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پیشبینی رخداد مه به کمک برخی روشهای تجربی (فرودگاههای تهران و مشهد) | ||
فیزیک زمین و فضا | ||
مقاله 9، دوره 44، شماره 2، تیر 1397، صفحه 379-395 اصل مقاله (1.12 M) | ||
شناسه دیجیتال (DOI): 10.22059/jesphys.2017.234790.1006906 | ||
نویسندگان | ||
سحر تاج بخش* 1؛ محمد مرادی2؛ مهدی رشیدزاد3؛ محمدرضا محمدپور پنچاه3 | ||
1استادیار، گروه کاوشهای جوی، پژوهشکده هواشناسی، تهران، ایران | ||
2استادیار، گروه هواشناسی هوانوردی، پژوهشکده هواشناسی، تهران، ایران | ||
3کارشناس ارشد هواشناسی، پژوهشکده هواشناسی، تهران، ایران | ||
چکیده | ||
مه یکی از پدیدههای وضع هواست که در نشست و برخاست هواپیماها، به سبب کاهش دید، نقش مهمی دارد. در این مطالعه سعی شده است در دو فرودگاه مهرآباد تهران و شهید هاشمینژاد مشهد، ضمن ارائۀ الگوهای همدیدی شرایط مهآلود، روشی به منظور بهبود حدس اولیه برای پیشبینی مه ارائه شود. با در نظر گرفتن دادههای موجود، 25 مطالعۀ موردی برای رخداد مه به کمک دو روش تجربی متداول (سندرس و کروداک-پریچارز) در فرودگاههای یادشده بررسی و دمای نقطۀ مه با دادههای واقعی و پیشبینی تعیین شد. الگوهای همدیدی در حالتهای موردی معرف حضور پرفشار قوی با مقادیر حداقل 1020 هکتوپاسکال در نوار شمالی ایران است که با فرارفت هوای سرد تراز 850 هکتوپاسکال، بادهای شمالی و نم ویژۀ 6 تا 8 گرم بر کیلوگرم همراه است. ارزیابی به روش بایاس نشان داد که روش سندرس در 75% حالات با رخداد مه در فرودگاههای یادشده همخوانی دارد. این ارزیابی برای روش کروداک-پریچارز به 65% کاهش یافت. با هدف استفاده از این روشها برای پیشبینی رخداد مه، روشهای یادشده به کمک خروجیهای مدل پیشبینی عددی WRF نیز مطالعه شد و ارزیابی نتایج صحت کمتری (50%) را نشان داد. از این رو به نظر میرسد روش تجربی سندرس برای حدس اولیۀ رخداد مه روش مناسبی باشد و در صورت افزایش صحت و دقت خروجیهای مدل پیشبینی عددی برای 12 ساعت آینده قابل استفاده است. | ||
کلیدواژهها | ||
حداقل دید فرودگاه؛ دمای نقطۀ مه؛ روش سندرس؛ مه؛ مدل پیشبینی عددی WRF | ||
عنوان مقاله [English] | ||
Forecasting fog using some experimental methods (Tehran and Mashhad airports) | ||
نویسندگان [English] | ||
Sahar Tajbakhsh1؛ Mohammad Moradi2؛ Mehdi Rashidzad3؛ mohammadreza Mohammadpur Panja3 | ||
1Assistant Professor, Atmospheric Survey Research Group, Atmospheric Science and Meteorological Research Center(ASMERC), Tehran, Iran | ||
2Assistant Professor, Aeronautical Meteorology Group, Atmospheric Science and Meteorological Research Center(ASMERC), Tehran, Iran | ||
3M.Sc. in Meteorology, Atmospheric Science and Meteorological Research Center(ASMERC), Tehran, Iran | ||
چکیده [English] | ||
Fog is among the most important weather hazards from the aviation perspective. This phenomenon can substantially lead to horizontal visibility reduction. Therefore, accurate prediction is essential for flight safety and easing air traffic. Fog consists of a weather condition in which water drops and ice crystals reduce the horizontal visibility to less than 1000 meters. Various methods are suggested for fog forecasting. Numerical and statistical methods, experimental approaches, and very short range fog forecasting are some of the most common methods. Experimental methods are commonly used for first guess in forecasting centers. Saunders technique is one of the forecasting methods for radiation fogs using radio sounds data. Although this technique goes back to many years ago, it is being used in many parts of the world, including UK Met Office, and is recommended by World Meteorological Organization. Present study tries to evaluate the performance of two experimental methods using real data after studying synoptic condition of fog occurrence in two selected airports. The validity of them is then measured with the real occurrence in a number of case studies of fog occurrence for the selected airports using the bias technique in order to choose the more appropriate method. In the next step, the more appropriate method is administered using the numerical prediction model output and is again evaluated with the bias technique. In both these methods, an index called fog point temperature has been used, and the fog occurrence has been determined by calculating this temperature and comparing it with the minimum temperature. The selected airports are Mehrabad Airport, Tehran and Shahid Hasheminezhad Airport, Mashhad, which have been chosen because of high flight traffic (in Tehran) and high fog occurrence (in Mashhad). Experimental methods examined in this study are Saunders and Prichars-Crodack techniques, which 25 case studies in selected Airports tried to offer the best results for first guess of fog occurrence. The accuracy of these relations was evaluated comparing real conditions using Bias technique. After choosing the more appropriate method, a similar process has been carried out using numerical prediction model of WRF for the next 12 hours. Results of synoptic evaluations show that high-pressure systems are a major factor in creating coldness in lower levels of the atmosphere. Evaluation of pressure field in this study doesn't show figures below 1020 hPa. Specific humidity values were 6-8 g/kg and 4-6 g/kg for 1000 and 925 hPa levels respectively. Winds are frequently northern or eastern and cold weather advection is seen in selected stations. In Saunders technique, using radio sound data of 1200 UTC in 25 case studies for mentioned airports, the fog point is calculated. This temperature is then compared with next day's minimum temperature and if the difference is less than -2°C, fog occurrence would be ruled out. Saunders considers this method mostly useful for radiation fog. In Crodack-Prichars technique, which is performed by creating a regression association between temperature and dew point temperature, the fog point temperature is determined. Here again, fog is not formed If the temperature difference is less than -2°C. After calculating fog point temperature using Saunders technique and comparing it with actual observation, it was found that among 25 cases, 15 fog observations were consistent with Saunders technique calculations. In the five cases of fog nonoccurrence, the results of this method were consistent with reality. So, Bias evaluation technique shows 75% for probability of detection. The same process has been carried out for Crodack-Prichars technique. In this method, a linear relationship exists between temperature, due point temperature, and fog point temperature. Wind condition and cloudiness are also presented experimentally in the form of a table. For different amounts of these two factors, a numerical amount of 1.5 to -1.5 is added to the fog point temperature. Fog occurrence is determined by calculating fog point temperature using Crodack-Prichars technique and comparing it with the minimum temperature according to table 2. This evaluation showed that in 13 of 20 fog occurrence cases, the right answer were obtained, and 5 cases of fog nonoccurrence, were consistent with reality. Therefore, POD index was reduced to 65%. Based on the results, Saunders technique has been considered as the more appropriate method for initial guessing in fog forecasting in the airports under study. Now, the values of temperature and due point temperature were determined for the next 12 hours using WRF numerical prediction model, and Saunders technique was used again for predicting fog (using predicted data). The results of this evaluation were also investigated using Bias evaluation technique, which were not so agreeable, so that it was consistent with reality in 50% of cases. Hence, it seems that careful consideration of numerical prediction models output is needed. | ||
کلیدواژهها [English] | ||
fog, Sanders Method, fog point, WRF numerical weather prediction | ||
مراجع | ||
تاج بخش، س.، 1395، مطالعۀ آماری و شناسایی نوع مه به کمک یک الگوریتم در مهمترین فرودگاههای کشور، بولتن پژوهشهای اقلیم شناسی (در دست انتشار). حجام، س.، برخورداری، ج. و مشکوتی الف.، ح.، 1393، تعیین مناسبترین شبکهی عصبی مصنوعی برای پیشبینی کوتاه مدت مه در فرودگاه ارومیه، مجموعه مقالات سومین کنفرانس ملی تصادفات جادهای، سوانح ریلی و هوایی، زنجان، ایران.
Cimini, D., Caumont, O., Löhnert, U., Alados-Arboledas, L., Bleisch, R., Huet, T., Ferrario, M. E., Madonna, F., Haefele, A., Nasir, F., Pace, G. and Posada, R., 2014, A data assimilation experiment of temperature and humidity profiles from an international 1 network of groundbased microwave radiometers, Proc. Microrad 2014, Pasadena, USA, 24-27 March, 2014. Chen, F. and Dudhia, J., 2001, Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Review 129 (4), 569-585. Cradock, J. M. and Prichars, D. L., 1951, forecasting the formation of radiation fog — a preliminary approach. Meteorological Research Paper No. 624. Meteorological Office (unpublished). Dejmal, K. and Repal, V., 2010, Implementation of methods for the radiation fog prediction, International Journal of Energy and environment, 4, 79-88. Doran, J. A., Rohr, P. J., Beberwyk, D. J., Brooks, G. R., Gayno, G. A., Williams, R. T., Lewis, J. M. and Lefevre, R. J., 1999, TheMM5at the AF Weather Agency—New products to support military operations. Preprints, Eighth Conf. on Aviation, Range, and Aerospace Meteorology, Dallas, TX, Amer. Meteor. Soc., 115–119. Dudhia, J., 1989, Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two–dimensional model. J. Atmos. Sci., 46, 3077–3107. Erik, M. B., Mitchell, K. E., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G. and Tarpley, J. D., 2003, Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. Journal of Geophysical Research atmosphere, 108, (22), 8851. Glenn Creighton, G., Kuchera, E., Adams-Selin, R., McCormick, J., Rentschler, S. and Wickard, B., 2014, AFWA Diagnostics in WRF, U.S.A. Hansen, B., 2007, a Fuzzy Logic–Based Analog Forecasting System for Ceiling and Visibility, Weather and Forecasting, 22, 1319-1330. Hong, S. Y, Dudhia, J. and Chen, S. H., 2004, A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103–120. Hong, S., Noh, Y. and Dudhia, J., 2006, A new vertical di_usion package with an explicit treatment of entrainment processes. Monthly Weather Review 134 (9), 2318-2341. Holtslag, M. C., Steeneveld, G. J. and Holtslag A. A. M., 2010, Fog forecasting: “old fashioned”semi-mpirical methods from radio sounding observations versus “modern” numerical models, 5th International Conference on Fog, Fog Collection and Dew Münster, Germany, 25–30 July 2010. Hyvarinen, O., Erola, K., Siljamo, N. and Koskenin, J., 2009, Comparison of Snow Cover from Satellite and Numerical Weather Prediction Models in the Northern Hemisphere and Northern Europe, Journal of Appley Meteorology and Climatology, 48, 1199-1216. ICAO, 2010, Technical specifications related to meteorological observations and reports: Annex 3 International Civil Aviation Organization, Montreal, Canada. International Civil Aviation Organization, 2016, Aeronautical information services: Annex 15, ICAO publication, Montreal, Canada. Iran airports and air navigation companies, 2017, Aeronautical Information publications (AIP). Jacobs, W., Nietosvaara, V., Michaelides, S. and Gmoser, H., 2005, COST Action 722, Meteorology and Short-range forecasting methods of fog, visibility and low clouds. Official European Communities in Luxembourg, p 270. Jacobs, W., Nietosvaara, V., Bott, A., Bendix, J., Cermak, J. and Michaelides, I., 2007, COST Action 722, Earth System Science and Environmental Management, Final report on Short Range Forecasting Methods of Fog, Visibility and Low Clouds. Available from COST- 722, European Science Foundation, p 500 Kain, J. S., 2004, The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181. Lee, H. Y. and Chang, D.-E., 2003, A numerical experiment of fog in Yongdong Province and the northeast air current, Atmosphere Res., 13(3), 108-109. Lester, J. F., 2007, Aviation weather, Jepson Pub. U.S.A. Meyer, M. B. and Lala, G. G., 1990, Climatological aspects of radiation fog occurrence at Albany, New York. J. Climate, 3, 577–586. Obukhov, A. M., 1971, Turbulence in an atmosphere with a non-uniform temperature. Boundary-Layer Meteorology 2 (1), 7-29. Saunders, W. E., 1951, A method of forecasting the temperature of fog formation. Meteorological Mag., 79, 213–219. Saunders, W. E., 1957, Variation of visibility in fog at Exeter airport and the time of fog dispersal. Meteorol Mag, 86, 362-368. Saunders, W. E., 1960, The clearance of water fog following the arrival of a cloud sheet during the night Meteorol Mag, 89, 8-10. Skamarock, W. C. and Klemp, J. B., 2008, A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J. Comp. Phys. 227 (7), 3465–3485. Stoelinga, M. T. and Warner, T. T., 1999, Nonhydrostatic, Mesobeta-scale model simulations of cloud ceiling and visibility for an east coast winter precipitation event. J. Appl. Meteor., 38, 385-404. Stunder, B. J. B., 1997, NCEP Model Output – FNL ARCHIVE DATA, TD. Tardif, R. and Rasmussen, R. M., 2007, Event-based climatology and typology of fog in the New York City region. J. Appl. Meteor. Climatol. 46, 1141–1168. Van Schalkwyk, L. and DYSON, L. L., 2013, Climatological Characteristics of Fog at Cape Town International Airport. J. Appl. Meteor. Climatol. vol28, pp 631-646. Viojovic, D. and Veljovik, K., 2008, Fog Analysis in Belgrade International Airport, Geophysical Research Abstracts, Vol. 10, P. 1. Wallace, J. M. and Hobbs, P. V., 2006, The Boundary Layer. Atmospheric Science, Second Edition: An Introductory Survey, Elsevier Inc., 375-412. Wild, O., Zhu, X. and Prather, M. J., 2000, Fast-J: Accurate simulation of in-and below-cloud photolysis in tropospheric chemical models. Journal of Atmospheric Chemistry 37 (3), 245-282. Willet, H. C., 1928, Fog and haze, their causes, distribution, and forecasting. Mon. Wea. Rev., 56, 435–468. World Meteorological Organization, No, 728. 2008, Aerodrome Reports and Forecasts: A Users’ Handbook to the Codes, WMO publication. Geneva, Switzerland World Meteorological Organization, No. 306,2014, Manual on Codes, International Codes, Volume I., Part A – Alphanumeric Codes , WMO publication. Geneva, Switzerland. World Meteorological Organization, No. 407, 2012, Manual on the observation of clouds and other meteors. , WMO publication. Geneva, Switzerland. World Meteorological Organization, , 2012, Mist and Fog Forecasting Techniques, HYPERLINK "http://www.caem.wmo.int/_pdf/low_cloud_visibility/lowcloudvis_04_mist_fog.pdf" www.caem.wmo.int/_pdf/low_cloud_visibility /lowcloudvis_04_mist_fog.pdf., WMO publication. Geneva, Switzerland. World Meteorological Organization, 2016, Saunders fog point technique, http://www.caem.wmo.int/_pdf, WMO publication. Geneva, Switzerland. Zhou, B., Du, J., McQueen, J. and Dimego, G., 2009, Ensemble forecast of ceiling, visibility, and fog with NCEP Short-Range Ensemble Forecast system (SREF). Preprints, Aviation, Range, and Aerospace Meteorology Special Symp. On Weather–Air Traffic Management Integration, Phoenix, AZ, Amer. Meteor. Soc., 4.5 | ||
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