مدل‌سازی عددی پدیده جوی مسبب آبگرفتگی در نواحی ساحلی خلیج فارس
محورهای موضوعی :
آب و محیط زیست
اسماعیل عباسی
1
(
استادیار گروه محیط زیست، پژوهشکده خلیج فارس دانشگاه خلیج فارس، بوشهر، ایران (مسوول مکاتبات)
)
هانا اعتمادی
2
(
استادیار گروه محیط زیست، پژوهشکده خلیج فارس دانشگاه خلیج فارس، بوشهر، ایران
)
تاریخ دریافت : 1397/03/13
تاریخ پذیرش : 1397/09/21
تاریخ انتشار : 1400/01/01
کلید واژه:
انفجار پایین‌سو,
توفان تندری,
مدل WRF,
بندر دیر,
چکیده مقاله :
زمینه و هدف: اجرای مدل های عددی جو با قدرت تفکیک بالا یکی از بهترین ابزارها جهت واکاوی جو در زمان رخداد پدیده های حدی می باشد. پژوهش حاضر به مدل سازی عددی پدیده جوی مسبب آبگرفتگی سواحل ایرانی خلیج فارس که در تاریخ 19 مارس سال 2017 به وقوع پیوست، پرداخته است.روش بررسی: مدل عددی مورد استفاده، نسخه 1/8/3 مدل WRF[1] با هسته دینامیکی[2]ARW می باشد که به کمک این مدل اقدام به ریز مقیاس نمایی و در واقع مدل سازی در منطقه انتخابی با مشخصات مرکزی عرض 27 درجه و 30 دقیقه شمالی و طول جغرافیایی51 درجه و 30 دقیقه شرقی با قدرت تفکیک 10 کیلومتر شده است.یافته ها: بعد از انجام مدل سازی عددی به کمک مدل WRF مشخص گردید که خروجی حاصل از مدل سازی پارامترهای جوی در منطقه مورد مطالعه با تعدادی از داده های واقعی اندازه گیری شده در ایستگاه سینوپتیک بخصوص دمای خشک و فشار تقریبا برابر بوده است. تحلیل نقشه و نمودارهای تولید شده به کمک مدل حکایت از وقوع توفان های تندری سوپر سلولی داردکه نتیجه آن خرد انفجارهای شدیدی است که بر روی سطح دریا در نزدیک سواحل بندر دیر رخ داده و نهایتا سبب ایجاد چهار موج و آبگرفتگی در این سواحل شده است.بحث و نتیجه گیری: براساس نتایج حاصل از خروجی های مدل، عامل اصلی رخداد این آبگرفتگی، وقوع یک توفان تندری سوپر سلول بر روی خلیج فارس و در فاصله نزدیک به سواحل بندر دیر تشخیص داده شد.[1] - Weather Research and Forecasting[2] - Advanced Research WRF
چکیده انگلیسی:
Background and Objectives: Implementation of numerical models of atmosphere with high resolution is one of the best tools to investigate the atmosphere at the time of occurrence of extreme phenomena. The present study has conducted to survey a numerical modeling of the atmospheric phenomenon which generated a water logging in Persian Gulf coastal area that occurred on March 19, 2017.Method: The WRF numerical model (version of 3.8.1) with the ARW dynamic core was used in this research. The WRF model are used to provide a dynamical downscaling and modeling in a selected domain with a central latitude of the 27° and 30 N and longitude 51° and 30׳ E in a 10 Km resolution.Results: The results showed that atmospheric variables modeling outputs in the study site were nearly equal to observed station data especially in dry temperature and pressure climatic variables. Also, the maps and diagram which is produced by model, indicated that a supercell thunderstorm has occurred which is caused the severe explosions occurring on the sea surface near the coast of Bandar Dayyer and eventually causing four waves and water logging on these coasts.Discussion and Conclusion: Based on the results of the model outputs, the main cause of this flood event was the occurrence of a supercell thunderstorms on the Persian Gulf near the coast of Bandar Dayyer.
منابع و مأخذ:
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Hong, S.Y., Noh, Y. and Dudhia, J. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly weather review. 134(9), 2318-2341.
Weisman, M.L., Davis, C., Wang, W., Manning, K.W. and Klemp, J.B. 2008. Experiences with 0–36-h explicit convective forecasts with the WRF-ARW model. Weather and Forecasting. 23(3), 407-437.
Bright, D.R. and Mullen, S.L. 2002. The sensitivity of the numerical simulation of the southwest a monsoon boundary layer to the choice of PBL turbulence parameterization in MM5. Weather and Forecasting. 17(1), 99-114
Shin, H.H. and Hong, S.Y. 2011. Intercomparison of planetary boundary-layer parametrizations in the WRF model for a single day from CASES-99. Boundary-Layer Meteorology. 139(2), 261-281.
Stensrud, D.J. 2009. Parameterization schemes: keys to understanding numerical weather prediction models. Cambridge University Press. pp. 185-196.
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Solari, G., Burlando, M., De Gaetano, P. and Repetto, M.P., 2015. Characteristics of thunderstorms relevant to the wind loading of structures. Wind and Structures. 20(6), 763-791.
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Mohee, F.M. and Miller, C., 2010. Climatology of thunderstorms for North Dakota, 2002–06. Journal of Applied Meteorology and Climatology 49(9), 1881-1890.
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Srivastava, R.C. 1985. A simple model of evaporatively driven dowadraft: Application to microburst downdraft. Journal of the Atmospheric Sciences. 42(10), 1004-1023.
Wakimoto, R.M., 1985. Forecasting dry microburst activity over the high plains. Monthly Weather Review. 113(7), 1131-1143.
Lin, Y.J., Hughes, R.G. and Pasken, R.W. 1987. Subcloud-layer kinematic and dynamic structures of a microburst-producing thunderstorm in Colorado determined from JAWS dual-doppler measurements. Boundary-Layer Meteorology. 39(1-2), 67-86.
Iran Meteorology Administration, 2017. Statistics and Information annual reports. (In Persian)
Stull, R., 2000. Meteorology for scientists and engineers. Brooks/Cole.
Glickman, T.S. and Walter, Z., 2000. Glossary of Meteorology American Meteorological Society. 855 pp.
Johns, R.H. and Doswell III, C.A., 1992. Severe local storms forecasting. Weather and Forecasting. 7(4), 588-612.
Fuelberg, H.E. and Biggar, D.G., 1994. The preconvective environment of summer thunderstorms over the Florida panhandle. Weather and Forecasting. 9(3), 316-326.
_||_
Moeng, C.H., Dudhia, J., Klemp, J. and Sullivan, P. 2007. Examining two-way grid nesting for large eddy simulation of the PBL using the WRF model. Monthly weather review. 135(6), 2295-2311.
Davis, C., Wang, W., Chen, Y., Corbosiero, K., Dudhia, J., Holland, G., Klemp, J., Michalakes, J., Rotunno, R., Snyder, C. and Xiao, Q. 2006. Advanced Research WRF Developments for Hurricane Prediction.
Done, J.M., Leung, L.R. and Kuo, Y.H. 2006. June. Understanding error in the long-term simulation of warm season rainfall using the WRF model. In 7th WRF users workshop, Boulder, CO, USA.
Powers, J.G. 2007. Numerical prediction of an Antarctic severe wind event with the Weather Research and Forecasting (WRF) model. Monthly Weather Review. 135(9), 3134-3157.
Shamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, M., Wang, W. and Powers, J. 2008. A Description of the Advanced Research WRF Version 3: NCAR Technical Note. National Center for Atmospheric Research.
Evans, J.P., Ekström, M. and Ji, F. 2012. Evaluating the performance of a WRF physics ensemble over South-East Australia. Climate Dynamics 39(6), 1241-1258.
Chotamonsak, C., Salathe Jr, E.P., Kreasuwan, J. and Chantara, S. 2012. Evaluation of precipitation simulations over Thailand using a WRF regional climate model. Chiang Mai Journal of Science. 39(4), 623-638.
Zhang, D.L. and Zheng, W.Z. 2004. Diurnal cycles of surface winds and temperatures as simulated by five boundary layer parameterizations. Journal of Applied Meteorology. 43(1), 157-169.
Deng, A. and Stauffer, D.R. 2006. On improving 4-km mesoscale model simulations. Journal of applied meteorology and climatology 45(3), 361-381.
Hong, S.Y., Noh, Y. and Dudhia, J. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly weather review. 134(9), 2318-2341.
Weisman, M.L., Davis, C., Wang, W., Manning, K.W. and Klemp, J.B. 2008. Experiences with 0–36-h explicit convective forecasts with the WRF-ARW model. Weather and Forecasting. 23(3), 407-437.
Bright, D.R. and Mullen, S.L. 2002. The sensitivity of the numerical simulation of the southwest a monsoon boundary layer to the choice of PBL turbulence parameterization in MM5. Weather and Forecasting. 17(1), 99-114
Shin, H.H. and Hong, S.Y. 2011. Intercomparison of planetary boundary-layer parametrizations in the WRF model for a single day from CASES-99. Boundary-Layer Meteorology. 139(2), 261-281.
Stensrud, D.J. 2009. Parameterization schemes: keys to understanding numerical weather prediction models. Cambridge University Press. pp. 185-196.
Doswell III, C.A., Brooks, H.E., Maddox, R.A. 1996. Flash flood forecasting: an ingredientsbased methodology. Weather Forecast. 11, 560–581.
Solari, G., Burlando, M., De Gaetano, P. and Repetto, M.P., 2015. Characteristics of thunderstorms relevant to the wind loading of structures. Wind and Structures. 20(6), 763-791.
Ashley, W.S., Mote, T.L. 2005. DerechohazardsintheUnitedStates.Bull.Am.Meteorol.Soc.86, 1577–1592.
Mohee, F.M. and Miller, C., 2010. Climatology of thunderstorms for North Dakota, 2002–06. Journal of Applied Meteorology and Climatology 49(9), 1881-1890.
Schoen, J.M. and Ashley, W.S. 2011. A climatology of fatal convective wind events by storm type. Weather and forecasting, 26(1), 109-121.
Allen JT, Allen ER. 2016. A review of severe thunderstorms in Australia. Atmospheric research. 178, 347-366.
Thom, H.C.S., 1969. New distributions of extreme wind speeds in the United States. Journal of the Structural Division. ASCE 94, 1787–1801.
Wood, G.S., Kwok, K.C., Motteram, N.A. and Fletcher, D.F. 2001. Physical and numerical modelling of thunderstorm downbursts. Journal of Wind Engineering and Industrial Aerodynamics, 89(6), 535-552.
Choi, E.C. 2004. Field measurement and experimental study of wind speed profile during thunderstorms. Journal of wind engineering and industrial Aerodynamics. 92(3-4), 275-290.
Sengupta, A. and Sarkar, P.P. 2008. Experimental measurement and numerical simulation of an impinging jet with application to thunderstorm microburst winds. Journal of Wind Engineering and Industrial Aerodynamics 96(3), 345-365.
Fujita, T.T. 1981. Tornadoes and downbursts in the context of generalized planetary scales. Journal of the Atmospheric Sciences. 38(8), 1511-1534.
Fujita, T.T. 1985. The downburst-Micoburst and Macroburst. Report of Projects NIMROD and JAWS.
Wilson, J.W., Roberts, R.D., Kessinger, C. and McCarthy, J., 1984. Microburst wind structure and evaluation of Doppler radar for airport wind shear detection. Journal of Climate and Applied Meteorology. 23(6), 898-915.
Hjelmfelt, M.R. 1988. Structure and life cycle of microburst outflows observed in Colorado. Journal of Applied Meteorology. 27(8), 900-927.
Proctor, F.H. 1989. Numerical simulations of an isolated microburst. Part II: Sensitivity experiments. Journal of the atmospheric sciences. 46(14), 2143-2165.
Srivastava, R.C. 1985. A simple model of evaporatively driven dowadraft: Application to microburst downdraft. Journal of the Atmospheric Sciences. 42(10), 1004-1023.
Wakimoto, R.M., 1985. Forecasting dry microburst activity over the high plains. Monthly Weather Review. 113(7), 1131-1143.
Lin, Y.J., Hughes, R.G. and Pasken, R.W. 1987. Subcloud-layer kinematic and dynamic structures of a microburst-producing thunderstorm in Colorado determined from JAWS dual-doppler measurements. Boundary-Layer Meteorology. 39(1-2), 67-86.
Iran Meteorology Administration, 2017. Statistics and Information annual reports. (In Persian)
Stull, R., 2000. Meteorology for scientists and engineers. Brooks/Cole.
Glickman, T.S. and Walter, Z., 2000. Glossary of Meteorology American Meteorological Society. 855 pp.
Johns, R.H. and Doswell III, C.A., 1992. Severe local storms forecasting. Weather and Forecasting. 7(4), 588-612.
Fuelberg, H.E. and Biggar, D.G., 1994. The preconvective environment of summer thunderstorms over the Florida panhandle. Weather and Forecasting. 9(3), 316-326.
