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Acta Meteorologica Sinica

, Volume 27, Issue 4, pp 455–475 | Cite as

Improving simulation of a tropical cyclone using dynamical initialization and large-scale spectral nudging: A case study of Typhoon Megi (2010)

  • Hui Wang (王 慧)
  • Yuqing Wang (王玉清)
  • Haiming Xu (徐海明)
Article

Abstract

In this study, an approach combining dynamical initialization and large-scale spectral nudging is proposed to achieve improved numerical simulations of tropical cyclones (TCs), including track, structure, intensity, and their changes, based on the Advanced Weather Research and Forecasting (ARW-WRF) model. The effectiveness of the approach has been demonstrated with a case study of Typhoon Megi (2010). The ARW-WRF model with the proposed approach realistically reproduced many aspects of Typhoon Megi in a 7-day-long simulation. In particular, the model simulated quite well not only the storm track and intensity changes but also the structure changes before, during, and after its landfall over the Luzon Island in the northern Philippines, as well as after it reentered the ocean over the South China Sea (SCS). The results from several sensitivity experiments demonstrate that the proposed approach is quite effective and ideal for achieving realistic simulations of real TCs, and thus is useful for understanding the TC inner-core dynamics, and structure and intensity changes.

Key words

dynamical initialization large-scale spectral nudging 

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References

  1. Bender, M. A., I. Ginis, and Y. Kurihara, 1993: Numerical simulations of tropical cyclone-ocean interaction with a high-resolution coupled model. J. Geophys. Res., 98(D12), 23245–23263.CrossRefGoogle Scholar
  2. Braun, S. A., 2002: A cloud-resolving simulation of Hurricane Bob (1991): Storm structure and eyewall buoyancy. Mon. Wea. Rev., 130(6), 1573–1592.CrossRefGoogle Scholar
  3. —, 2006: High-resolution simulation of Hurricane Bonnie (1998). Part II: Water budget. J. Atmos. Sci., 63(1), 43–64.CrossRefGoogle Scholar
  4. —, and W. K. Tao, 2000: Sensitivity of high-resolution simulations of Hurricane Bob (1991) to planetary boundary layer parameterizations. Mon. Wea. Rev., 128(12), 3941–3961.CrossRefGoogle Scholar
  5. —, M. T. Montgomery, and Z. -X. Pu, 2006: Highresolution simulation of Hurricane Bonnie (1998). Part I: The organization of eyewall vertical motion. J. Atmos. Sci., 63(1), 19–42.CrossRefGoogle Scholar
  6. Cha, D. -H., C. -S. Jin, D. -K. Lee, et al., 2011: Impact of intermittent spectral nudging on regional climate simulation using Weather Research and Forecasting model. J. Geophys. Res., 116, D10103, doi:10.1029/2010JD015069.CrossRefGoogle Scholar
  7. —, and Y. Q. Wang, 2013: A dynamical initialization scheme for real-time forecasts of tropical cyclones using the WRF model. Mon. Wea. Rev., 141(3), 964–986.CrossRefGoogle Scholar
  8. Chou, K. -H., C. -C. Wu, Y. Wang, et al., 2011: Eyewall evolution of typhoons crossing the Philippines and Taiwan: An observational study. Terr. Atmos. Ocean. Sci., 22(6), 535–548.CrossRefGoogle Scholar
  9. Cram, T. A., J. Persing, M. T. Montgomery, et al., 2007: A Lagrangian trajectory view on transport and mixing processes between the eye, eyewall, and environment using a high-resolution simulation of Hurricane Bonnie (1998). J. Atmos. Sci., 64(6), 1835–1856.CrossRefGoogle Scholar
  10. Davis, C. A., and L. F. Bosart, 2001: Numerical simulations of the genesis of Hurricane Diana (1984). Part I: Control simulation. Mon. Wea. Rev., 129(8), 1859–1881.CrossRefGoogle Scholar
  11. —, and S. Low-Nam, 2001: The NCAR-AFWA Tropical Cyclone Bogussing Scheme. Air Force Weather Agency (AFWA) Rep., 12 pp. [Available online at http://www.mmm.ucar.edu/mm5/mm5v3/tcbogus.html.]Google Scholar
  12. —, and L. F. Bosart, 2002: Numerical simulations of the genesis of Hurricane Diana (1984). Part II: Sensitivity of track and intensity prediction. Mon. Wea. Rev., 130(5), 1100–1124.CrossRefGoogle Scholar
  13. —, W. Wang, S. S. Chen, et al., 2008: Prediction of landfalling hurricanes with the advanced hurricane WRF model. Mon. Wea. Rev., 136(6), 1990–2005.CrossRefGoogle Scholar
  14. Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46(20), 3077–3107.CrossRefGoogle Scholar
  15. Ek, M. B., K. E. Mitchell, Y. Lin, et al., 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108, 8851, doi:10.1029/2002JD003296.CrossRefGoogle Scholar
  16. Feser, F., and H. von Storch, 2008: A dynamical downscaling case study for typhoons in Southeast Asia using a regional climate model. Mon. Wea. Rev., 136(5), 1806–1815.CrossRefGoogle Scholar
  17. Goerss, J. S., and R. A. Jeffries, 1994: Assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System. Wea. Forecasting, 9(4), 557–576.CrossRefGoogle Scholar
  18. Hendricks, E. A., M. S. Peng, X. -Y. Ge, et al., 2011: Performance of a dynamic initialization scheme in the Coupled Ocean-Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC). Wea. Forecasting, 26(5), 650–663.CrossRefGoogle Scholar
  19. Hogsett, W., and D. -L. Zhang, 2009: Numerical simulation of Hurricane Bonnie (1998). Part III: Energetics. J. Atmos. Sci., 66(9), 2678–2696.CrossRefGoogle Scholar
  20. —, and —, 2010: Genesis of Typhoon Chanchu (2006) from a westerly wind burst associated with the MJO. Part I: Evolution of a vertically tilted precursor vortex. J. Atmos. Sci., 67(12), 3774–3792.CrossRefGoogle Scholar
  21. —, and —, 2011: Genesis of Typhoon Chanchu (2006) from a westerly wind burst associated with the MJO. Part II: Roles of deep convection in tropical transition. J. Atmos. Sci., 68(6), 1377–1396.CrossRefGoogle Scholar
  22. Holland, G. J., 1983: Tropical cyclone motion: Environmental interaction plus a beta effect. J. Atmos. Sci., 40(2), 328–342.CrossRefGoogle Scholar
  23. Hong, S. -Y., and J. -O. J. Lim, 2006: The WRF singlemoment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42(2), 129–151.Google Scholar
  24. Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43(1), 170–181.CrossRefGoogle Scholar
  25. —, and J. M. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47(23), 2784–2802.CrossRefGoogle Scholar
  26. —, and J. M. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain-Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr. No. 24, Amer. Meteor. Soc., 165–170.Google Scholar
  27. Kida, H., T. Koide, H. Sasaki, et al., 1991: A new approach for coupling a limited area model to a GCM for regional climate simulations. J. Meteor. Soc. Japan, 69, 723–728.Google Scholar
  28. Kurihara, Y., M. A. Bender, and R. J. Ross, 1993: An initialization scheme of hurricane models by vortex specification. Mon. Wea. Rev., 121(7), 2030–2045.CrossRefGoogle Scholar
  29. —, —, R. E. Tuleya, et al., 1995: Improvements in the GFDL Hurricane Prediction System. Mon. Wea. Rev., 123(9), 2791–2801.CrossRefGoogle Scholar
  30. Kwon, I. -H., and H. -B. Cheong, 2010: Tropical cyclone initialization with a spherical high-order filter and an idealized three-dimensional bogus vortex. Mon. Wea. Rev., 138(4), 1344–1367.CrossRefGoogle Scholar
  31. Leslie, L. M., and G. J. Holland, 1995: On the bogussing of tropical cyclones in numerical models: A comparison of vortex profiles. Meteor. Atmos. Phys., 56(1-2), 101–110.CrossRefGoogle Scholar
  32. Li, X. -L., and Z. -X. Pu, 2008: Sensitivity of numerical simulation of early rapid intensification of Hurricane Emily (2005) to cloud microphysical and planetary boundary layer parameterizations. Mon. Wea. Rev., 136(12), 4819–4838.CrossRefGoogle Scholar
  33. Liu, B., and L. Xie, 2012: A scale-selective data assimilation approach to improving tropical cyclone track and intensity forecasts in a limited-area model: A case study of Hurricane Felix (2007). Wea. Forecasting, 27(1), 124–140.CrossRefGoogle Scholar
  34. Liu, Y. B., D. -L. Zhang, and M. K. Yau, 1997: A multiscale numerical study of Hurricane Andrew (1992). Part I: Explicit simulation and verification. Mon. Wea. Rev., 125(12), 3073–3093.CrossRefGoogle Scholar
  35. —, —, and —, 1999: A multiscale numerical study of Hurricane Andrew (1992). Part II: Kinematics and inner-core structures. Mon. Wea. Rev., 127(11), 2597–2616.CrossRefGoogle Scholar
  36. Ma, S. -H., A. -X. Qu, and Y. Wang, 2007: The performance of the new tropical cyclone track prediction system of the China National Meteorological Center. Meteor. Atmos. Phys., 97(1–4), 29–39.CrossRefGoogle Scholar
  37. Miguez-Macho, G., G. L. Stenchikov, and A. Robock, 2005: Regional climate simulations over North America: Interaction of local processes with improved large-scale flow. J. Climate, 18(8), 1227–1246.CrossRefGoogle Scholar
  38. Mlawer, E. J., S. J. Taubman, P. D. Brown, et al., 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 (D14), 16663–16682.CrossRefGoogle Scholar
  39. Moon, I.-J., I. Ginis, T. Hara, et al., 2007: A physicsbased parameterization of air-sea momentum flux at high wind speeds and its impact on hurricane intensity predictions. Mon. Wea. Rev., 135(8), 2869–2878.CrossRefGoogle Scholar
  40. Musgrave, K. D., C. A. Davis, and M. T. Montgomery, 2008: Numerical simulations of the formation of Hurricane Gabrielle (2001). Mon. Wea. Rev., 136(8), 3151–3167.CrossRefGoogle Scholar
  41. Nakanishi, M., and H. Niino, 2004: An improved Mellor-Yamada Level-3 model with condensation physics: Its design and verification. Boundary-Layer Meteor., 112(1), 1–31.CrossRefGoogle Scholar
  42. Peng, M. S., B. -F. Jeng, and C. -P. Chang, 1993: Forecast of typhoon motion in the vicinity of Taiwan during 1989–90 using a dynamical model. Wea. Forecasting, 8(3), 309–325.CrossRefGoogle Scholar
  43. Pu, Z. -X., and S. A. Braun, 2001: Evaluation of bogus vortex techniques with four-dimensional variational data assimilation. Mon. Wea. Rev., 129(8), 2023–2039.CrossRefGoogle Scholar
  44. Riette, S., and D. Caya, 2002: Sensitivity of short simulations to the various parameters in the new CRCM spectral nudging. Research Activities in Atmospheric and Oceanic Modelling, Ritchie H., Ed., WMO/TD-No 1105, Report No. 32, 7.39–7.40.Google Scholar
  45. Rogers, M. L. Black, S. S. Chen, et al., 2007: An evaluation of microphysics fields from mesoscale model simulations of tropical cyclones. Part I: Comparisons with observations. J. Atmos. Sci., 64(6), 1811–1834.CrossRefGoogle Scholar
  46. Rogers, R., 2010: Convective-scale structure and evolution during a high-resolution simulation of tropical cyclone rapid intensification. J. Atmos. Sci., 67(1), 44–70.CrossRefGoogle Scholar
  47. Tallapragada, V., Y. C. Kwon, Q. Liu, et al., 2012: Operational implementation of high-resolution triplynested HWRF at NCEP/EMC-A major step towards addressing intensity forecast problem. The 30th Conference on Hurricanes and Tropical Meteorology, Amer. Meteor. Soc., 15–20 April 2012, Ponte Vedra Beach, Florida.Google Scholar
  48. Ueno, M., 1989: Operational bogussing and numerical prediction of typhoon in JMA. JMA/NPD Tech. Rep., 28, 48 pp.Google Scholar
  49. van Nguyen, H., and Y. -L. Chen, 2011: High-resolution initialization and simulations of Typhoon Morakot (2009). Mon. Wea. Rev., 139(5), 1463–1491.CrossRefGoogle Scholar
  50. von Storch, H., H. Langenberg, and F. Feser, 2000: A spectral nudging technique for dynamical downscaling purposes. Mon. Wea. Rev., 128(10), 3664–3673.CrossRefGoogle Scholar
  51. Wang, Y. Q., 1998: On the bogussing of tropical cyclones in numerical models: The influence of vertical structure. Meteor. Atmos. Phys., 65(3–4), 153–170.CrossRefGoogle Scholar
  52. —, 2001: An explicit simulation of tropical cyclones with a triply nested movable mesh primitive equation model: TCM3. Part I: Model description and control experiment. Mon. Wea. Rev., 129(6), 1370–1394.CrossRefGoogle Scholar
  53. Wu, C. -C., K. -H. Chou, H. -J. Cheng, et al., 2003: Eyewall contraction, breakdown and reformation in a landfalling typhoon. Geophys. Res. Lett., 30(17), 1887, doi:10.1029/2003GL017653.CrossRefGoogle Scholar
  54. —, H. J. Cheng, Y. Q. Wang, et al., 2009: A numerical investigation of the eyewall evolution of a landfalling typhoon. Mon. Wea. Rev., 137(1), 21–40.CrossRefGoogle Scholar
  55. Yang, M. -J., D. -L. Zhang, and H. -L. Huang, 2008: A modeling study of Typhoon Nari (2001) at landfall. Part I: Topographic effects. J. Atmos. Sci., 65(10), 3095–3115.CrossRefGoogle Scholar
  56. —, —, X. -D. Tang, et al., 2011: A modeling study of Typhoon Nari (2001) at landfall. Part II: Structural changes and terrain-induced asymmetries. J. Geophys. Res., 116, D09112, doi:10.1029/2010JD015445.CrossRefGoogle Scholar
  57. Yau, M. K., Y. B. Liu, D. -L. Zhang, et al., 2004: A multiscale numerical study of Hurricane Andrew (1992). Part VI: Small-scale inner-core structures and wind streaks. Mon. Wea. Rev., 132(6), 1410–1433.CrossRefGoogle Scholar
  58. Zhang, D. -L., Y. B. Liu, and M. K. Yau, 2000: A multiscale numerical study of Hurricane Andrew (1992). Part III: Dynamically-induced vertical motion. Mon. Wea. Rev., 128(11), 3772–3788.CrossRefGoogle Scholar
  59. —, —, and —, 2001: A multiscale numerical study of Hurricane Andrew (1992). Part IV: Unbalanced flows. Mon. Wea. Rev., 129(1), 92–107.CrossRefGoogle Scholar
  60. —, —, and —, 2002: A multiscale numerical study of Hurricane Andrew (1992). Part V: Inner-core thermodynamics. Mon. Wea. Rev., 130(11), 2745–2763.CrossRefGoogle Scholar
  61. —, L. Tian, and M. J. Yang, 2011: Genesis of Typhoon Nari (2001) from a mesoscale convective system. J. Geophys. Res., 116, D23104, doi:10.1029/2011JD016640.CrossRefGoogle Scholar
  62. Zhang, Q. -H., S. -J. Chen, Y. -H. Kuo, et al., 2005: Numerical study of a typhoon with a large eye: Model simulation and verification. Mon. Wea. Rev., 133(4), 725–742.CrossRefGoogle Scholar
  63. Zhang, X. Y., Q. N. Xiao, and P. J. Fitzpatrick, 2007: The impact of multisatellite data on the initialization and simulation of Hurricane Lili’s (2002) rapid weakening phase. Mon. Wea. Rev., 135(2), 526–548.CrossRefGoogle Scholar
  64. Zhu, T., D. -L. Zhang, and F. Z. Weng, 2004: Numerical simulation of Hurricane Bonnie (1998). Part I: Eyewall evolution and intensity changes. Mon. Wea. Rev., 132(1), 225–241.CrossRefGoogle Scholar
  65. —, and —, 2006: Numerical simulation of Hurricane Bonnie (1998). Part II: Sensitivity to varying cloud microphysical processes. J. Atmos. Sci., 63(1), 109–126.CrossRefGoogle Scholar
  66. Zou, X. L., and Q. N. Xiao, 2000: Studies on the initialization and simulation of a mature hurricane using a variational bogus data assimilation scheme. J. Atmos. Sci., 57(6), 836–860.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hui Wang (王 慧)
    • 1
    • 2
  • Yuqing Wang (王玉清)
    • 2
  • Haiming Xu (徐海明)
    • 1
  1. 1.Key Laboratory of Meteorological Disaster of Ministry of EducationNanjing University of Information Science & TechnologyNanjingChina
  2. 2.International Pacific Research Center and Department of Meteorology, School of Ocean and Earth Science and TechnologyUniversity of Hawaii at ManoaHonoluluUSA

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