• Chen, Y., and M. K. Yau, 2003: Asymmetric structures in a simulated landfalling hurricane. J. Atmos. Sci., 60 , 22942312.

  • DeMaria, M., and J. Kaplan, 1994: A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic basin. Wea. Forecasting, 9 , 209220.

    • Search Google Scholar
    • Export Citation
  • Depperman, R. C., 1947: Notes on the origin and structures of Philippine typhoons. Bull. Amer. Meteor. Soc., 28 , 399404.

  • Georgiou, P., 1985: Design wind speeds in tropical cyclone prone regions. Ph.D. thesis, University of Western Ontario, 295 pp.

  • Holland, G. J., 1980: An analytic model of the wind and pressure profiles in hurricanes. Mon. Wea. Rev., 108 , 12121218.

  • Houston, S. H., W. A. Shaffer, M. D. Powell, and J. Chen, 1999: Comparisons of HRD and SLOSH surface wind fields in hurricanes: Implications for storm surge modeling. Wea. Forecasting, 14 , 671686.

    • Search Google Scholar
    • Export Citation
  • Hsu, S. A., and Z. Yan, 1998: A note on the radius of maximum wind for hurricanes. J. Coastal Res., 14 , 667668.

  • Hughes, L. A., 1952: On the low-level wind structure of tropical storms. J. Meteor., 9 , 422428.

  • Jakobsen, F., and H. Madsen, 2004: Comparison and further development of parameteric tropical cyclone models for storm surge modelling. J. Wind Eng. Ind. Aerodyn., 92 , 375391.

    • Search Google Scholar
    • Export Citation
  • Jarvinen, B. R., and C. J. Neumann, 1979: Statistical forecasts of tropical cyclone intensity for the North Atlantic basin. NOAA Tech. Memo., NWS NHC-10, 22 pp.

  • Jelesnianski, C. P., J. Chen, and W. A. Shaffer, 1992: SLOSH: Sea, lake and overland surges from hurricane. National Weather Service, Silver Spring, MD, 71 pp.

  • Large, W. G., and S. Pond, 1981: Open ocean momentum flux measurements in moderate to strong winds. J. Phys. Oceanogr., 11 , 324336.

  • Powell, M. D., and S. H. Houston, 1996: Hurricane Andrew’s landfall in south Florida. Part II: Surface wind fields and potential real-time applications. Wea. Forecasting, 11 , 329349.

    • Search Google Scholar
    • Export Citation
  • Powell, M. D., and S. H. Houston, 1998: Surface wind fields of 1995 Hurricanes Erin, Opal, Luis, Marilyn, and Roxanne at landfall. Mon. Wea. Rev., 126 , 12591273.

    • Search Google Scholar
    • Export Citation
  • Powell, M. D., S. H. Houston, and T. A. Reinhold, 1996: Hurricane Andrew’s landfall in south Florida. Part I: Standardizing measurements for documentation of surface wind fields. Wea. Forecasting, 11 , 304328.

    • Search Google Scholar
    • Export Citation
  • Riehl, H., 1954: Tropical Meteorology. McGraw-Hill, 392 pp.

  • Ross, R. J., and Y. Kurihara, 1992: A simplified scheme to simulate asymmetries due to the beta effect in barotropic vortices. J. Atmos. Sci., 49 , 16201628.

    • Search Google Scholar
    • Export Citation
  • Schloemer, R. W., 1954: Analysis and synthesis of hurricane wind patterns over Lake Okeechobee. NOAA Hydromet Rep. 31, 49 pp.

  • Shapiro, L., 1983: The asymmetric boundary layer flow under a translating hurricane. J. Atmos. Sci., 40 , 19841998.

  • Wang, Y., and G. J. Holland, 1996: Tropical cyclone motion and evolution in vertical shear. J. Atmos. Sci., 53 , 33133332.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 474 226 9
PDF Downloads 407 202 8

A Real-Time Hurricane Surface Wind Forecasting Model: Formulation and Verification

View More View Less
  • 1 Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina
  • | 2 College of Physical and Mathematical Sciences, North Carolina State University, Raleigh, North Carolina
  • | 3 Department of Statistics, North Carolina State University, Raleigh, North Carolina
Restricted access

Abstract

A real-time hurricane wind forecast model is developed by 1) incorporating an asymmetric effect into the Holland hurricane wind model; 2) using the National Oceanic and Atmospheric Administration (NOAA)/National Hurricane Center’s (NHC) hurricane forecast guidance for prognostic modeling; and 3) assimilating the National Data Buoy Center (NDBC) real-time buoy data into the model’s initial wind field. The method is validated using all 2003 and 2004 Atlantic and Gulf of Mexico hurricanes. The results show that 6- and 12-h forecast winds using the asymmetric hurricane wind model are statistically more accurate than using a symmetric wind model. Detailed case studies were conducted for four historical hurricanes, namely, Floyd (1999), Gordon (2000), Lily (2002), and Isabel (2003). Although the asymmetric model performed generally better than the symmetric model, the improvement in hurricane wind forecasts produced by the asymmetric model varied significantly for different storms. In some cases, optimizing the symmetric model using observations available at initial time and forecast mean radius of maximum wind can produce comparable wind accuracy measured in terms of rms error of wind speed. However, in order to describe the asymmetric structure of hurricane winds, an asymmetric model is needed.

Corresponding author address: Lian Xie, Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Box 8208, Raleigh, NC 27695-8208. Email: lian_xie@ncsu.edu

Abstract

A real-time hurricane wind forecast model is developed by 1) incorporating an asymmetric effect into the Holland hurricane wind model; 2) using the National Oceanic and Atmospheric Administration (NOAA)/National Hurricane Center’s (NHC) hurricane forecast guidance for prognostic modeling; and 3) assimilating the National Data Buoy Center (NDBC) real-time buoy data into the model’s initial wind field. The method is validated using all 2003 and 2004 Atlantic and Gulf of Mexico hurricanes. The results show that 6- and 12-h forecast winds using the asymmetric hurricane wind model are statistically more accurate than using a symmetric wind model. Detailed case studies were conducted for four historical hurricanes, namely, Floyd (1999), Gordon (2000), Lily (2002), and Isabel (2003). Although the asymmetric model performed generally better than the symmetric model, the improvement in hurricane wind forecasts produced by the asymmetric model varied significantly for different storms. In some cases, optimizing the symmetric model using observations available at initial time and forecast mean radius of maximum wind can produce comparable wind accuracy measured in terms of rms error of wind speed. However, in order to describe the asymmetric structure of hurricane winds, an asymmetric model is needed.

Corresponding author address: Lian Xie, Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Box 8208, Raleigh, NC 27695-8208. Email: lian_xie@ncsu.edu

Save