A Deterministic Rapid Intensification Aid

Charles R. Sampson Naval Research Laboratory, Monterey, California

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John Kaplan NOAA/AOML/Hurricane Research Division, Miami, Florida

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John A. Knaff NOAA/NESDIS, Fort Collins, Colorado

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Mark DeMaria NOAA/NESDIS, Fort Collins, Colorado

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Chris A. Sisko National Hurricane Center, Miami, Florida

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Abstract

Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)−1; or 12.9, 15.4, and 18.0 m s−1 (24 h)−1] for the 24-h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50% probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40% threshold for producing the RI aid initially. The 40% threshold is available for approximately 8% of all verifying forecasts, produces approximately 4% reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%–20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill).

Corresponding author address: Charles R. Sampson, NRL, 7 Grace Hopper Ave., Stop 2, Monterey, CA 93943-5502. E-mail: sampson@nrlmry.navy.mil

Abstract

Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)−1; or 12.9, 15.4, and 18.0 m s−1 (24 h)−1] for the 24-h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50% probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40% threshold for producing the RI aid initially. The 40% threshold is available for approximately 8% of all verifying forecasts, produces approximately 4% reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%–20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill).

Corresponding author address: Charles R. Sampson, NRL, 7 Grace Hopper Ave., Stop 2, Monterey, CA 93943-5502. E-mail: sampson@nrlmry.navy.mil
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  • Bender, M. A., Ginis I. , Tuleya R. , Thomas B. , and Marchok T. , 2007: The operational GFDL coupled hurricane–ocean prediction system and a summary of its performance. Mon. Wea. Rev., 135, 39653989.

    • Search Google Scholar
    • Export Citation
  • Bernardet, L., and Coeditors, cited 2010: Hurricane Weather Research and Forecasting (HWRF) Model scientific documentation. [Available online at http://www.dtcenter.org/HurrWRF/users/docs/scientific_documents/HWRF_final_2-2_cm.pdf.]

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., 2009: A simplified dynamical system for tropical cyclone intensity prediction. Mon. Wea. Rev., 137, 6882.

  • DeMaria, M., Mainelli M. , Shay L. K. , Knaff J. A. , and Kaplan J. , 2005: Further improvement to the Statistical Hurricane Intensity Prediction Scheme (SHIPS). Wea. Forecasting, 20, 531543.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., Knaff J. A. , and Kaplan J. , 2006: On the decay of tropical cyclone winds crossing narrow landmasses. J. Appl. Meteor. Climatol., 45, 491499.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., Knaff J. A. , and Sampson C. R. , 2007: Evaluation of long-term trends in tropical cyclone intensity forecasts. Meteor. Atmos. Phys., 97, 1928.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K., Desautels C. , Holloway C. , and Korty R. , 2004: Environmental control of tropical cyclone intensity. J. Atmos. Sci., 61, 843858.

    • Search Google Scholar
    • Export Citation
  • Hogan, T. F., and Rosmond T. E. , 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
  • Kaplan, J., and DeMaria M. , 1995: A simple empirical model for predicting the decay of tropical cyclone winds after landfall. J. Appl. Meteor., 34, 24992512.

    • Search Google Scholar
    • Export Citation
  • Kaplan, J., and DeMaria M. , 2001: A note on the decay of tropical cyclone winds after landfall in the New England area. J. Appl. Meteor., 40, 280286.

    • Search Google Scholar
    • Export Citation
  • Kaplan, J., DeMaria M. , and Knaff J. A. , 2010: A revised tropical cyclone rapid intensification index for the Atlantic and eastern North Pacific basins. Wea. Forecasting, 25, 220241.

    • 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, 8092.

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., Guard C. , Kossin J. , Marchok T. , Sampson B. , Smith T. , and Surgi N. , 2006: Operational guidance and skill in forecasting structure change. Proc. Sixth Int. Workshop on Tropical Cyclones, San Jose, Costa Rica. WMO, 1.5. [Available online at http://severe.worldweather.org/iwtc/.]

    • Search Google Scholar
    • Export Citation
  • Rennick, M. A., 1999: Performance of the navy’s tropical cyclone prediction model in the western North Pacific basin during 1996. Wea. Forecasting, 14, 314.

    • Search Google Scholar
    • Export Citation
  • Reynolds, C. A., Doyle J. D. , Hodur R. M. , and Jin H. , 2010: Naval Research Laboratory multiscale targeting guidance for T-PARC and TCS-08. Wea. Forecasting, 25, 526544.

    • 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.

    • Search Google Scholar
    • Export Citation
  • Sampson, C. R., Goerss J. S. , and Weber H. C. , 2006: Operational performance of a new barotropic model (WBAR) in the western North Pacific basin. Wea. Forecasting, 21, 656662.

    • Search Google Scholar
    • Export Citation
  • Sampson, C. R., Franklin J. L. , Knaff J. A. , and DeMaria M. , 2008: Experiments with a simple tropical cyclone intensity consensus. Wea. Forecasting, 23, 304312.

    • Search Google Scholar
    • Export Citation
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