پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 152 |
| تعداد شماره‌ها | 5,619 |
| تعداد مقالات | 61,967 |
| تعداد مشاهده مقاله | 101,969,716 |
| تعداد دریافت فایل اصل مقاله | 80,541,621 |
ارزیابی عملکرد طرحوارههای همرفت کومهای در مدل HWRF در پیشبینی مشخصه‌های توفان حارهای، مطالعه موردی توفان حارهای گونو | ||
| فیزیک زمین و فضا | ||
| مقاله 10، دوره 47، شماره 1، اردیبهشت 1400، صفحه 145-174 اصل مقاله (2.6 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2021.310820.1007250 | ||
| نویسنده | ||
نفیسه پگاه فر  
| ||
| استادیار، پژوهشکده علوم جوی، پژوهشگاه ملی اقیانوسشناسی و علوم جوی، تهران، ایران | ||
| چکیده | ||
| حساسیتسنجی مدلهای عددی در پیشبینی ویژگیهای پدیده چرخند حارهای کاری مهم است. در این پژوهش عملکرد 5 طرحواره پارامترسازی همرفت کومهای شامل BMJ، KF، SAS، SASAS و TiedTKE با اجرای مدل HWRF برای شبیهسازی چرخند حارهای گونو بررسی شد. نتایج نشان داد که هیچ یک از طرحوارهها انتهای مسیر چرخند را درست پیشبینی نکرده و در شرایط شدت بیش از دسته 3، روند تغییر فشار سطحی و روند باد بیشینه هم درست پیشبینی نشد. البته، در شدتهای کمتر طرحواره SAS دقیقترین نتیجه را تولید کرد. مشابهت قابل‌‌قبولی میان الگوهای شبیهسازی شده و تحلیلی برای نیمرخهای قائم دمای پتانسیلی و سرعت افقی مشاهده شد. شدت جریان‌های نزولی و صعودی شبیهسازی شده بیش از مقادیر تحلیلی و نزدیکتر به مرکز چرخند بودند. طرحوارههای SAS و SASAS نیز به‌ترتیب با کمترین خطا جریان‌های نزولی و صعودی را تولید کردند. الگوی واگرایی تراز زبرین توسط میدان‌های تحلیلی و شبیهسازی شده رؤیت شد، اما همگرایی تراز زیرین در هیچکدام دیده نشد. بیشینه مقدار انرژی پتانسیل دسترسپذیر همرفتی شبیهسازی شده نسبت به تحلیلی در فاصله دورتری از سواحل عمان پیشبینی شد. تنها طرحواره SASAS توانست شکلگیری شدیدترین هسته تاوایی پتانسیلی در نزدیکی سطح را شبیهسازی کند. بیشینه مقدار بارش تجمعی پیشبینی شده تمام طرحوارهها یکسان و نصف مقدار مشاهداتی بود. چینش افقی باد شبیهسازی شده توسط هر 5 طرحواره کمتر از مقادیر تحلیلی بود. در ایستگاه چابهار، طرحوارههای KF، TiedTKE و SASAS به‌ترتیب در پیشبینی مقادیر سطحی سرعت باد، فشار تراز دریا و دما دقیقترین نتایج را تولید کردند. | ||
| کلیدواژه‌ها | ||
| مدل HWRF؛ طرحوارههای پارامترسازی همرفت کومهای؛ چرخند حارهای گونو؛ تاوایی پتانسیلی؛ بارش | ||
| عنوان مقاله [English] | ||
| Evaluation of cumulus schemes of HWRF model in forecasting tropical cyclone characteristics, Gonu tropical cyclone case study | ||
| نویسندگان [English] | ||
| Nafiseh Pegahfar | ||
| Assistant Professor, Atmospheric Science Center, Iranian National Institute for Oceanography and Atmospheric Science, Tehran, Iran | ||
| چکیده [English] | ||
| Sensitivity of numerical models in the prediction of Tropical Cyclone (TC) characteristics has been considered in numerous research studies. In this research, application of five cumulus schemes of HWRF (Hurricane Weather Research and Forecasting) model, including KF, SAS, BMJ, TiedTKE and SASAS has been examined during Tropical Cyclone Gonu (TCG) from 4 to 7 June 2007. The simulations have been conducted using three nests with 27, 9 and 3 km resolutions. To this aim, the performance of schemes in predicting TCG intensity using minimum surface pressure and maximum 10-m wind speed are analyzed. Following, their effect on forecasting the radius of maximum wind is evaluated. The parameters of lower-level divergence, upper-level convergence, potential temperature, potential vorticity, Convective Available Potential Energy (CAPE), wind vector (both horizontal and vertical components), wind shear, precipitation and radar reflectivity have been analyzed. The results of the simulations have been compared with the analysis data, IMD and TRMM observational data and routine atmospheric parameter measured at the Chabahar station. The comparison was done in different time of TCG lifetime. To examine the performance of HWRF cumulus schemes for track and intensity of the TCG, the whole life cycle of TCG was considered. To test the efficiency of HWRF cumulus schemes in predicting some dynamical and thermodynamical parameters, the time of maximum intensity of TCG (18 UTC on 4 June 2007) was focused on. To evaluate the functionality of HWRF cumulus schemes in the coastal area, the outputs were discussed in the last two days of the TCG life cycle. Results showed that based on the used configuration, none of the five cumulus schemes predicted the TCG reaching the southern coast of Iran. Moreover, neither the pressure decrease nore the maximum wind speed were predicted accurately at the time of maximum intensity of TCG. Until TCG intensity was more that category-3, neither minimum surface pressure trend and nor the maximum wind speed trend have been forecasted well. However, for the less intense conditions, two schemes of TiedTKE and SAS produced the nearest values. The performance of all five cumulus schemes, similarly predicted the radius of the maximum wind, except TiedTKE scheme that predicted the super cyclone 6 hours earlier. The analysed and simulated of the vertical cross sections of potential temperature and horizontal wind were similar, respectively. The simulated values of the vertical component of wind were considerably larger than those from the analysis data and were also closer to the TCG center. The maximum values of simulated CAPE were off the Oman coast compared to the analysis values. Only the simulations using SASAS cumulus schemes showed the strongest potential vorticity near the surface. The simulated updrafts and downdrafts were larger than those from the analysis data. The simulated values of the major updrafts and downdrafts were closer to the center of the TCG, comparing to those from the analysis data. The upper-level divergence patterns were seen in both simulations using all 5 cumulus schemes and also in the analysis data, while the lower-level convergences were not captured neither in the simulations nor in the analysis data. The maximum value of the simulated accumulated precipitation using all 5 cumulus schemes were 80 mm in a 6 hour interval, however, the observational value from the TRMM was 25 mm/h. The predicted radar reflectivity from the simulations were similar and the simulated maximum values were the same, but the expansions of the simulated maximum values were different. All cumulus schemes predicted the wind shear values less than the analytical values. At Chabahar station, the observational values of the 10-m wind speed, sea level pressure, and temperature have been compared to the simulated values using all 5 cumulus schemes, in the period of 6-7 Jun 2007. The statistical parameters of correlation, standard deviation and root mean square were used to identify the best cumulus scheme. The least error prediction was obtained using KF cumulus schemes to predict the 10-m wind, the TiedTKE cumulus scheme to simulate sea level pressure the observed, and SASAS cumulus schemes to produce temperature. | ||
| کلیدواژه‌ها [English] | ||
| HWRF model, cumulus parametrization schemes, Tropical cyclone Gonu, potential vorticityT precipitation | ||
| مراجع | ||
|
پگاهفر، ن. و غفاریان، پ.، 1395، بررسی فراسنج‌های هواشناختی در وردسپهر زیرین و زبرین در دوره عمر چرخند حارهای هیان، اقیانوسشناسی، 13، 55-67. پگاهفر، ن.، 1398، بررسی همدیدی‌مقیاس شارهای آنتروپی در چرخند حارهای گونو، فیزیک زمین و فضا، 45(2)، 459-472. مزرعه فراهانی، م.، احمدی، م. و ثقفی، م.ع.، ،1394، ارزیابی نیروهای مؤثر بر تشکیل و تقویت توفان حارهای گونو با استفاده از مدل تحلیلی کیو و بررسی عملکرد مدلهای عددی در تعیین شدت آن، م. فیزیک زمین وفضا، 41، 273-280.
Alaka Jr., G.J., Zhang, X., Gopalakrishnan, S.G., Goldenberg, S.B. and Marks, F.D., 2017, Performance of basin-scale HWRF tropical cyclone track forecasts. Weather and Forecasting, 32(3), 1253-1271. Allahdadi, M.N., Chaichitehrani, N., Allahyar, M. and McGee, L., 2017, Wave spectral patterns during a historical cyclone: a numerical model for cyclone Gonu in the northern Oman Sea. Open Journal of Fluid Dynamics, 7(02), p.131. Allahdadi, M.N., Chaichitehrani, N., Jose, F., Nasrollahi, A., Afshar, A. and Allahyar, M., 2018, Cyclone-generated Storm Surge in the Northern Gulf of Oman: A Field Data Analysis during Cyclone Gonu. American Journal of Fluid Dynamics, 8(1), 10-18. Bao, J.W., Gopalakrishnan, S.G., Michelson, S.A., Marks, F.D. and Montgomery, M.T., 2012, Impact of physics representations in the HWRFX on simulated hurricane structure and pressure–wind relationships. Monthly weather review, 140(10), 3278-3299. Biswas, M.K., Bernardet, L., Ginis, I., Kwon, Y., Liu, B., Liu, Q., Marchok, T., Mehra, A., Newman, K., Sheinin, D., Subramanian, S., Tallapragada, V., Thomas, B., Tong, M., Trahan, S., Wang, W., Yablonsky, R. and Zhang, X., 2016, Hurricane Weather Research and Forecasting (HWRF) Model: 2016, Scientific Documentation. Biswas, M.K., Bernardet, L. and Dudhia, J., 2014, Sensitivity of hurricane forecasts to cumulus parameterizations in the HWRF model. Geophysical Research Letters, 41(24), 9113-9119. Biswas, M.K., Bernardet, L., Ginis, I., Kwon, Y., Liu, Q., Marchok, T., Sheinin, D., Tallapragada, V., Thomas, B., Tong, M. and Trahan, S., 2018, Hurricane weather research and forecasting (HWRF) model: 2017, scientific documentation. Carrió, D.S., Homar, V., Jansa, A., Romero, R. and Picornell, M.A., 2017, Tropicalization process of the 7 November 2014 Mediterranean cyclone: Numerical sensitivity study. Atmospheric Research, 197, 300-312. Chen, H. and Gopalakrishnan, S.G., 2015, A study on the asymmetric rapid intensification of Hurricane Earl (2010) using the HWRF system. Journal of the Atmospheric Sciences, 72(2), 531-550. Chen, Q. and Fang, J., 2012, Effects of vertical wind shear on intensity and structure of tropical cyclone. Journal of Tropical Meteorology, 18(2). Das, A.K., Rao, Y.R., Tallapragada, V., Zhang, Z., Bhowmik, S.R. and Sharma, A., 2015, Evaluation of the Hurricane Weather Research and Forecasting (HWRF) model for tropical cyclone forecasts over the North Indian Ocean (NIO). Natural Hazards, 75(2), 1205-1221. Davis, C. and Bosart, L.F., 2002, Numerical simulations of the genesis of Hurricane Diana (1984). Part II: Sensitivity of track and intensity prediction. Monthly weather review, 130(5), 1100-1124. Davis, C., Wang, W., Chen, S.S., Chen, Y., Corbosiero, K., DeMaria, M., Dudhia, J., Holland, G., Klemp, J., Michalakes, J. and Reeves, H., 2008, Prediction of landfalling hurricanes with the advanced hurricane WRF model. Monthly weather review, 136(6), 1990-2005. Deshpande, M., Pattnaik, S. and Salvekar, P.S., 2010, Impact of physical parameterization schemes on numerical simulation of super cyclone Gonu. Natural Hazards, 55(2), 211-231. Dodla, V.B., Desamsetti, S. and Yerramilli, A., 2011, A comparison of HWRF, ARW and NMM models in Hurricane Katrina (2005) simulation. International journal of environmental research and public health, 8(6), 2447-2469. Emanuel, K. and Zhang, F., 2016, On the predictability and error sources of tropical cyclone intensity forecasts. J. Atmos. Sci. 73(9), 3739-3747. Fahad, A.A. and Ahmed, T., 2015, Impacts of different cumulus physics over south Asia region with case study tropical cyclone Viyaru. arXiv preprint arXiv:1506.01481. Gentry, M.S. and Lackmann, G.M., 2006, April. The sensitivity of WRF simulations of Hurricane Ivan to choice of cumulus parameterization. In Preprints, 27th Conf. on Hurricanes and Tropical Meteorology, Monterey, A, Amer. Meteor. Soc. P (Vol. 5). Gopalakrishnan, S., Liu, Q., Marchok, T., Sheinin, S., Surgi, N., Tuleya, R., Yablonsky, R. and Zhang, X., 2010, Hurricane Weather Research and Forecasting (HWRF) Model Scientific Documentation. Edited By L. Bernardet. 75pp. Gopalakrishnan, S.G., Marks Jr, F., Zhang, J.A., Zhang, X., Bao, J.W. and Tallapragada, V., 2013, A study of the impacts of vertical diffusion on the structure and intensity of the tropical cyclones using the high-resolution HWRF system. Journal of the atmospheric sciences, 70(2), 524-541. Gopalakrishnan, S.G., Marks Jr, F., Zhang, X., Bao, J.W., Yeh, K.S. and Atlas, R., 2011, The experimental HWRF system: A study on the influence of horizontal resolution on the structure and intensity changes in tropical cyclones using an idealized framework. Monthly Weather Review, 139(6), 1762-1784. Han, J. and Pan, H.L., 2011, Revision of Convection and Vertical Diffusion Schemes in the NCEP Global Forecast System. Weather Forecast. 26, 520-533. Hill, K.A. and Lackmann, G.M., 2009, Analysis of idealized tropical cyclone simulations using the Weather Research and Forecasting model: Sensitivity to turbulence parameterization and grid spacing. Monthly weather review, 137(2), 745-765. Janjic, Z. I., 1994, The step–mountain eta coordinate model: further developments of the Janjic, Z. I., 2000, Comments on “Development and Evaluation of a Convection Scheme for Use in Climate Models. J. Atmos. Sci., 57, p. 3686. Jones, S.C., 2000, The evolution of vortices in vertical shear. II: Large‐scale asymmetries. Quarterly Journal of the Royal Meteorological Society, 126(570), 3137-3159. Kain, J.S., 2004, The Kain-Fritsch convective parameterization: an update, J. Applied Meteorol. 4:170-181. Kanase, R.D. and Salvekar, P.S., 2014, Study of weak intensity cyclones over Bay of Bengal using WRF model. Atmos. Climate Sci. 4(04), 534. Karyampudi, V.M., Lai, G.S. and Manobianco, J., 1998, Impact of initial conditions, rainfall assimilation and cumulus parameterization on simulations of Hurricane Florence. Mon. Weather Rev. 126, 3077-3101. Krieger, J.R., Zhang, J., Atkinson, D.E., Zhang, X. and Shulski, M.D., 2009, P1. 2 Sensitivity of WRF model forecasts to different physical parameterizations in the beaufort sea region. In The Eighth Conference on Coastal Atmospheric and Oceanic Prediction and Processes. http://ams. confex. com/ams/pdfpapers/150439. pdf. Li, X. and Pu, Z., 2009, Sensitivity of numerical simulations of the early rapid intensification of Hurricane Emily to cumulus parameterization schemes in different model horizontal resolutions. J. Meteorol Soc. Japan. Ser. II. 87(3), 403-421. Marin, J.C., Raymond, D.J. and Raga, G.B., 2009, Intensification of tropical cyclones in the GFS model. Atmospheric Chemistry and Physics, 9(4), 1407-1417. Nolan, D.S. and McGauley, M.G., 2012, Tropical cyclogenesis in wind shear: Climatological relationships and physical processes. Cyclones: Formation, triggers, and control, pp.1-36. Osuri, K.K., Mohanty, U.C., Routray, A., Kulkarni, M.A. and Mohapatra, M., 2012, Customization of WRF-ARW model with physical parameterization schemes for the simulation of tropical cyclones over North Indian Ocean. Natural Hazards, 63(3), 1337-1359. Osuri, K.K., Nadimpalli, R., Mohanty, U.C. and Niyogi, D., 2017, Prediction of rapid intensification of tropical cyclone Phailin over the Bay of Bengal using the HWRF modelling system. Quarterly Journal of the Royal Meteorological Society, 143(703), 678-690. Pegahfar, N. and Gharaylou, M., 2020, Entropy evolution characteristics during an intense tropical cyclone. Meteorology and Atmospheric Physics, pp.1-22. Saikumar, P.J. and Ramashri, T., 2017, Impact of Physics Parameterization Schemes in the Simulation of Laila Cyclone Using the Advanced Mesoscale Weather Research and Forecasting Model. Inte. J. Applied Engineering Res. 12(22), 12645-12651. Schwartz, C.S., Kain, J.S., Weiss, S.J., Xue, M., Bright, D.R., Kong, F., Thomas, K.W., Levit, J.J., Coniglio, M.C. and Wandishin, M.S., 2010, Toward improved convection-allowing ensembles: Model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Weather and Forecasting, 25(1), 263-280. Singh, K.S. and Bhaskaran, P.K., 2017, Impact of PBL and convection parameterization schemes for prediction of severe land-falling Bay of Bengal cyclones using WRF-ARW model, J. Atmos. Solar Terres. Phys. 165, 10- 24. Singh, K.S. and Bhaskaran, P.K., 2018, Impact of lateral boundary and initial conditions in the prediction of Bay of Bengal cyclones using WRF model and its 3D-VAR data assimilation system, J. Atmos. Solar Terres. Phys. 175, 64-75. Singh, K.S. and Tyagi, B., 2018, Impact of data assimilation and air-sea interaction parameterization schemes for prediction of Bay of Bengal cyclone Phailin. Meteorol. Applications DOI: 10.1002/met.1734. Singh, K.S., Tyagi, B., Verma, V.K. and Maity, S., 2019, Assessing the performance evaluation of different convective parameterization schemes in simulating the intensity of severe cyclonic storms over the Bay of Bengal region. Meteorological Applications, 26(4), 597-609. Sun, Y., Zhong, Z., Lu, W. and Hu, Y., 2014, Why are tropical cyclone tracks over the western North Pacific sensitive to the cumulus parameterization scheme in regional climate modeling? A case study for Megi (2010). Monthly Weather Review, 142(3), 1240-1249. Tang, B.H.A., 2010, Midlevel ventilation’s constraint on tropical cyclone intensity. Doctoral dissertation, Massachusetts Institute of Technology. http://hdl.handle.net/1721.1/62321. Tiedtke, M., 1989, A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Weather Rev. 117, 1779-1800. Torn, R.D., 2016, Evaluation of atmosphere and ocean initial condition uncertainty and stochastic exchange coefficients on ensemble tropical cyclone intensity forecasts. Mon. Weather Rev. 144(9), 3487-3506. Warner, T.T. and Hsu, H.M., 2000, Nested-model simulation of moist convection: The impact of coarse-grid parameterized convection on fine-grid resolved convection. Monthly weather review, 128(7), 2211-2231. 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. Wu, C.-C., Chou, K-H., Wang, Y. and Kuo, Y-H., 2006, Tropical cyclone initialization and prediction based on four-dimensional variational data assimilation. J. Atmos. Sci., 63, 2383–2395. Wu, L. and Wang B., 2000, A potential vorticity tendency diagnostic approach for tropical cyclone motion. Monthly Weather Review, 128, 1899-1911. Yang, B., Wang, Y. and Wang, B., 2007, The effect of internally generated inner-core asymmetries on tropical cyclone potential intensity. Journal of the atmospheric sciences, (4)64, 1165-1188. Zhang, C., Wang, Y. and Hamilton, K., 2011a, Improved Representation of Boundary Layer Clouds over the Southeast Pacific in ARW-WRF using a Modified Tiedtke Cumulus Parameterization Scheme. Mon. Weather Rev. 3489-3513, DOI: 0.1175/MWR-D-10-05091.1. Zhang, C., Wang, Y and Hamilton, K., 2011b, Improved Representation of Boundary Layer Clouds over the Southeast Pacific in ARW-WRF using a Modified Tiedtke Cumulus Parameterization Scheme. Mon. Weather Rev. 3489-3513, DOI: 0.1175/MWR-D-10-05091.1 | ||
|
آمار تعداد مشاهده مقاله: 263 تعداد دریافت فایل اصل مقاله: 124 |
||
