محاسبه آماری حداکثر بارش محتمل ۲۴ ساعته و حداکثر آب بارش‌شُو ایستگاه اصفهان: دومین کنفرانس دانشجویی منابع آب و خاک، دانشگاه شیراز.
Adeyemi, B., and Joerg, S., 2012, Analysis of water vapor over Nigeria using radiosonde and satellite data: Journal of Applied Meteorology and Climatology, 51(10), 1855-1866.
Alshawaf, F., Balidakis, K., Dick, G., Heise, S., and Wickert, J., 2017, Estimating trends in atmospheric water vapour and temperature time series over Germany: Journal of Atmosphere, 10, 3117-3132.
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.
Bedka, S., Knuteson, R., Revercomb, H., Tobin, D., and Turner, D., 2010, An assessment of the absolute accuracy of the Atmospheric Infrared Sounder v5 precipitable water vapor product at tropical, midlatitude, and arctic ground‐truth sites: September 2002 through August 2008: Journal of Geophysical Research: Atmospheres, 115(17), 241-256.
Bender, M., Dick, G., Wickert, J., Schmidt, T., Song, S., Gendt, G., Ge, M., and Rothacher, M., 2008, Validation of GPS slant delays using water vapour radiometers and weather models: Meteorologische Zeitschrift, 17(7), 807–812.
Benevides, P., Catalao, J., and Miranda, P. M. A., 2015, On the inclusion of GPS precipitable water vapor in the nowcasting of rainfall: Natural Hazards and Earth System Sciences, 15(21), 2605–2616.
Bengtsson, L., Hagemann, S., and Hodges, K. I., 2004, Can climate trends be calculated from reanalysis data?: Journal of Geophysical Research: Atmospheres, 109, D11, https://doi.org/10.1029/2004JD004536.
Bennitt, G. V., and Jupp, A., 2012, Operational assimilation of GPS zenith total delay observations into the met office numerical weather prediction models: Monthly Weather Review, 140, 2706–2719.
Bevis, M., Businger, S., Herring, T. A., Rocken, C., Anthes, R. A., and Ware, R. H., 1992, GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system: Journal of Geophysical Research: Atmospheres, 97(8), 15787–15801.
 
Bock, O., Keil, C., Richard, E., Flamant, C., and Bouin, M. N., 2005, Validation of precipitable water from ECMWF model analyses with GPS and radiosonde data during the MAP SOP: Quarterly Journal of the Royal Meteorological Society, 131, 3013–3036.
Bolsenga, S. J., 1965, The relationship between total atmospheric water vapor and surface dew point on a mean daily and hourly basis: Journal of Applied Meteorology, 4, 430–432.
Bretherton, H. S., Matthew, E. P., and Larissa, E. B., 2004, Relationships between Water Vapor Path and Precipitation over the Tropical Oceans: Journal of Climate, 17 ,1517-1528.
Campmany, E., Bech, J., Rodríguez-Marcos, J., Sola, Y., and Lorente, J., 2010, A comparison of total precipitable water measurements from radiosonde and sunphotometers: Atmospheric Research, 97, 385-392.
Campos-Arias, P., Esquivel-Hernández, G., Valverde-Calderon, J. F., Rodríguez-Rosales, S., Moya-Zamora, J., Sanchez-Murillo, R., and Boll, J., 2019, GPS Precipitable Water Vapor estimations over Costa Rica: A Comparison against atmospheric sounding and Moderate Resolution Imaging Spectrometer (MODIS): Climate, 7, 63-76.
Chang-Geun, P., Kyoung-Min, R., and Jungho, C., 2012, Radiosonde sensors bias in precipitable water vapor from comparisons with global positioning system measurements: Journal of Astronomy and Space Sciences, 29(3), 295-303.
Chen, B., and Liu, Z., 2016, Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite: Journal of Geophysical Research: Atmospheres, 121(11), 442-462.
Diedrich, H., Wittchen, F., Preusker, R., and Fischer, J., 2016, Representativeness of total column water vapour retrievals from instruments on polar orbiting satellites: Atmospheric Chemistry and Physics, 16, 8331–8339.
Elgered, G., and Jarlemark, P. O., 1998, Ground-based microwave radiometry and long-term observations of atmospheric water vapor: Radio Science, 33(7), 707–717.
Falaiye, O. A., Abimbola, O. J., Pinker, R. T., and Willoughby, A. A., 2018, Multi-technique analysis of precipitable water vapor estimates in the sub-Sahel West Africa: Heliyon, 4 ,756.
Fujibe, F., 2016, Annual variation of extreme precipitation intensity in Japan: Assessment of the validity of Clausius-Clapeyron scaling in seasonal change: Scientific Online Letters on Atmosphere, 12, 106–110.
Fujita, M., and Sato, T., 2017, Observed behaviours of precipitable water vapour and precipitation intensity in response to upper air profiles estimated from surface air temperature: Scientific Reports, 7(3-4),4233.
Fujita, M., Wada, A., Iwabuchi, T., and Rocken, C., 2012, GPS precipitable water vapor dataset for climate science: Proceedings of the 25th international technical meeting of the satellite division of the Institute of Navigation, 19, 3454–3458.
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, 1007–1021.
Gendt, G., Dick, G., Reigber, C., Tomassini, M., Liu, Y., and Ramatschi, M., 2004, Near real time GPS water vapor monitoring for numerical weather prediction in Germany: Journal of Meteorological Society of Japan, 82, 361–370.
Gui, K., Che, H., Chen, Q., Zeng, Z., Liu, H., Wang, Y., Zheng, Y., Sun, T., Liao, T., and Wang, H., 2017, Evaluation of radiosonde, MODIS-NIR-Clear, and AERONET precipitable water vapor using IGS ground-based GPS measurements over China: Atmospheric Research, 197, 461–473.
Haas, R., Elgered, G., Gradinarsky, L., and Johansson, J. M., 2003, Assessing long term trends in the atmospheric water vapor content by combining data from VLBI, GPS, radiosondes and microwave radiometry: Proceedings of the 16th working meeting on European VLBI for geodesy and astrometry, edited by: Schwegmann, W. and Thorandt, V., Bundesamt für Kartographie and Geodäsie, 9–10 May 2003, Frankfurt/Leipzig, Germany, 14, 279–288.
Hagan, D. E., Webster, C. R., Farmer, C. B., May, R. D., Herman, R. L., Weinstock, E. M., and Newman, P. A., 2004, Validating AIRS upper atmosphere water vapor retrievals using aircraft and balloon in situ measurements: Geophysical Research Letters, 31(21), 217-242.
Hausmann, P., Sussmann, R., Trickl, T., and Schneider, M., 2017, A decadal time series of water vapor and D/H isotope ratios above Zugspitze: transport patterns to central Europe: Atmospheric Chemistry and Physics, 17, 7635–7651.
Heise, S., Dick, G., Gendt, G., Schmidt, T., and Wickert, J., 2009, Integrated water vapor from IGS ground-based GPS observations: initial results from a global 5-min data set: Annals of Geophysics, 27, 2851–2859.
Jade, S., and Vijayan, M., 2008, GPS-based atmospheric precipitable water vapor estimation using meteorological parameters interpolated from NCEP global reanalysis data: Journal of Geophysical Research: Atmospheres, 113(10), 1029.
Jiang, J., Zhou, T., and Zhang, W., 2019, Evaluation of satellite and reanalysis precipitable water vapor data sets against radiosonde observations in Central Asia: Earth and Space Science, 10,1029.
Kanemaru, K., and Masunaga, H. A., 2013, satellite study of the relationship between sea surface temperature and column water vapor over tropical and subtropical oceans: Journal of Climate, 26, 4204–4218.
Kristin, K., Brin, G., 2008, Global positioning system (GPS) perceptible water in forecasting lightning at spaceport Canaveral: Weather Forecasting, 23, 219 – 232.
Kumar, S., Allan, R. P., Zwiers, F., Lawrence, D. M., and Dirmeyer, P. A., 2015, Revisiting trends in wetness and dryness in the presence of internal climate variability and water limitations over land: Geophysical Research Letters, 42, 10867–10875.
Lee, M. I., Schubert, S. D., Suarez, M. J., Held, I. M., Lau, N. C., Plushy, J. J., Kumar, A., Kim, H. K., and Schema, J. K. E., 2007, An analysis of the warm-season diurnal cycle over the continental United States and northern Mexico in general circulation models: Journal of Hydrometeorology, 8(3), 344–366.
Lenderink, G., and van Meijgaard, E. V., 2010, Linking increases in hourly precipitation extremes to atmospheric temperature and moisture changes: Environmental Research Letters, 5, 025208.
Li, X., Tan, H., Dick, G., Wickert, J., and Schuh, H., 2018, Real-time sensing of precipitable water vapor from BeiDou observations: Hongkong and CMONOC networks: Journal of Geophysical Research: Atmospheres, 123, 212-221.
Loriaux, J. M., Lenderink, G., Roode, S. R. D., and Siebesma, A. P., 2013, Understanding convective xtreme precipitation scaling using observations and an entraining plume model: Journal of the Atmospheric Sciences, 70, 3641–3655.
Lu, N., Qin, J., Yang, K., Gao, Y., Xu, X., and Koike, T., 2011, On the use of GPS measurements for moderate resolution imaging spectrometer precipitable water vapor evaluation over southern Tibet: Journal of Geophysical Research, 16(D23), 1–7.
Luo, X., Mayer, M., and Heck, B., 2008, Extended neutrospheric modeling for the GNSS-based determination of high-resolution atmospheric water vapor fields: Boletim de Ciencias Geodesicas., 14, 149–170.
Maghrabi, A., and Al Dajani, H. M., 2012, 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, 1-8.
Moteki, N., and Kondo, Y., 2013, A new theoretical method for calculating temperature and water vapor saturation ratio in an expansion cloud chamber: Journal of Geophysical Research: Atmospheres, 118, 6627-6633.
Nilsson, T., and Elgered, G., 2008, Long-term trends in the atmospheric water vapor content estimated from groundbased GPS data: Journal of Geophysical Research: Atmospheres, 113, D19101.
Ning, T., Wickert, J., Deng, Z., Heise, S., Dick, G., Vey, S., and Schone, T., 2016, Homogenized time series of the atmospheric water vapor content obtained from the GNSS reprocessed data: Journal of Climate, 29, 2443–2456, https://doi.org/10.1175/JCLI-D-15- 0158.1.
Ojo, O., 2006, The distribution of mean monthly precipitable water vapor and annual precipitation efficiency in Nigeria: Theoretical and Applied Climatology, 18, 221-238.
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(D5).
Raja, M. R. V., Gutman, S. I., Yoe, J. G., McMillin, L. M., and Zhao, J., 2008, The validation of AIRS retrievals of integrated precipitable water vapor using measurements from a network of ground-based GPS receivers over the contiguous United States: Journal of Atmospheric and Oceanic Technology, 25(3), 416-428.
Sharifi, M. A., Khaniani, A. S., and Joghataei, M., 2015, Comparison of GPS precipitable water vapor and meteorological parameters during rainfalls in Tehran: Meteorology and Atmospheric Physics, 127(6), 701-710.
Sherwood, S. C., Roca, R., Weckwerth, T. M., and Andronova, N. G., 2010, Tropospheric water vapor, convection, and climate: Reviews of Geophysics, 48(15), 2001.
Sun, L., Shen, B., and Sui, B., 2010, A study on water vapor transport and budget of heavy rain in northeast China: Advances in Atmospheric Sciences, 27(6), 1399–1414.
van der Ent, R. J., and Tuinenburg, O. A., 2017, The residence time of water in the atmosphere revisited: Hydrology and Earth System Sciences, 21, 779–790.
Vaquero-Martínez, J., Antón, M., Ortiz de Galisteo, J., Cachorro, V., Costa, M., Román, R., and Bennouna, Y., 2017, Validation of MODIS integrated water vapor product against reference GPS data at the Iberian Peninsula: International Journal of Applied Earth Observations and Geoinformation, 63, 214–221.
Vaquero-Martínez, J., Anton, M., Ortiz de Galisteo, J. P., Cachorro, V. E., Alvarez-Zapatero, P., Roman, R., Loyola, D., Costa, M. J., Wang, H., and Gonzalez Abad, G., 2018, Inter-comparison of integrated water vapor from satellite instruments using
reference GPS data at the Iberian Peninsula: Remote Sensing Of Environment, 204, 729–740.
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, 656–667.
Willoughby, A. A., Adimula, I. A., Aro, T. O., and Owolabi, I. E., 2008, Analysis of radiosonde data on tropospheric water vapor in Nigeria: Journal of Physics, 20(2), 299-308.
You, Q., Jiang, Z., Bao, Y., Pepin, N., and Fraedrich, K., 2016, Trends in upper tropospheric water vapour over the Tibetan Plateau from remote sensing: International Journal of Climatology, 36, 4862.
Zehang, J., Shi chuch, X., Lu, Q., Xie, Z., 2010, Evaluation of total perceptible water over east Asia from FY-3A/VIRR infrared radiances: Atmospheric and Oceanic Letters, 3, 93 – 99.
Zhang, X., Li, M., and Sun, T., 2013, Spatiotemporal variation of water vapor in upper troposphere over Central Asia based on AIRS satellite retrieval (in Chinese): Arid Zone Research, 30(6), 951–957.
Zhang, Y., Wang, D., Zhai, P., and Gu, G., 2012, Applicability of AIRS monthly mean atmospheric water vapor profiles over the Tibetan Plateau region: Journal of Atmospheric and Oceanic Technology, 29(11), 1617–1628.