Cover Weather and Forecasting
Weather and Forecasting

  • Bender, M. A., Ross R. J. , Tuleya R. E. , and Kurihara Y. , 1993: Improvements in tropical cyclone track and intensity forecasts using the GFDL initialization system. Mon. Wea. Rev., 121 , 2046–2061.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • DeMaria, M., and Kaplan J. , 1994: A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic basin. Wea. Forecasting, 9 , 209–220.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • DeMaria, M., Mainelli M. , Shay L. K. , Knaff J. A. , and Kaplan J. , 2005: Further improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS). Wea. Forecasting, 20 , 531–543.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • DeMaria, M., Knaff J. A. , and Sampson C. , 2007: Evaluation of long-term trends in tropical cyclone intensity forecasts. Meteor. Atmos. Phys., 97 , 19–28.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Jarvinen, B. R., and Neumann C. J. , 1979: Statistical forecast of tropical cyclone intensity. NOAA Tech. Memo. NS NHC-10, 22 pp.

  • Kaplan, J., and DeMaria M. , 2003: Large-scale characteristics of rapidly intensifying tropical cyclones in the North Atlantic basin. Wea. Forecasting, 18 , 1093–1108.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Krishnamurti, T. N., Kishtawal C. M. , LaRow T. , Bachiochi D. , Zhang Z. , Williford C. E. , Gadgil S. , and Surendran S. , 1999: Improved weather and seasonal climate forecasts from multimodel superensemble. Science, 285 , 1548–1550.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Krishnamurti, T. N., Kishtawal C. M. , Shin D. W. , and Williford C. E. , 2000a: Improving tropical precipitation forecasts from a multianalysis superensemble. J. Climate, 13 , 4217–4227.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Krishnamurti, T. N., and Coauthors, 2000b: Multimodel ensemble forecasts for weather and seasonal climate. J. Climate, 13 , 4196–4216.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kurihara, Y., Tuleya R. E. , and Bender M. A. , 1998: The GFDL hurricane prediction system and its performance during the 1995 hurricane season. Mon. Wea. Rev., 126 , 1306–1322.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Panofsky, H. A., and Brier G. W. , 1958: Some Applications of Statistics to Meteorology. The Pennsylvania State University, 224 pp.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 26 26 26
PDF Downloads 1 1 1
Article Type:
Research Article

An Alternative Tropical Cyclone Intensity Forecast Verification Technique

Sim D. Aberson1
View More View Less
  • 1 NOAA/AOML/Hurricane Research Division, Miami, Florida
Print Publication:
01 Dec 2008
DOI:
https://doi.org/10.1175/2008WAF2222123.1
Page(s):
1304–1310
Restricted access

Abstract

The National Hurricane Center (NHC) does not verify official or model forecasts if those forecasts call for a tropical cyclone to dissipate or if the real tropical cyclone dissipates. A new technique in which these forecasts are included in a contingency table with all other forecasts is presented. Skill scores and probabilities are calculated. Forecast verifications with the currently used technique have shown a slight improvement in intensity forecasts. The new technique, taking into account all forecasts, suggests that the probability of a forecast having a large (>30 kt) error is decreasing, and the likelihood of the error being less than about 10 kt is increasing in time, at all forecast lead times except 12 h when the forecasts are already quite good.

Corresponding author address: Sim D. Aberson, NOAA/AOML/Hurricane Research Division, Miami, FL 33149. Email: sim.aberson@noaa.gov

Abstract

The National Hurricane Center (NHC) does not verify official or model forecasts if those forecasts call for a tropical cyclone to dissipate or if the real tropical cyclone dissipates. A new technique in which these forecasts are included in a contingency table with all other forecasts is presented. Skill scores and probabilities are calculated. Forecast verifications with the currently used technique have shown a slight improvement in intensity forecasts. The new technique, taking into account all forecasts, suggests that the probability of a forecast having a large (>30 kt) error is decreasing, and the likelihood of the error being less than about 10 kt is increasing in time, at all forecast lead times except 12 h when the forecasts are already quite good.

Corresponding author address: Sim D. Aberson, NOAA/AOML/Hurricane Research Division, Miami, FL 33149. Email: sim.aberson@noaa.gov

Save