Consensus on Climate Trends in Western North Pacific Tropical Cyclones

Nam-Young Kang The Florida State University, Tallahassee, Florida

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James B. Elsner The Florida State University, Tallahassee, Florida

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Abstract

Research on trends in western North Pacific tropical cyclone (TC) activity is limited by problems associated with different wind speed conversions used by the various meteorological agencies. This paper uses a quantile method to effectively overcome this conversion problem. Following the assumption that the intensity ranks of TCs are the same among agencies, quantiles at the same probability level in different data sources are regarded as having the same wind speed level. Tropical cyclone data from the Joint Typhoon Warning Center (JTWC) and Japan Meteorological Agency (JMA) are chosen for research and comparison. Trends are diagnosed for the upper 45% of the strongest TCs annually. The 27-yr period beginning with 1984, when the JMA began using the technique, is determined to be the most reliable for achieving consensus among the two agencies regarding these trends. The start year is a compromise between including as many years in the data as possible, but not so many that the period includes observations that result in inconsistent trend estimates. The consensus of TC trends between the two agencies over the period is interpreted as fewer but stronger events since 1984, even with the lower power dissipation index (PDI) in the western North Pacific in recent years.

Corresponding author address: Nam-Young Kang, Bellamy Building 320, The Florida State University, Tallahassee, FL 32306. E-mail: nkang@fsu.edu

Abstract

Research on trends in western North Pacific tropical cyclone (TC) activity is limited by problems associated with different wind speed conversions used by the various meteorological agencies. This paper uses a quantile method to effectively overcome this conversion problem. Following the assumption that the intensity ranks of TCs are the same among agencies, quantiles at the same probability level in different data sources are regarded as having the same wind speed level. Tropical cyclone data from the Joint Typhoon Warning Center (JTWC) and Japan Meteorological Agency (JMA) are chosen for research and comparison. Trends are diagnosed for the upper 45% of the strongest TCs annually. The 27-yr period beginning with 1984, when the JMA began using the technique, is determined to be the most reliable for achieving consensus among the two agencies regarding these trends. The start year is a compromise between including as many years in the data as possible, but not so many that the period includes observations that result in inconsistent trend estimates. The consensus of TC trends between the two agencies over the period is interpreted as fewer but stronger events since 1984, even with the lower power dissipation index (PDI) in the western North Pacific in recent years.

Corresponding author address: Nam-Young Kang, Bellamy Building 320, The Florida State University, Tallahassee, FL 32306. E-mail: nkang@fsu.edu
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  • Atkinson, G. D., 1974: Investigation of gust factors in tropical cyclones. Joint Typhoon Warning Center Tech. Note JTWC 74–1, 9 pp.

  • Atkinson, G. D., and C. R. Holliday, 1977: Tropical cyclone minimum sea level pressure/maximum sustained wind relationship for the western North Pacific. Mon. Wea. Rev., 105, 421427.

    • Search Google Scholar
    • Export Citation
  • Chan, J. C. L., 2005: Interannual and interdecadal variations of tropical cyclone activity over the western North Pacific. Meteor. Atmos. Phys., 89, 143152.

    • Search Google Scholar
    • Export Citation
  • Chu, J. H., C. R. Sampson, A. S. Levine, and E. Fukada, 2002: The Joint Typhoon Warning Center tropical cyclone best tracks, 1945–2000. Joint Typhoon Warning Center, 22 pp.

  • Dvorak, V. F., 1975: Tropical cyclone intensity analysis and forecasting from satellite imagery. Mon. Wea. Rev., 103, 420430.

  • Dvorak, V. F., 1982: Tropical cyclone intensity analysis and forecasting from satellite visible or enhanced infrared imagery. NOAA National Environmental Satellite Service, Applications Laboratory Training Notes, 42 pp.

  • Dvorak, V. F., 1984: Tropical cyclone intensity analysis using satellite data. NOAA Tech. Rep. 11, 45 pp.

  • Elsner, J. B., J. P. Kossin, and T. H. Jagger, 2008: The increasing intensity of the strongest tropical cyclones. Nature, 455, 9295, doi:10.1038/nature07234.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 2005: Increasing destructiveness of tropical cyclones over the past 30 years. Nature, 436, 686688.

  • Kamahori, H. N., N. Yamazaki, N. Mannoji, and K. Takahashi, 2006: Variability in intense tropical cyclone days in the western North Pacific. SOLA, 2, 104107.

    • Search Google Scholar
    • Export Citation
  • Kang, N.-Y., and J. B. Elsner, 2012: An empirical framework for tropical cyclone climatology. Climate Dyn., 39, 669680, doi:10.1007/s00382-011-1231-x.

    • Search Google Scholar
    • Export Citation
  • Knapp, K. R., and M. C. Kruk, 2010: Quantifying interagency differences in tropical cyclone best-track wind speed estimates. Mon. Wea. Rev., 138, 14591473.

    • Search Google Scholar
    • Export Citation
  • Koba, H., T. Hagiwara, S. Osano, and S. Akashi, 1991: Relationships between CI number and minimum sea level pressure/maximum wind speed of tropical cyclones. Geophys. Mag., 44, 1525.

    • Search Google Scholar
    • Export Citation
  • Levinson, D. H., H. J. Diamond, K. R. Knapp, M. C. Kruk, and E. J. Gibney, 2010: Toward a homogenous global tropical cyclone best-track dataset. Bull. Amer. Meteor. Soc., 91, 377380.

    • Search Google Scholar
    • Export Citation
  • Nakazawa, T., and S. Hoshino, 2009: Intercomparison of Dvorak parameters in the tropical cyclone datasets over the western North Pacific. SOLA, 5, 3336.

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

  • Simpson, R. H., 1974: The hurricane disaster potential scale. Weatherwise, 27, 169186.

  • Song, J. J., J. Wang, and L. Wu, 2010: Trend discrepancies among three best track data sets of western North Pacific tropical cyclones. J. Geophys. Res., 115, D12128, doi:10.1029/2009JD013058.

  • Velden, C., T. Olander, and R. Zehr, 1998: Development of an objective scheme to estimate tropical cyclone intensity from digital geostationary satellite imagery. Wea. Forecasting, 13, 172186.

    • Search Google Scholar
    • Export Citation
  • Velden, C., and Coauthors, 2006: The Dvorak tropical cyclone intensity estimation technique: A satellite-based method that has endured for over 30 years. Bull. Amer. Meteor. Soc., 87, 11951210.

    • Search Google Scholar
    • Export Citation
  • Webster, P. J., G. J. Holland, J. A. Curry, and H.-R. Chang, 2005: Changes in tropical cyclone number, duration, and intensity in a warming environment. Science, 309, 18441846, doi:10.1126/science.1116448.

    • Search Google Scholar
    • Export Citation
  • Wu, M. C., K. H. Yeung, and W. L. Chang, 2006: Trends in western North Pacific tropical cyclone intensity. Eos, Trans. Amer. Geophys. Union, 87, 537538, doi:10.1029/2006EO480001.

    • Search Google Scholar
    • Export Citation
  • Yeung, K. H., 2006: Issues related to global warming—Myths, realities and warnings. Hong Kong Observatory Reprint 647, 16 pp. [Available online at http://www.weather.gov.hk/publica/reprint/r647.pdf.]

  • Yu, H., C. Hu, and L. Jiang, 2007: Comparison of three tropical cyclone intensity datasets. Acta Meteor. Sin., 21, 121128.

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