Simple Diagnosis of Tropical Cyclone Structure via Pressure Gradients

John A. Knaff NOAA/NESDIS/Regional and Mesoscale Meteorology Branch, Fort Collins, Colorado

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Charles R. Sampson Naval Research Laboratory, Monterey, California

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Patrick J. Fitzpatrick Geosystems Research Institute, Mississippi State University, Stennis Space Center, Mississippi

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Yi Jin Naval Research Laboratory, Monterey, California

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Christopher M. Hill Geosystems Research Institute, Mississippi State University, Stennis Space Center, Mississippi

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Abstract

In 1980 the Holland tropical cyclone (TC) wind profile model was introduced. This simple model was originally intended to estimate the wind profile based on limited surface pressure information alone. For this reason and its relative simplicity, the model has been used in many practical applications. In this paper the potential of a simplified version of the Holland B parameter, which is related to the shape of the tangential wind profile, is explored as a powerful diagnostic tool for monitoring TC structure. The implementation examined is based on the limited information (maximum wind, central pressure, radius and pressure of the outer closed isobar, radii of operationally important wind radii, etc.) that is typically available in operational models and routine analyses of TC structure. This “simplified Holland B” parameter is shown to be sensitive to TC intensity, TC size, and the rate of radial decay of the tangential winds, but relatively insensitive to the radius of maximum winds. A climatology of the simplified Holland B parameter based on historical best-track data is also developed and presented, providing the expected natural ranges of variability. The relative simplicity, predictable variability, and desirable properties of the simplified Holland B parameter make it ideal for a variety of applications. Examples of how the simplified Holland B parameter can be used for improving forecaster guidance, developing TC structure tools, diagnosing TC model output, and understanding and comparing the climatological variations of TC structure are presented.

Corresponding author address: John Knaff, NOAA/NESDIS/RAMMB, Colorado State University, Campus Delivery 1375, Fort Collins, CO 80523-1375. E-mail: john.knaff@noaa.gov

Abstract

In 1980 the Holland tropical cyclone (TC) wind profile model was introduced. This simple model was originally intended to estimate the wind profile based on limited surface pressure information alone. For this reason and its relative simplicity, the model has been used in many practical applications. In this paper the potential of a simplified version of the Holland B parameter, which is related to the shape of the tangential wind profile, is explored as a powerful diagnostic tool for monitoring TC structure. The implementation examined is based on the limited information (maximum wind, central pressure, radius and pressure of the outer closed isobar, radii of operationally important wind radii, etc.) that is typically available in operational models and routine analyses of TC structure. This “simplified Holland B” parameter is shown to be sensitive to TC intensity, TC size, and the rate of radial decay of the tangential winds, but relatively insensitive to the radius of maximum winds. A climatology of the simplified Holland B parameter based on historical best-track data is also developed and presented, providing the expected natural ranges of variability. The relative simplicity, predictable variability, and desirable properties of the simplified Holland B parameter make it ideal for a variety of applications. Examples of how the simplified Holland B parameter can be used for improving forecaster guidance, developing TC structure tools, diagnosing TC model output, and understanding and comparing the climatological variations of TC structure are presented.

Corresponding author address: John Knaff, NOAA/NESDIS/RAMMB, Colorado State University, Campus Delivery 1375, Fort Collins, CO 80523-1375. E-mail: john.knaff@noaa.gov
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  • Bessho, K., DeMaria M. , and Knaff J. A. , 2006: Tropical cyclone wind retrievals from the Advanced Microwave Sounder Unit (AMSU): Application to surface wind analysis. J. Climate Appl. Meteor., 45, 399415.

    • Search Google Scholar
    • Export Citation
  • Blake, E. B., Gibney E. J. , Brown D. P. , Mainelli M. , Franklin J. L. , Kimberlain T. B. , and Hammer G. R. , 2009: Tropical Cyclones of the Eastern North Pacific Ocean, 1949-2006. Historical Climatology Series, Vol. 6-5, National Climatic Data Center, 166 pp. [Available on-line at http://ols.nndc.noaa.gov/plolstore/plsql/olstore.prodspecific?prodnum=C00755-PUB-A0001.]

    • Search Google Scholar
    • Export Citation
  • Courtney, J., and Knaff J. A. , 2009: Adapting the Knaff and Zehr wind–pressure relationship for operational use in tropical cyclone warning centres. Aust. Meteor. Oceanogr. J., 58, 167179.

    • Search Google Scholar
    • Export Citation
  • Dvorak, V. F., 1984: Tropical cyclone intensity analysis using satellite data. NOAA Tech. Rep. 11, 45 pp. [Available from NOAA/NESDIS, 5200 Auth Rd., Washington, DC 20333.]

    • Search Google Scholar
    • Export Citation
  • Gelsthorpe, R. V., Schied E. , and Wilson J. J. W. , 2000: ASCAT—MetOp’s advanced scatterometer. ESA Bull., 102, 1927.

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

    • Search Google Scholar
    • Export Citation
  • Graf, J. E., Tsi W.-Y. , and Jones L. , 1998: Overview of QuikSCAT mission—A quick deployment of a high resolution, wide swath scanning scatterometer for ocean wind measurement. Proc. IEEE Southeastcon ’98: Engineering for a New Era, Orlando, FL, IEEE, 314–317. [Available online at http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=673359.]

    • Search Google Scholar
    • Export Citation
  • Hess, S. L., 1959: Introduction to Theoretical Meteorology. Robert E. Krieger Publishing, 362 pp.

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

  • Holland, G. J., Belanger J. I. , and Fritz A. , 2010: A revised model for radial profiles of hurricane winds. Mon. Wea. Rev., 138, 43934401.

    • Search Google Scholar
    • Export Citation
  • Holmlund, K., Velden C. , and Rohn M. , 2001: Enhanced automated quality control applied to high-density satellite-derived winds. Mon. Wea. Rev., 129, 517529.

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., 2009: Revisiting the maximum intensity of recurving tropical cyclones. Int. J. Climatol., 29, 827837.

  • Knaff, J. A., and Zehr R. M. , 2007: Reexamination of tropical cyclone wind–pressure relationships. Wea. Forecasting, 22, 7188.

  • Knaff, J. A., and Harper B. A. , 2010: Tropical cyclone surface wind structure and wind–pressure relationships. Proc. Seventh Int. Workshop on Tropical Cyclones—VII, La Reunion, France, WMO, 35 pp. [Available online at http://www.cawcr.gov.au/projects/iwtc/documentation/KN1.pdf.]

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., Sampson C. R. , DeMaria M. , Marchok T. P. , Gross J. M. , and McAdie C. J. , 2007: Statistical tropical cyclone wind radii prediction using climatology and persistence. Wea. Forecasting, 22, 781791.

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., Brown D. P. , Courtney J. , Gallina G. M. , and Beven J. L. II, 2010: An evaluation of Dvorak technique-based tropical cyclone intensity estimates. Wea. Forecasting, 25, 13621379.

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., DeMaria M. , Molenar D. A. , Sampson C. R. , and Seybold M. G. , 2011: An automated, objective, multiple-satellite-platform tropical cyclone surface wind analysis. J. Appl. Meteor. Climatol., 50, 21492166.

    • Search Google Scholar
    • Export Citation
  • Knapp, K. R., Kruk M. C. , Levinson D. H. , Diamond H. J. , and Neumann C. J. , 2010: The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying tropical cyclone best-track data. Bull. Amer. Meteor. Soc., 91, 363376.

    • Search Google Scholar
    • Export Citation
  • Maclay, K. S., DeMaria M. , and Vonder Haar T. H. , 2008: Tropical cyclone inner-core kinetic energy evolution. Mon. Wea. Rev., 136, 48824898.

    • Search Google Scholar
    • Export Citation
  • Merrill, R. T., 1984: A comparison of large and small tropical cyclones. Mon. Wea. Rev., 112, 14081418.

  • Mueller, K. J., DeMaria M. , Knaff J. , Kossin J. P. , and Vonder Haar T. H. , 2006: Objective estimation of tropical cyclone wind structure from infrared satellite data. Wea. Forecasting, 21, 9901005.

    • Search Google Scholar
    • Export Citation
  • Neumann, C. J., 1993: Global overview. Global Guide to Tropical Cyclone Forecasting, G. J. Holland, Ed., WMO/TC-560, Rep. TCP-31, World Meteorological Organization, 1–43. [Available online at http://www.cawcr.gov.au/publications/BMRC_archive/tcguide/.]

    • Search Google Scholar
    • Export Citation
  • Powell, M. D., Houston S. H. , Amat L. R. , and Morisseau-Leroy N. , 1998: The HRD real-time hurricane wind analysis system. J. Wind Eng. Indust. Aerodyn., 77–78, 5364.

    • Search Google Scholar
    • Export Citation
  • Rappaport, E. N., and Coauthors, 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting, 24, 395419.

  • 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
  • Schwerdt, R. W., Ho F. P. , and Watkins R. R. , 1979: Meteorological criteria for standard project hurricane and probable maximum hurricane windfields, Gulf and East Coasts of the United States. NOAA Tech. Rep. NWS 23, 317 pp. [Available from National Hurricane Center Library, 11691 SW 117 St., Miami, FL 33165-2149.]

    • Search Google Scholar
    • Export Citation
  • Velden, C. S., Hayden C. M. , Nieman S. J. , Menzel W. P. , Wanzong S. , and Goerss J. S. , 1997: Upper-tropospheric winds derived from geostationary satellite water vapor observations. Bull. Amer. Meteor. Soc., 78, 173195.

    • Search Google Scholar
    • Export Citation
  • Vickery, P. J., and Wadhera D. , 2008: Statistical models of Holland pressure profile parameter and radius to maximum winds of hurricanes from flight-level pressure and H*Wind data. J. Appl. Meteor. Climatol., 47, 24972517.

    • Search Google Scholar
    • Export Citation
  • Willoughby, H. E., and Rahn M. E. , 2004: Parametric representation of the primary hurricane vortex. Part I: Observations and evaluation of the Holland (1980) model. Mon. Wea. Rev., 132, 30333048.

    • Search Google Scholar
    • Export Citation
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