Editorial Type:
Article
Article Type:
Research Article

Improvements to a Tropical Cyclone Initialization Scheme and Impacts on Forecasts

Hiep Van Nguyen Department of Atmospheric Sciences, University of Hawaii at Manoa, Honolulu, Hawaii

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Yi-Leng Chen Department of Atmospheric Sciences, University of Hawaii at Manoa, Honolulu, Hawaii

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Print Publication:
01 Nov 2014
DOI:
https://doi.org/10.1175/MWR-D-13-00326.1
Page(s):
4340–4356
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Abstract

This study makes improvements to the tropical cyclone (TC) initialization method introduced by Nguyen and Chen (i.e., the NC2011 scheme). The authors found that prescribing sea level pressure associated with the initial vortex using a modified Fujita formula has very little impact on the vortex structure and intensity during a series of 1-h model integration and relocation. On the other hand, inserting an artificial warm core makes the vortex spin up much faster. When a warm core is inserted during the initial spinup process, the computational time required for model initialization is reduced by ½–⅓. Because prescribed sea level pressure is not required to spin up the vortex, information on vortex size, such as radius of maximum wind, is no longer needed. The performance of the improved NC2011 scheme with an initial prescribed warm core during the initial spinup process is tested for typhoons that made landfall over southern China or Vietnam in 2006. Before landfall, these storms were over the open ocean where conventional data were sparse, without special observations. Two sets of model runs, with (NC2011-CTRL) and without (CTRL) vortex initialization, are performed for comparison. The initial and time-dependent boundary conditions are from the NCEP Final Analyses (FNL). There are twelve 48-h simulations in each run set. Results show that the vortex initialization improves TC track and intensity simulations.

Current affiliation: Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam.

Corresponding author address: Yi-Leng Chen, Dept. of Meteorology, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, Honolulu, HI 96822. E-mail: yileng@hawaii.edu

Abstract

This study makes improvements to the tropical cyclone (TC) initialization method introduced by Nguyen and Chen (i.e., the NC2011 scheme). The authors found that prescribing sea level pressure associated with the initial vortex using a modified Fujita formula has very little impact on the vortex structure and intensity during a series of 1-h model integration and relocation. On the other hand, inserting an artificial warm core makes the vortex spin up much faster. When a warm core is inserted during the initial spinup process, the computational time required for model initialization is reduced by ½–⅓. Because prescribed sea level pressure is not required to spin up the vortex, information on vortex size, such as radius of maximum wind, is no longer needed. The performance of the improved NC2011 scheme with an initial prescribed warm core during the initial spinup process is tested for typhoons that made landfall over southern China or Vietnam in 2006. Before landfall, these storms were over the open ocean where conventional data were sparse, without special observations. Two sets of model runs, with (NC2011-CTRL) and without (CTRL) vortex initialization, are performed for comparison. The initial and time-dependent boundary conditions are from the NCEP Final Analyses (FNL). There are twelve 48-h simulations in each run set. Results show that the vortex initialization improves TC track and intensity simulations.

Current affiliation: Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam.

Corresponding author address: Yi-Leng Chen, Dept. of Meteorology, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, Honolulu, HI 96822. E-mail: yileng@hawaii.edu
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  • Bao, J.-W., S. G. Gopalakrishnan, S. A. Michelson, F. D. Marks, and M. T. Montgomery, 2012: Impact of physics representations in the HWRFX on simulated hurricane structure and pressure–wind relationships. Mon. Wea. Rev., 140, 3278–3299, doi:10.1175/MWR-D-11-00332.1.

    • Search Google Scholar
    • Export Citation

  • Betts, A. K., and M. J. Miller, 1993: The Betts–Miller scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 107–121.

    • Search Google Scholar
    • Export Citation

  • Chen, C.-Y., Y.-L. Chen, and H. V. Nguyen, 2014: The spin-up process of a cyclone vortex in a tropical cyclone initialization scheme and its impact on the initial TC structure. SOLA, 10, 93–97, doi:10.2151/sola.2014-019.

    • Search Google Scholar
    • Export Citation

  • Davidson, N. E., and H. C. Weber, 2000: The BMRC high-resolution tropical cyclone prediction system: TC-LAPS. Mon. Wea. Rev., 128, 1245–1265, doi:10.1175/1520-0493(2000)128<1245:TBHRTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Davis, C., and S. Low-Nam, 2001: The NCAR-AFWA tropical cyclone bogussing scheme. Air Force Weather Agency (AFWA) Rep., 12 pp. [Available online at http://sgi200.ust.hk/mm5/mm5v3/tc-report.pdf.]

  • 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, doi:10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Dunnavan, G. M., and J. W. Diercks, 1980: An analysis of Super Typhoon Tip (October 1979). Mon. Wea. Rev., 108, 1915–1923, doi:10.1175/1520-0493(1980)108<1915:AAOSTT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Fujita, T., 1952: Pressure distribution within typhoon. Geophys. Mag., 23, 437–451.

  • Grell, G. A., and D. Devenyi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, doi:10.1029/2002GL015311.

    • Search Google Scholar
    • Export Citation

  • Hawkins, H. F., and D. T. Rubsam, 1968: Hurricane Hilda, 1964. Mon. Wea. Rev., 96, 617–636, doi:10.1175/1520-0493(1968)096<0617:HH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Holland, G. J., 1980: An analytic model of the wind and pressure profiles in hurricanes. Mon. Wea. Rev., 108, 1212–1218, doi:10.1175/1520-0493(1980)108<1212:AAMOTW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Hong, S.-Y., and J.-O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129–151.

  • Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103–120, doi:10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Janjić, Z. I., 1994: The step-mountain eta coordinate model: Further development of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927–945, doi:10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Janjić, Z. I., 2000: Comments on “Development and evaluation of a convection scheme for use in climate models.” J. Atmos. Sci., 57, 3686–3686, doi:10.1175/1520-0469(2000)057<3686:CODAEO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181, doi:10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kain, J. S., 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.

  • Kidder, S. Q., M. D. Goldberg, R. M. Zehr, M. DeMaria, J. F. W. Purdom, C. S. Velden, N. C. Grody, and S. J. Kusselson, 2000: Satellite analysis of tropical cyclones using the Advanced Microwave Sounding Unit (AMSU). Bull. Amer. Meteor. Soc., 81, 1241–1260, doi:10.1175/1520-0477(2000)081<1241:SAOTCU>2.3.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kucas, M. E., 2010: Challenges of forecasting tropical cyclone intensity change at the Joint Typhoon Warning Center. 29th Conf. on Hurricanes and Tropical Meteorology, Tucson, AZ, Amer. Meteor. Soc., 9C.6. [Available online at https://ams.confex.com/ams/pdfpapers/168732.pdf.]

  • Kurihara, Y., M. A. Bender, and R. J. Ross, 1993: An initialization scheme of hurricane models by vortex specification. Mon. Wea. Rev., 121, 2030–2045, doi:10.1175/1520-0493(1993)121<2030:AISOHM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kwon, I.-H., and H.-B. Cheong, 2010: Tropical cyclone initialization with spherical high-order filter and idealized three-dimensional bogus vortex. Mon. Wea. Rev., 138, 1344–1367, doi:10.1175/2009MWR2943.1.

    • Search Google Scholar
    • Export Citation

  • Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 1065–1092, doi:10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Liu, Y., 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, 3073–3093, doi:10.1175/1520-0493(1997)125<3073:AMNSOH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the long-wave. J. Geophys. Res., 102, 16 663–16 682, doi:10.1029/97JD00237.

    • Search Google Scholar
    • Export Citation

  • Monin, A. S., and A. M. Obukhov, 1954: Basic laws of turbulent mixing in the surface layer of the atmosphere (in Russian). Contrib. Geophys. Inst. Acad. Sci. USSR,151, 163–187.

  • Nguyen, H. V., and Y.-L. Chen, 2011: High-resolution initialization and simulations of Typhoon Morakot (2009). Mon. Wea. Rev., 139, 1463–1491, doi:10.1175/2011MWR3505.1.

    • Search Google Scholar
    • Export Citation

  • Noh, Y., W. G. Cheon, S.-Y. Hong, and S. Raasch, 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 401–427, doi:10.1023/A:1022146015946.

    • Search Google Scholar
    • Export Citation

  • Pu, Z. X., and S. A. Braun, 2001: Evaluation of bogus vortex techniques with four dimensional variational data assimilation. Mon. Wea. Rev., 129, 2023–2039, doi:10.1175/1520-0493(2001)129<2023:EOBVTW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Rogers, E., T. Black, B. Ferrier, Y. Lin, D. Parrish, and G. DiMego, cited 2001: Changes to the NCEP Meso Eta Analysis and Forecast System: Increase in resolution, new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis. NWS Tech. Procedures Bull. 488, NOAA/NWS. [Available online at http://www.emc.ncep.noaa.gov/mmb/mmbpll/eta12tpb.]

  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the advanced research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v2.pdf.]

  • Velden, C. S., B. M. Goodman, and R. T. Merrill, 1991: Western North Pacific tropical cyclone intensity estimation from NOAA polar-orbiting satellite microwave data. Mon. Wea. Rev., 119, 159–168, doi:10.1175/1520-0493(1991)119<0159:WNPTCI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Wu, C.-C., and Coauthors, 2005: Dropwindsonde observations for typhoon surveillance near the Taiwan region (DOTSTAR): An overview. Bull. Amer. Meteor. Soc., 86, 787–790, doi:10.1175/BAMS-86-6-787.

    • Search Google Scholar
    • Export Citation

  • Wu, C.-C., K.-H. Chou, Y. Wang, and Y.-H. Kuo, 2006: Tropical cyclone initialization and prediction based on four-dimensional variational data assimilation. J. Atmos. Sci., 63, 2383–2395, doi:10.1175/JAS3743.1.

    • Search Google Scholar
    • Export Citation

  • Wu, C.-C., Y.-H. Huang, and G.-Y. Lien, 2012: Concentric eyewall formation in Typhoon Sinlaku (2008). Part I: Assimilation of T-PARC data based on the ensemble Kalman filter (EnKF). Mon. Wea. Rev., 140, 506–527, doi:10.1175/MWR-D-11-00057.1.

    • Search Google Scholar
    • Export Citation

  • Zhang, S., T. Li, X. Ge, M. Peng, and N. Pan, 2012: A 3DVAR-based dynamical initialization scheme for tropical cyclone predictions. Wea. Forecasting, 27, 473–483, doi:10.1175/WAF-D-10-05066.1.

    • Search Google Scholar
    • Export Citation

  • Zhao, Y., B. Wang, and Y. Wang, 2007: Initialization and simulation of a landfalling typhoon using a variational bogus mapped data assimilation (BMDA). Meteor. Atmos. Phys., 98, 269–282, doi:10.1007/s00703-007-0265-4.

    • Search Google Scholar
    • Export Citation

  • Zou, X., and Q. Xiao, 2000: Studies on the initialization and simulation of a mature hurricane using a variational bogus data assimilation scheme. J. Atmos. Sci., 57, 836–860, doi:10.1175/1520-0469(2000)057<0836:SOTIAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
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