Editorial Type:
Article
Article Type:
Research Article

Probabilistic Evaluation of the Dynamics and Prediction of Supertyphoon Megi (2010)

Chuanhai Qian Nanjing University of Information Science and Technology, Nanjing, and National Meteorological Center, Beijing, China, and Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Chuanhai Qian in
Current site
Google Scholar
PubMed Close
,
Fuqing Zhang Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Fuqing Zhang in
Current site
Google Scholar
PubMed Close
,
Benjamin W. Green Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Benjamin W. Green in
Current site
Google Scholar
PubMed Close
,
Jin Zhang National Meteorological Center, Beijing, China

Search for other papers by Jin Zhang in
Current site
Google Scholar
PubMed Close
, and
Xiaqiong Zhou NOAA/NCEP, College Park, Maryland

Search for other papers by Xiaqiong Zhou in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Dec 2013
DOI:
https://doi.org/10.1175/WAF-D-12-00121.1
Page(s):
1562–1577
Restricted access

Abstract

Supertyphoon Megi was the most intense tropical cyclone (TC) of 2010. Megi tracked westward through the western North Pacific and crossed the Philippines on 18 October. Two days later, Megi made a sharp turn to the north, an unusual track change that was not forecast by any of the leading operational centers. This failed forecast was a consequence of exceptionally large uncertainty in the numerical guidance—including the operational ensemble of the European Centre for Medium-Range Weather Forecasts (ECMWF)—at various lead times before the northward turn. This study uses The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble dataset to examine the uncertainties in the track forecast of the ECMWF operational ensemble. The results show that Megi's sharp turn is sensitive to its own movement in the early period, the size and structure of the storm, the strength and extent of the western Pacific subtropical high, and an approaching eastward-moving midlatitude trough. In particular, a larger TC (in addition to having a stronger beta effect) may lead to a stronger erosion of the southwestern extent of the subtropical high, which will subsequently lead to an earlier and sharper northward turn.

Corresponding author address: Prof. Fuqing Zhang, Dept. of Meteorology, The Pennsylvania State University, 503 Walker Building, University Park, PA 16802-5013. E-mail: fzhang@psu.edu

Abstract

Supertyphoon Megi was the most intense tropical cyclone (TC) of 2010. Megi tracked westward through the western North Pacific and crossed the Philippines on 18 October. Two days later, Megi made a sharp turn to the north, an unusual track change that was not forecast by any of the leading operational centers. This failed forecast was a consequence of exceptionally large uncertainty in the numerical guidance—including the operational ensemble of the European Centre for Medium-Range Weather Forecasts (ECMWF)—at various lead times before the northward turn. This study uses The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble dataset to examine the uncertainties in the track forecast of the ECMWF operational ensemble. The results show that Megi's sharp turn is sensitive to its own movement in the early period, the size and structure of the storm, the strength and extent of the western Pacific subtropical high, and an approaching eastward-moving midlatitude trough. In particular, a larger TC (in addition to having a stronger beta effect) may lead to a stronger erosion of the southwestern extent of the subtropical high, which will subsequently lead to an earlier and sharper northward turn.

Corresponding author address: Prof. Fuqing Zhang, Dept. of Meteorology, The Pennsylvania State University, 503 Walker Building, University Park, PA 16802-5013. E-mail: fzhang@psu.edu
Save
Cover Weather and Forecasting
Weather and Forecasting

  • Adem, J., and Lezama P. , 1960: On the motion of a cyclone embedded in a uniform flow. Tellus, 12, 255–258.

  • Aksoy, A., Lorsolo S. , Vukicevic T. , Sellwood K. J. , Aberson S. D. , and Zhang F. , 2012: The HWRF Hurricane Ensemble Data Assimilation System (HEDAS) for high-resolution data: The impact of airborne Doppler radar observations in an OSSE. Mon. Wea. Rev., 140, 1843–1862.

    • Search Google Scholar
    • Export Citation

  • Ancell, B., and Hakim G. J. , 2007: Comparing adjoint- and ensemble-sensitivity analysis with applications to observation targeting. Mon. Wea. Rev., 135, 4117–4134.

    • Search Google Scholar
    • Export Citation

  • Anthes, R. A., and Hoke J. E. , 1975: The effect of horizontal divergence and the latitudinal variation of the Coriolis parameter on the drift of a model hurricane. Mon. Wea. Rev., 103, 757–763.

    • Search Google Scholar
    • Export Citation

  • Bougeault, P., and Coauthors, 2010: The THORPEX Interactive Grand Global Ensemble. Bull. Amer. Meteor. Soc., 91, 1059–1072.

  • Brennan, M. J., and Majumdar S. J. , 2011: An examination of model track forecast errors for Hurricane Ike (2008) in the Gulf of Mexico. Wea. Forecasting, 26, 848–867.

    • Search Google Scholar
    • Export Citation

  • Buizza, R., Bidlot J.-R. , Wedi N. , Fuentes M. , Hamrud M. , Holt G. , and Vitart F. , 2007: The new ECMWF VAREPS (Variable Resolution Ensemble Prediction System). Quart. J. Roy. Meteor. Soc., 133, 681–695.

    • Search Google Scholar
    • Export Citation

  • Cangialosi, J. P., and Franklin J. L. , 2011: 2010 National Hurricane Center forecast verfication report. NOAA, 77 pp. [Available online at http://www.nhc.noaa.gov/verification/pdfs/verification_2010.pdf.]

  • Chan, J. C.-L., and Gray W. M. , 1982: Tropical cyclone movement and surrounding flow relationships. Mon. Wea. Rev., 110, 1354–1374.

  • Chan, J. C.-L., and Williams R. T. , 1987: Analytical and numerical studies of the beta-effect in tropical cyclone motion. Part I: Zero mean flow. J. Atmos. Sci., 44, 1257–1265.

    • Search Google Scholar
    • Export Citation

  • Chan, S. T., 2010: Tropical Cyclone Operational Warning Strategies (IWTC-7). WMO/CAS/WWW, 27 pp. [Available online at http://www.wmo.int/pages/prog/arep/wwrp/tmr/otherfileformats/documents/4_3.pdf.]

  • Chang, E. K. M., Zheng M. , and Raeder K. , 2013: Medium-range ensemble sensitivity analysis of two extreme Pacific extratropical cyclones. Mon. Wea. Rev., 141, 211–231.

    • Search Google Scholar
    • Export Citation

  • Colbert, A. J., and Soden B. J. , 2012: Climatological variations in North Atlantic tropical cyclone tracks. J. Climate, 25, 657–673.

  • Dong, K., and Neumann C. J. , 1986: The relationship between tropical cyclone motion and environmental geostrophic flows. Mon. Wea. Rev., 114, 115–122.

    • Search Google Scholar
    • Export Citation

  • Elsberry, R. L., 1987: Tropical cyclone motion. A Global View of Tropical Cyclones, R. L. Elsberry, Ed., Office of Naval Research, 91–131.

  • Fang, J., and Zhang F. , 2012: Effect of beta shear on simulated tropical cyclones. Mon. Wea. Rev., 140, 3327–3346.

  • Fiorino, M., and Elsberry R. L. , 1989: Some aspects of vortex structure related to tropical cyclone motion. J. Atmos. Sci., 46, 975–990.

    • Search Google Scholar
    • Export Citation

  • Goerss, J. S., 2000: Tropical cyclone track forecasts using an ensemble of dynamic models. Mon. Wea. Rev., 128, 1187–1193.

  • Hamill, T. M., Whitaker J. S. , Kleist D. T. , Fiorino M. , and Benjamin S. G. , 2011: Predictions of 2010's tropical cyclones using the GFS and ensemble-based data assimilation methods. Mon. Wea. Rev., 139, 3243–3247.

    • Search Google Scholar
    • Export Citation

  • Hawblitzel, D., Zhang F. , Meng Z. , and Davis C. A. , 2007: Probabilistic evaluation of the dynamics and predictability of mesoscale convective vortex event of 10–13 June 2003. Mon. Wea. Rev., 135, 1544–1563.

    • Search Google Scholar
    • Export Citation

  • Jung, B.-J., Kim H.-M. , Zhang F. , and Wu C.-C. , 2012: Effect of targeted dropsonde observations and best track data on the track forecasts of Typhoon Sinlaku (2008) using an ensemble Kalman filter. Tellus, 64A, 14 984.

    • Search Google Scholar
    • Export Citation

  • Melhauser, C., and Zhang F. , 2012: Practical and intrinsic predictability of severe and convective weather at the mesoscales. J. Atmos. Sci., 69, 3350–3371.

    • Search Google Scholar
    • Export Citation

  • Munsell, E. B., Zhang F. , and Stern D. P. , 2013: Predictability and dynamics of a nonintensifying tropical storm: Erika (2009). J. Atmos. Sci., 70, 2505–2524.

    • Search Google Scholar
    • Export Citation

  • Qian, C., and Coauthors, 2006: Grade of Tropical Cyclones. GB/T 19201-2006, China Standards Press, 10 pp.

  • Qian, C., Duan Y. , Ma S. , and Xu Y. , 2012: The current status and future development of China operational typhoon forecasting and its key technologies. Adv. Meteor. Sci. Technol., 2 (5), 36–43.

    • Search Google Scholar
    • Export Citation

  • Sippel, J. A., and Zhang F. , 2008: Probabilistic evaluation of the dynamics and predictability of tropical cyclogenesis. J. Atmos. Sci., 65, 3440–3459.

    • Search Google Scholar
    • Export Citation

  • Sippel, J. A., and Zhang F. , 2010: Factors affecting the predictability of Hurricane Humberto (2007). J. Atmos. Sci., 67, 1759–1778.

  • Velden, C. S., and Leslie L. M. , 1991: The basic relationships between tropical cyclone intensity and the depth of the environmental steering layer in the Australian region. Wea. Forecasting, 6, 244–253.

    • Search Google Scholar
    • Export Citation

  • Weng, Y., and Zhang F. , 2012: Assimilating airborne Doppler radar observations with an ensemble Kalman filter for convection-permitting hurricane initialization and prediction: Katrina (2005). Mon. Wea. Rev., 140, 841–859.

    • Search Google Scholar
    • Export Citation

  • Zhang, F., 2005: Dynamics and structure of mesoscale error covariance of a winter cyclone estimated through short-range ensemble forecasts. Mon. Wea. Rev., 133, 2876–2893.

    • Search Google Scholar
    • Export Citation

  • Zhang, F., Weng Y. , Sippel J. A. , Meng Z. , and Bishop C. H. , 2009: Cloud-resolving hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 137, 2105–2125.

    • Search Google Scholar
    • Export Citation

  • Zhang, F., Weng Y. , Kuo Y.-H. , Whitaker J. S. , and Xie B. , 2010: Predicting Typhoon Morakot's catastrophic rainfall with a convection-permitting mesoscale ensemble system. Wea. Forecasting, 25, 1816–1825.

    • Search Google Scholar
    • Export Citation

  • Zhang, F., Weng Y. , Gamache J. F. , and Marks F. D. , 2011: Performance of convection-permitting hurricane initialization and prediction during 2008-2010 with ensemble data assimilation of inner-core airborne Doppler radar observations. Geophys. Res. Lett., 38, L15810, doi:10.1029/2011GL048469.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2545 1131 28
PDF Downloads 378 156 5