• Aberson, S. D., 2001: The ensemble of tropical cyclone track forecasting models in the North Atlantic basin (1976–2000). Bull. Amer. Meteor. Soc., 82 , 18951904.

    • Search Google Scholar
    • Export Citation
  • Barrett, B. S., and L. M. Leslie, 2005: An examination of the quality of the Atlantic tropical cyclone database. Preprints, 16th Conf. on Climate Variability and Change, San Diego, CA, Amer. Meteor. Soc., CD-ROM, P1.30.

  • Barrett, B. S., L. M. Leslie, and C-S. Liou, 2004: Relationship between climatology and model track, bearing, and speed errors. Preprints, 20th Conf. on Weather Analysis and Forecasting, Seattle, WA, Amer. Meteor. Soc., CD-ROM, 13.6.

  • Bender, M. A., and I. Ginis, 2000: Real-case simulations of hurricane–ocean interaction using a high-resolution coupled model: Effects on hurricane intensity. Mon. Wea. Rev., 128 , 917946.

    • Search Google Scholar
    • Export Citation
  • Bender, M. A., R. J. Ross, R. E. Tuleya, and Y. Kurihara, 1993: Improvements in tropical cyclone track forecasts using the GFDL initialization system. Mon. Wea. Rev., 121 , 20462061.

    • Search Google Scholar
    • Export Citation
  • Bessafi, M., A. Lasserre-Bigorry, C. J. Neumann, F. Pignolet-Tardan, D. Payet, and M. Lee-Ching-Ken, 2002: Statistical prediction of tropical cyclone motion: An analog–CLIPER approach. Wea. Forecasting, 17 , 821831.

    • Search Google Scholar
    • Export Citation
  • Buckley, B. W., L. M. Leslie, and M. S. Speer, 2003: The impact of observational technology on climate database quality: Tropical cyclones in the Tasman Sea. J. Climate, 16 , 26402645.

    • Search Google Scholar
    • Export Citation
  • Caplan, P., J. Derber, W. Gemmill, S-Y. Hong, H-L. Pan, and D. Parrish, 1997: Changes to the 1995 NCEP operational medium-range forecast model analysis–forecast system. Wea. Forecasting, 12 , 581594.

    • Search Google Scholar
    • Export Citation
  • Chen, Q-S., L-E. Bai, and D. H. Bromwich, 1997: A harmonic-Fourier spectral limited-area model with an external wind lateral boundary condition. Mon. Wea. Rev., 125 , 143167.

    • Search Google Scholar
    • Export Citation
  • Côté, J., S. Gravel, A. Méthot, A. Patoine, M. Roch, and A. N. Staniforth, 1998: The operational CMC–MRB Global Environmental Multiscale (GEM) model. Part I: Design consideration and formulation. Mon. Wea. Rev., 126 , 13731395.

    • Search Google Scholar
    • Export Citation
  • Cullen, M. J. P., 1993: The unified forecast/climate model. Meteor. Mag., 122 , 81122.

  • Fraedrich, K., C. C. Raible, and F. Sielmann, 2003: Analog ensemble forecasts of tropical cyclone tracks in the Australian region. Wea. Forecasting, 18 , 311.

    • Search Google Scholar
    • Export Citation
  • Franklin, J. L., C. J. McAdie, and M. B. Lawrence, 2003: Trends in track forecasting for tropical cyclones threatening the United States, 1970–2001. Bull. Amer. Meteor. Soc., 84 , 11971203.

    • Search Google Scholar
    • Export Citation
  • Goerss, J. S., 2000: Tropical cyclone track forecasts using an ensemble of dynamical models. Mon. Wea. Rev., 128 , 11871193.

  • Goerss, J. S., and R. Jeffries, 1994: Assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System. Wea. Forecasting, 9 , 557576.

    • Search Google Scholar
    • Export Citation
  • Goerss, J. S., C. R. Sampson, and J. M. Gross, 2004: A history of western North Pacific tropical cyclone track forecast skill. Wea. Forecasting, 19 , 633638.

    • Search Google Scholar
    • Export Citation
  • Gray, W. M., P. J. Klotzbach, and W. Thorston, 2004: Summary of 2004 Atlantic tropical cyclone activity and verification of author’s seasonal and monthly forecasts. Dept. of Atmospheric Science Rep., Colorado State University, Fort Collins, CO, 38 pp.

  • Heming, J. T., J. C. L. Chan, and A. M. Radford, 1995: A new scheme for the initialization of tropical cyclones in the UK Meteorological Office global model. Meteor. Appl., 2 , 171184.

    • Search Google Scholar
    • Export Citation
  • Hogan, T. F., and T. E. Rosmond, 1991: The description of the Navy Operational Global Atmospheric Prediction System’s spectral forecast model. Mon. Wea. Rev., 119 , 17861815.

    • Search Google Scholar
    • Export Citation
  • Holland, G. J., 1983: Tropical cyclone motion: Environmental interaction plus a beta effect. J. Atmos. Sci., 40 , 328342.

  • Hope, J. R., and C. J. Neumann, 1970: An operational technique for relating the movement of existing tropical cyclones to past tracks. Mon. Wea. Rev., 98 , 925933.

    • Search Google Scholar
    • Export Citation
  • Horsfall, F., M. DeMaria, and J. M. Gross, 1997: Optimal use of large-scale boundary and initial fields for limited-area hurricane forecast models. Preprints, 22d Conf. on Hurricanes and Tropical Meteorology, Fort Collins, CO, Amer. Meteor. Soc., 571–572.

  • Jarvinen, B. R., C. J. Neumann, and M. A. S. Davis, 1984: A tropical cyclone data tape for the North Atlantic basin, 1886–1983: Contents, limitations, and uses. NOAA Tech. Memo. NWS NHC-22, 28 pp.

  • Kalnay, E., M. Kanamitsu, and W. E. Baker, 1990: Global numerical weather prediction at the National Meteorological Center. Bull. Amer. Meteor. Soc., 71 , 14101428.

    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., 1989: Description of the NMC global data assimilation and forecast system. Wea. Forecasting, 4 , 335342.

  • Krishnamurti, T. N., C. M. Kishtawal, T. LaRow, D. Bachiochi, Z. Zhang, C. E. Williford, S. Gadgil, and S. Surendran, 1999: Improved skills for weather and seasonal climate forecasts from multimodel superensemble. Science, 285 , 15481550.

    • Search Google Scholar
    • Export Citation
  • Krishnamurti, T. N., C. M. Kishtawal, T. LaRow, D. Bachiochi, Z. Zhang, C. E. Williford, S. Gadgil, and S. Surendran, 2000a: Improving tropical precipitation forecasts from a multianalysis superensemble. J. Climate, 13 , 42174227.

    • Search Google Scholar
    • Export Citation
  • Krishnamurti, T. N., C. M. Kishtawal, D. W. Shin, and C. E. Williford, 2000b: Multimodel superensemble forecasts for weather and seasonal climate. J. Climate, 13 , 41964216.

    • Search Google Scholar
    • Export Citation
  • Krishnamurti, T. N., and Coauthors, 2001: Real-time multianalysis–multimodel superensemble forecasts of precipitation using TRMM and SSM/I products. Mon. Wea. Rev., 129 , 28612883.

    • Search Google Scholar
    • Export Citation
  • Kurihara, Y., M. A. Bender, and R. T. Ross, 1993: An initialization scheme of hurricane models by vortex specification. Mon. Wea. Rev., 121 , 20302045.

    • Search Google Scholar
    • Export Citation
  • Kurihara, Y., M. A. Bender, R. E. Tuleya, and R. J. Ross, 1995: Improvements in the GFDL hurricane prediction system. Mon. Wea. Rev., 123 , 27912801.

    • Search Google Scholar
    • Export Citation
  • Kurihara, Y., R. E. Tuleya, and M. A. Bender, 1998: The GFDL hurricane prediction system and its performance in the 1995 hurricane season. Mon. Wea. Rev., 126 , 13061322.

    • Search Google Scholar
    • Export Citation
  • Landsea, C. W., 1993: A climatology of intense (or major) Atlantic hurricanes. Mon. Wea. Rev., 121 , 17031713.

  • Landsea, C. W., N. Nicholls, W. M. Gray, and L. A. Avila, 1996: Downward trends in the frequency of intense Atlantic hurricanes during the past five decades. Geophys. Res. Lett., 23 , 16971700.

    • Search Google Scholar
    • Export Citation
  • Lawrence, M. B., 2002: Tropical cyclone report: Hurricane Lili 21 September-04 October. National Hurricane Center, Miami, FL, 14 pp. [Available online at http://www.nhc.noaa.gov/2002lili.shtml.].

  • Leslie, L. M., G. J. Holland, M. Glover, and F. J. Woodcock, 1990: A climatological-persistence (CLIPER) scheme for predicting Australian region tropical cyclone tracks. Aust. Meteor. Mag., 38 , 8792.

    • Search Google Scholar
    • Export Citation
  • Lord, S. J., 1993: Recent developments in tropical cyclone track forecasting with the NMC global analysis and forecast system. Preprints, 20th Conf. on Hurricanes and Tropical Meteorology, San Antonio, TX, Amer. Meteor. Soc., 290–291.

  • Marks, D. G., 1992: The beta and advection model for hurricane track forecasting. NOAA Tech. Memo. NWS NMC-70, 89 pp.

  • McAdie, C. J., and M. B. Lawrence, 2000: Improvements to tropical cyclone track forecasting in the Atlantic basin, 1970–1998. Bull. Amer. Meteor. Soc., 81 , 989999.

    • Search Google Scholar
    • Export Citation
  • Neumann, C. J., 1972: An alternate to the HURRAN tropical cyclone forecast system. NOAA Tech. Memo. NWS SR-62, 22 pp.

  • Neumann, C. J., and J. R. Hope, 1972: Performance analysis of the HURRAN tropical cyclone forecast system. Mon. Wea. Rev., 100 , 245255.

    • Search Google Scholar
    • Export Citation
  • Neumann, C. J., and J. M. Pelissier, 1981a: An analysis of Atlantic tropical cyclone forecast errors, 1970–1979. Mon. Wea. Rev., 109 , 12481266.

    • Search Google Scholar
    • Export Citation
  • Neumann, C. J., and J. M. Pelissier, 1981b: Models for the prediction of tropical cyclone motion over the North Atlantic: An operational evaluation. Mon. Wea. Rev., 109 , 522538.

    • Search Google Scholar
    • Export Citation
  • Neumann, C. J., and C. J. McAdie, 1991: A revised National Hurricane Center NHC83 model (NHC90). NOAA Tech. Memo. NWS NHC-44, 35 pp.

  • Neumann, C. J., B. R. Jarvinen, and A. G. Pike, 1981: Tropical cyclones of the North Atlantic Ocean, 1871–1981. Historical Climatology Series 6-2, National Climatic Data Center, Asheville, NC, 174 pp.

  • Pasch, R. J., M. B. Lawrence, L. A. Avila, J. L. Beven, J. L. Franklin, and S. R. Stewart, 2004: Atlantic hurricane season of 2002. Mon. Wea. Rev., 132 , 18291859.

    • Search Google Scholar
    • Export Citation
  • Pike, A. C., and C. J. Neumann, 1987: The variation of track forecast difficulty among tropical cyclone basins. Wea. Forecasting, 2 , 237241.

    • Search Google Scholar
    • Export Citation
  • Powell, M. D., and S. D. Aberson, 2001: Accuracy of United States tropical cyclone landfall forecasts in the Atlantic basin (1976–2000). Bull. Amer. Meteor. Soc., 82 , 27492768.

    • Search Google Scholar
    • Export Citation
  • Sheets, R. H., 1990: The National Hurricane Center: Past, present and future. Wea. Forecasting, 5 , 185232.

  • Shuman, F. G., 1989: History of numerical weather prediction at the National Meteorological Center. Wea. Forecasting, 4 , 286296.

  • Sievers, O., K. Fraedrich, and C. C. Raible, 2000: Self-adapting analog ensemble predictions of tropical cyclone tracks. Wea. Forecasting, 15 , 623629.

    • Search Google Scholar
    • Export Citation
  • Simpson, R. H., 1974: The hurricane disaster potential scale. Weatherwise, 27 ., 169, 186.

  • Stewart, S. R., 2004: Tropical cyclone report: Hurricane Ivan 2–26 September 2004. National Hurricane Center, Miami, FL, 44 pp. [Available online at http://www.nhc.noaa.gov/2004ivan.shtml.].

  • Velden, C. S., and L. M. Leslie, 1991: The basic relationship between tropical cyclone intensity and the depth of the environmental steering layer in the Australian region. Wea. Forecasting, 6 , 244253.

    • Search Google Scholar
    • Export Citation
  • Weber, H. C., 2003: Hurricane track prediction using a statistical ensemble of numerical models. Mon. Wea. Rev., 131 , 749770.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 60 33 4
PDF Downloads 43 29 4

An Example of the Value of Strong Climatological Signals in Tropical Cyclone Track Forecasting: Hurricane Ivan (2004)

View More View Less
  • 1 School of Meteorology, University of Oklahoma, Norman, Oklahoma
Restricted access

Abstract

Since 1970, tropical cyclone (TC) track forecasts have improved steadily in the Atlantic basin. This improvement has been linked primarily to advances in numerical weather prediction (NWP) models. Concurrently, with few exceptions, the development and operational use of statistical track prediction schemes have experienced a relative decline. Statistical schemes provided the most accurate TC track forecasts until approximately the late 1980s. In this note, it is shown that increased reliance on the global NWP models does not always guarantee the best forecast. Here, Hurricane Ivan is used from the 2004 Atlantic TC season as a classical example, and reminder, of how strong climatological signals still can add substantial value to TC track forecasts, in the form of improved accuracy and increased timeliness at minimal computational cost.

In an 8-day period in early September 2004, Hurricane Ivan was repeatedly, and incorrectly, forecast by 12 operational NWP models to move with a significant northward (poleward) component. It was found that the mean 24-h trajectory forecasts of a consensus of five commonly used NWP track prediction aids had a statistically significant right-of-track bias. Furthermore, the official track forecasts, which relied heavily on erroneous numerical guidance over this period, were also found to have significant poleward trajectory errors. At the same time, a climatology-based prediction technique, drawn entirely from the historical record of motion characteristics of TCs in geographical locations similar to Ivan, correctly and consistently indicated a more westward motion component, had a small directional spread, and was supported by a large number of archived cases. This climatological signal was in conflict with the deterministic NWP model output, and it is suggested that the large errors in the official track forecast for TC Ivan could have been reduced considerably by taking into greater account such a strong climatological signal. The potential impact of such an error reduction is a saving of lives and billions of dollars in both actual damage and unnecessary evacuations costs, for just this one hurricane. We also suggest that this simple strategy of examining the strength of the climatological signal be considered for all TCs to identify cases where the NWP and official forecasts differ significantly from strong, persistent climatological signals.

Corresponding author address: Bradford S. Barrett, School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072. Email: bradb@ou.edu

Abstract

Since 1970, tropical cyclone (TC) track forecasts have improved steadily in the Atlantic basin. This improvement has been linked primarily to advances in numerical weather prediction (NWP) models. Concurrently, with few exceptions, the development and operational use of statistical track prediction schemes have experienced a relative decline. Statistical schemes provided the most accurate TC track forecasts until approximately the late 1980s. In this note, it is shown that increased reliance on the global NWP models does not always guarantee the best forecast. Here, Hurricane Ivan is used from the 2004 Atlantic TC season as a classical example, and reminder, of how strong climatological signals still can add substantial value to TC track forecasts, in the form of improved accuracy and increased timeliness at minimal computational cost.

In an 8-day period in early September 2004, Hurricane Ivan was repeatedly, and incorrectly, forecast by 12 operational NWP models to move with a significant northward (poleward) component. It was found that the mean 24-h trajectory forecasts of a consensus of five commonly used NWP track prediction aids had a statistically significant right-of-track bias. Furthermore, the official track forecasts, which relied heavily on erroneous numerical guidance over this period, were also found to have significant poleward trajectory errors. At the same time, a climatology-based prediction technique, drawn entirely from the historical record of motion characteristics of TCs in geographical locations similar to Ivan, correctly and consistently indicated a more westward motion component, had a small directional spread, and was supported by a large number of archived cases. This climatological signal was in conflict with the deterministic NWP model output, and it is suggested that the large errors in the official track forecast for TC Ivan could have been reduced considerably by taking into greater account such a strong climatological signal. The potential impact of such an error reduction is a saving of lives and billions of dollars in both actual damage and unnecessary evacuations costs, for just this one hurricane. We also suggest that this simple strategy of examining the strength of the climatological signal be considered for all TCs to identify cases where the NWP and official forecasts differ significantly from strong, persistent climatological signals.

Corresponding author address: Bradford S. Barrett, School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072. Email: bradb@ou.edu

Save