Accuracy of Atlantic and Eastern North Pacific Tropical Cyclone Intensity Forecast Guidance

Russell L. Elsberry Department of Meteorology, Naval Postgraduate School, Monterey, California

Search for other papers by Russell L. Elsberry in
Current site
Google Scholar
PubMed
Close
,
Tara D. B. Lambert Department of Meteorology, Naval Postgraduate School, Monterey, California

Search for other papers by Tara D. B. Lambert in
Current site
Google Scholar
PubMed
Close
, and
Mark A. Boothe Department of Meteorology, Naval Postgraduate School, Monterey, California

Search for other papers by Mark A. Boothe in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

Five statistical and dynamical tropical cyclone intensity guidance techniques available at the National Hurricane Center (NHC) during the 2003 and 2004 Atlantic and eastern North Pacific seasons were evaluated within three intensity phases: (I) formation; (II) early intensification, with a subcategory (IIa) of a decay and reintensification cycle; and (III) decay. In phase I in the Atlantic, the various techniques tended to predict that a tropical storm would form from six tropical depressions that did not develop further, and thus the tendency was for false alarms in these cases. For the other 24 depressions that did become tropical storms, the statistical–dynamical techniques, statistical hurricane prediction scheme (SHIPS) and decay SHIPS (DSHIPS), have some skill relative to the 5-day statistical hurricane intensity forecast climatology and persistence technique, but they also tend to intensify all depressions and thus are prone to false alarms. In phase II, the statistical–dynamical models SHIPS and DSHIPS do not predict the rapid intensification cases (≥30 kt in 24 h) 48 h in advance. Although the dynamical Geophysical Fluid Dynamics Interpolated model does predict rapid intensification, many of these cases are at the incorrect times with many false alarms. The best performances in forecasting at least 24 h in advance the 21 decay and reintensification cycles in the Atlantic were the three forecasts by the dynamical Geophysical Fluid Dynamics Model-Navy (interpolated) model. Whereas DSHIPS was the best technique in the Atlantic during the decay phase III, none of the techniques excelled in the eastern North Pacific. All techniques tend to decay the tropical cyclones in both basins too slowly, except that DSHIPS performed well (12 of 18) during rapid decay events in the Atlantic. This evaluation indicates where NHC forecasters have deficient guidance and thus where research is necessary for improving intensity forecasts.

Corresponding author address: R. L. Elsberry, Dept. of Meteorology, Naval Postgraduate School, Monterey, CA 93943. Email: elsberry@nps.edu

Abstract

Five statistical and dynamical tropical cyclone intensity guidance techniques available at the National Hurricane Center (NHC) during the 2003 and 2004 Atlantic and eastern North Pacific seasons were evaluated within three intensity phases: (I) formation; (II) early intensification, with a subcategory (IIa) of a decay and reintensification cycle; and (III) decay. In phase I in the Atlantic, the various techniques tended to predict that a tropical storm would form from six tropical depressions that did not develop further, and thus the tendency was for false alarms in these cases. For the other 24 depressions that did become tropical storms, the statistical–dynamical techniques, statistical hurricane prediction scheme (SHIPS) and decay SHIPS (DSHIPS), have some skill relative to the 5-day statistical hurricane intensity forecast climatology and persistence technique, but they also tend to intensify all depressions and thus are prone to false alarms. In phase II, the statistical–dynamical models SHIPS and DSHIPS do not predict the rapid intensification cases (≥30 kt in 24 h) 48 h in advance. Although the dynamical Geophysical Fluid Dynamics Interpolated model does predict rapid intensification, many of these cases are at the incorrect times with many false alarms. The best performances in forecasting at least 24 h in advance the 21 decay and reintensification cycles in the Atlantic were the three forecasts by the dynamical Geophysical Fluid Dynamics Model-Navy (interpolated) model. Whereas DSHIPS was the best technique in the Atlantic during the decay phase III, none of the techniques excelled in the eastern North Pacific. All techniques tend to decay the tropical cyclones in both basins too slowly, except that DSHIPS performed well (12 of 18) during rapid decay events in the Atlantic. This evaluation indicates where NHC forecasters have deficient guidance and thus where research is necessary for improving intensity forecasts.

Corresponding author address: R. L. Elsberry, Dept. of Meteorology, Naval Postgraduate School, Monterey, CA 93943. Email: elsberry@nps.edu

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bender, M. A., Ginis I. , Marchok T. P. , Pan H. L. , Thomas B. , and Tuleya R. E. , cited. 2005: A summary of upgrades to the operational GFDL hurricane model for 2003. [Available online at http://ams.confex.com/ams/pdfpapers/75131.pdf.].

  • Blackerby, J. S., 2005: The accuracy of western North Pacific tropical cyclone intensity guidance. M.S. thesis, Dept. of Meteorology, Naval Postgraduate School, 127 pp. [Available at online http://theses.nps.navy.mil/05Mar_Blackerby.pdf.].

  • Carr L. E. III, , Elsberry R. L. , and Peak J. E. , 2001: Beta test of the Systematic Approach expert system prototype as a tropical cyclone track forecasting aid. Wea. Forecasting, 16 , 355368.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeMaria, M., Zehr R. M. , Kossin J. P. , and Knaff J. A. , 2002: The use of GOES imagery in statistical hurricane intensity prediction. Preprints, 25th Conf. on Hurricanes and Tropical Meteorology, San Diego, CA, Amer. Meteor. Soc., 120–121.

  • DeMaria, M. R., 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 , 531543.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Elsberry, R. L., and Carr L. E. III, 2000: Consensus of dynamical tropical cyclone track forecasts. Mon. Wea. Rev., 128 , 41314138.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Elsberry, R. L., Fraim T. S. , and Trapnell R. N. Jr., 1976: A mixed layer model of the oceanic thermal response to hurricanes. J. Geophys. Res., 81 , 11531162.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., and Rappaport E. , 2000: Forecast skill of a simplified hurricane intensity prediction model. Preprints, 24th Conf. on Hurricanes and Tropical Meteorology, Fort Lauderdale, FL, Amer. Meteor. Soc., CD-ROM, 6A.5.

  • Franklin, J. L., 2005: 2004 National Hurricane Center verification report. Preprints, 59th Interdepartmental Hurricane Conf., Miami, FL, Office Federal Coordinator Meteorology. [Available online at http://www.ofcm.gov/ihc05/Presentations/01%20session1/s1-03franklin.ppt.].

  • Goerss, J., 2000: Tropical cyclone track forecasts using an ensemble of dynamical models. Mon. Wea. Rev., 128 , 11871193.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gross, J. M., 2004: North Atlantic and East Pacific track and intensity verification for 2003. Preprints, 58th Interdepartmental Hurricane Conf., Charleston, SC, Office Federal Coordinator Meteorology. [Available online at http://www.ofcm.gov/ihc04/presentations/b_session1/03_jgross.ppt.].

  • Kaplan, J., and DeMaria M. , 2003: Large-scale characteristics of rapidly intensifying tropical cyclones in the North Atlantic basin. Wea. Forecasting, 18 , 10931108.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., DeMaria M. , Sampson C. R. , and Gross J. M. , 2003: Statistical 5-day tropical cyclone intensity forecasts derived from climatology and persistence. Wea. Forecasting, 18 , 10931108.

    • Search Google Scholar
    • Export Citation
  • Lambert, T. D. B., 2005: Accuracy of Atlantic and eastern North Pacific tropical cyclone intensity guidance. M.S. thesis, Dept. of Meteorology, Naval Postgraduate School, 119 pp. [Available online at http://theses.nps.navy.mil/05Sep_Lambert.pdf.].

  • Rennick, M. A., 1999: Performance of the navy’s tropical cyclone prediction model in the western North Pacific basin during 1996. Wea. Forecasting, 14 , 297305.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sampson, C. R., and Schrader A. J. , 2000: The Automated Tropical Cyclone Forecasting System (version 3.2). Bull. Amer. Meteor. Soc., 81 , 12311240.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Willoughby, H. E., Clos J. A. , and Shoreibah M. G. , 1982: Concentric eyewalls, secondary wind maxima, and the evolution of the hurricane vortex. J. Atmos. Sci., 39 , 395411.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1468 456 157
PDF Downloads 556 106 4