• Alcala, C. M., and Dessler A. E. , 2002: Observations of deep convection in the tropics using the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar. J. Geophys. Res., 107, 4792, doi:10.1029/2002JD002457.

    • Search Google Scholar
    • Export Citation
  • Bosart, L. F., Velden C. S. , Bracken W. E. , Molinari J. , and Black P. G. , 2000: Environmental influences on the rapid intensification of Hurricane Opal (1995) over the Gulf of Mexico. Mon. Wea. Rev., 128, 322352, doi:10.1175/1520-0493(2000)128<0322:EIOTRI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chan, J. C. L., Duan Y. H. , and Shay L. K. , 2001: Tropical cyclone intensity change from a simple ocean–atmosphere coupled model. J. Atmos. Sci., 58, 154172, doi:10.1175/1520-0469(2001)058<0154:TCICFA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chen, H., and Zhang D.-L. , 2013: On the rapid intensification of Hurricane Wilma (2005). Part II: Convective burst and the upper-level warm core. J. Atmos. Sci., 70, 146162, doi:10.1175/JAS-D-12-062.1.

    • Search Google Scholar
    • Export Citation
  • Cione, J. J., Kaplan J. , Gentemann C. , and DeMaria M. , 2010: Developing an inner-core SST cooling algorithm for use in SHIPS. National Hurricane Center. [Available online at http://www.nhc.noaa.gov/jht/03-05_proj.shtml.]

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., Mainelli M. , Shay L. K. , Knaff J. A. , and Kaplan J. , 2005: Futher improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS). Wea. Forecasting, 20, 531543, doi:10.1175/WAF862.1.

    • Search Google Scholar
    • Export Citation
  • Dowdy, S., and Wearden S. , 1991: Statistics for Research. 2nd ed. Wiley-Interscience, 555 pp.

  • Dvorak, V., 1995: Tropical clouds and cloud systems observed in satellite imagery: Tropical cyclones. Workbook Vol. 2, 359 pp. [Available from NOAA/NESDIS, 5200 Auth Rd., Washington, DC 20333.]

  • Fang, J., and Zhang F. , 2010: Initial development and genesis of Hurricane Dolly (2008). J. Atmos. Sci., 67, 655672, doi:10.1175/2009JAS3115.1.

    • Search Google Scholar
    • Export Citation
  • Frank, W. M., and Ritchie E. A. , 2001: Effects of vertical wind shear on the intensity and structure of numerically simulated hurricanes. Mon. Wea. Rev., 129, 22492269, doi:10.1175/1520-0493(2001)129<2249:EOVWSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gallina, G. M., and Velden C. S. , 2002: Environmental vertical wind shear and tropical cyclone intensity change utilizing enhanced satellite derived wind information. Preprints, 25th Conf. on Hurricanes and Tropical Meteorology, San Diego, CA, Amer. Meteor. Soc., 3C.5. [Available online at https://ams.confex.com/ams/pdfpapers/35650.pdf.]

  • Gettelman, A., Hoor P. , Pan L. L. , Randel W. J. , Hegglin M. I. , and Birner T. , 2011: The extratropical upper troposphere and lower stratosphere. Rev. Geophys., 49, RG3003, doi:10.1029/2011RG000355.

    • Search Google Scholar
    • Export Citation
  • Gray, W. M., 1968: Global view of the origin of tropical disturbances and storms. Mon. Wea. Rev., 96, 669700, doi:10.1175/1520-0493(1968)096<0669:GVOTOO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Guimond, S. R., Heymsfield G. M. , and Turk F. J. , 2010: Multiscale observations of Hurricane Dennis 2005: The effects of hot towers on rapid intensification. J. Atmos. Sci., 67, 633654, doi:10.1175/2009JAS3119.1.

    • Search Google Scholar
    • Export Citation
  • Hanley, D., Molinari J. , and Keyser D. , 2001: A composite study of the interactions between tropical cyclones and upper-tropospheric troughs. Mon. Wea. Rev., 129, 25702584, doi:10.1175/1520-0493(2001)129<2570:ACSOTI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hence, D. A., and Houze R. A. Jr., 2011: Vertical structure of hurricane eyewalls as seen by the TRMM Precipitation Radar. J. Atmos. Sci., 68, 16371652, doi:10.1175/2011JAS3578.1.

    • Search Google Scholar
    • Export Citation
  • Hendricks, E. A., 2012: Internal dynamical control on tropical cyclone intensity variability. Trop. Cyclone Res. Rev., 1, 97105, doi:10.6057/2012TCRR01.11.

    • Search Google Scholar
    • Export Citation
  • Hendricks, E. A., Montgomery M. T. , and Davis C. A. , 2004: On the role of “vortical” hot towers in formation of Tropical Cyclone Diana (1984). J. Atmos. Sci., 61, 12091232, doi:10.1175/1520-0469(2004)061<1209:TROVHT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hendricks, E. A., Peng M. S. , Fu B. , and Li T. , 2010: Quantifying environmental control on tropical cyclone intensity change. Mon. Wea. Rev., 138, 32433271, doi:10.1175/2010MWR3185.1.

    • Search Google Scholar
    • Export Citation
  • Hendricks, E. A., McNoldy B. D. , and Schubert W. H. , 2012: Observed inner-core structural variability in Hurricane Dolly (2008). Mon. Wea. Rev., 140, 40664077, doi:10.1175/MWR-D-12-00018.1.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, G. M., Halverson J. B. , Simpson J. , Tian L. , and Bui T. P. , 2001: ER-2 Doppler radar investigation of the eyewall of Hurricane Bonnie during the Convection and Moisture Experiment-3. J. Appl. Meteor., 40, 13101330, doi:10.1175/1520-0450(2001)040<1310:EDRIOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hou, A. Y., and Coauthors, 2014: The Global Precipitation Measurement Mission. Bull. Amer. Meteor. Soc., 95, 701722, doi:10.1175/BAMS-D-13-00164.1.

    • Search Google Scholar
    • Export Citation
  • Houze, R. A., Jr., Lee W.-C. , and Bell M. M. , 2009: Convective contribution to the genesis of Hurricane Ophelia (2005). Mon. Wea. Rev., 137, 27782800, doi:10.1175/2009MWR2727.1.

    • Search Google Scholar
    • Export Citation
  • Jiang, H., 2012: The relationship between tropical cyclone intensity change and the strength of inner-core convection. Mon. Wea. Rev., 140, 11641176, doi:10.1175/MWR-D-11-00134.1.

    • Search Google Scholar
    • Export Citation
  • Jiang, H., and Ramirez E. M. , 2013: Necessary conditions for tropical cyclone rapid intensification as derived from 11 years of TRMM data. J. Climate, 26, 64596470, doi:10.1175/JCLI-D-12-00432.1.

    • Search Google Scholar
    • Export Citation
  • Jiang, H., Liu C. , and Zipser E. J. , 2011: A TRMM-based tropical cyclone cloud and precipitation feature database. J. Appl. Meteor. Climatol., 50, 12551274, doi:10.1175/2011JAMC2662.1.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kaplan, J., and DeMaria M. , 2003: Large-scale characteristics of rapidly intensifying tropical cyclones in the North Atlantic basin. Wea. Forecasting, 18, 10931108, doi:10.1175/1520-0434(2003)018<1093:LCORIT>2.0.CO;2.

    • 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, doi:10.1175/2009WAF2222280.1.

    • Search Google Scholar
    • Export Citation
  • Kelley, O. A., and Halverson J. B. , 2011: How much tropical cyclone intensification can result from the energy released inside of a convective burst? J. Geophys. Res., 116, D20118, doi:10.1029/2011JD015954.

    • Search Google Scholar
    • Export Citation
  • Kelley, O. A., Stout J. , and Halverson J. B. , 2004: Tall precipitation cells in tropical cyclone eyewalls are associated with tropical cyclone intensification. Geophys. Res. Lett., 31, L24112, doi:10.1029/2004GL021616.

    • 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). Bull. Amer. Meteor. Soc., 91, 363376, doi:10.1175/2009BAMS2755.1.

    • Search Google Scholar
    • Export Citation
  • Liu, C., Zipser E. J. , Cecil D. J. , Nesbitt S. W. , and Sherwood S. , 2008: A cloud and precipitation feature database from 9 years of TRMM observations. J. Appl. Meteor. Climatol., 47, 27122728, doi:10.1175/2008JAMC1890.1.

    • Search Google Scholar
    • Export Citation
  • Luo, Z., Liu G. Y. , and Stephens G. L. , 2008: CloudSat adding new insight into tropical penetrating convection. Geophys. Res. Lett., 35, L19819, doi:10.1029/2008GL035330.

    • Search Google Scholar
    • Export Citation
  • Mainelli, M., DeMaria M. , Shay L. K. , and Goni G. , 2008: Application of oceanic heat content estimation to operational forecasting of recent Atlantic category 5 hurricanes. Wea. Forecasting, 23, 316, doi:10.1175/2007WAF2006111.1.

    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M., Jewett B. F. , Gilmore M. S. , Nesbitt S. W. , and Hsieh T.-L. , 2012: Vertical velocity and microphysical distributions related to rapid intensification in a simulation of Hurricane Dennis (2005). J. Atmos. Sci., 69, 35153534, doi:10.1175/JAS-D-12-016.1.

    • Search Google Scholar
    • Export Citation
  • Molinari, J., and Vollaro D. , 1989: External influences on hurricane intensity. Part I: Outflow layer eddy angular momentum fluxes. J. Atmos. Sci., 46, 10931105, doi:10.1175/1520-0469(1989)046<1093:EIOHIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Molinari, J., Skubis S. , and Vollaro D. , 1995: External influences on hurricane intensity. Part III: Potential vorticity structure. J. Atmos. Sci., 52, 35933606, doi:10.1175/1520-0469(1995)052<3593:EIOHIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Monette, S. A., Velden C. S. , Griffin K. S. , and Rozoff C. M. , 2012: Examining trends in satellite-detected tropical overshooting tops as a potential predictor of tropical cyclone rapid intensification. J. Appl. Meteor. Climatol., 51, 19171930, doi:10.1175/JAMC-D-11-0230.1.

    • Search Google Scholar
    • Export Citation
  • Montgomery, M. T., Nicholls M. E. , Cram T. A. , and Saunders A. B. , 2006: A vortical hot tower route to tropical cyclogenesis. J. Atmos. Sci., 63, 355386, doi:10.1175/JAS3604.1.

    • Search Google Scholar
    • Export Citation
  • Nguyen, L. T., and Molinari J. , 2012: Rapid intensification of a sheared, fast-moving hurricane over the Gulf Stream. Mon. Wea. Rev., 140, 33613378, doi:10.1175/MWR-D-11-00293.1.

    • Search Google Scholar
    • Export Citation
  • Nguyen, M. C., Reeder M. J. , Davidson N. E. , Smith R. K. , and Montgomery M. T. , 2011: Inner-core vacillation cycles during the intensification of Hurricane Katrina. Quart. J. Roy. Meteor. Soc., 137, 829844, doi:10.1002/qj.823.

    • Search Google Scholar
    • Export Citation
  • NHC, 2008: Joint Hurricane Testbed (JHT) opportunities for transfer of research and technology into tropical cyclone analysis and forecast operations. [Available online at http://www.nhc.noaa.gov/jht/index.shtml.]

  • Nolan, D. S., and Grasso L. D. , 2003: Three-dimensional perturbations to balanced, hurricane-like vortices. Part II: Symmetric response and nonlinear simulations. J. Atmos. Sci., 60, 27172745, doi:10.1175/1520-0469(2003)060<2717:NTPTBH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rappaport, E. N., and Coauthors, 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting, 24, 395419, doi:10.1175/2008WAF2222128.1.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., and Smith T. M. , 1993: An improved real-time global sea surface temperature analysis. J. Climate, 6, 114119, doi:10.1175/1520-0442(1993)006<0114:AIRTGS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Riehl, H., and Malkus J. , 1958: On the heat balance in the equatorial trough zone. Geophysica, 6, 503538.

  • Rogers, R., 2010: Convective-scale structure and evolution during a high-resolution simulation of tropical cyclone rapid intensification. J. Atmos. Sci., 67, 4470, doi:10.1175/2009JAS3122.1.

    • Search Google Scholar
    • Export Citation
  • Schreck, C. J., III, Knapp K. R. , and Kossin J. P. , 2014: The impact of best track discrepancies on global tropical cyclone climatologies using IBTrACS. Mon. Wea. Rev., 142, 38813899, doi:10.1175/MWR-D-14-00021.1.

    • Search Google Scholar
    • Export Citation
  • Schubert, W. H., Montgomery M. T. , Taft R. K. , Guinn T. A. , Fulton S. R. , Kossin J. P. , and Edwards J. P. , 1999: Polygonal eyewalls, asymmetric eye contraction, and potential vorticity mixing in hurricanes. J. Atmos. Sci., 56, 11971223, doi:10.1175/1520-0469(1999)056<1197:PEAECA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schubert, W. H., Rozoff C. M. , Vigh J. L. , McNoldy B. D. , and Kossin J. P. , 2007: On the distribution of subsidence in the hurricane eye. Quart. J. Roy. Meteor. Soc., 133, 595605, doi:10.1002/qj.49.

    • Search Google Scholar
    • Export Citation
  • Shay, L. K., and Brewster J. K. , 2010: Oceanic heat content variability in the eastern Pacific Ocean for hurricane intensity forecasting. Mon. Wea. Rev., 138, 21102131, doi:10.1175/2010MWR3189.1.

    • Search Google Scholar
    • Export Citation
  • Shay, L. K., Goni G. J. , and Black P. G. , 2000: Effects of a warm oceanic feature on Hurricane Opal. Mon. Wea. Rev., 128, 13661383, doi:10.1175/1520-0493(2000)128<1366:EOAWOF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Shu, S., Ming J. , and Chi P. , 2012: Large-scale characteristics and probability of rapidly intensifying tropical cyclones in the western North Pacific basin. Wea. Forecasting, 27, 411423, doi:10.1175/WAF-D-11-00042.1.

    • Search Google Scholar
    • Export Citation
  • Sitkowski, M., Kossin J. P. , and Rozoff C. M. , 2011: Intensity and structure changes during hurricane eyewall replacement cycles. Mon. Wea. Rev., 139, 38293847, doi:10.1175/MWR-D-11-00034.1.

    • Search Google Scholar
    • Export Citation
  • Tao, C., and Jiang H. , 2013: Global distribution of hot towers in tropical cyclones based on 11-yr TRMM data. J. Climate, 26, 13711386, doi:10.1175/JCLI-D-12-00291.1.

    • Search Google Scholar
    • Export Citation
  • Wada, A., and Usui N. , 2007: Importance of tropical cyclone heat potential for tropical cyclone intensity and intensification in the western North Pacific. J. Oceanogr., 63, 427447, doi:10.1007/s10872-007-0039-0.

    • Search Google Scholar
    • Export Citation
  • Wang, H., and Wang Y. , 2014: A numerical study of Typhoon Megi (2010). Part I: Rapid intensification. Mon. Wea. Rev., 142, 2948, doi:10.1175/MWR-D-13-00070.1.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. 2nd ed. Academic Press, 627 pp.

  • Willoughby, H. E., 1998: Tropical cyclone eye thermodynamics. Mon. Wea. Rev., 126, 30533067, doi:10.1175/1520-0493(1998)126<3053:TCET>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Willoughby, H. E., Clos J. A. , and Shoreibah M. G. , 1982: Concentric eye walls, secondary wind maxima, and the evolution of the hurricane vortex. J. Atmos. Sci., 39, 395411, doi:10.1175/1520-0469(1982)039<0395:CEWSWM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wong, M. L. M., and Chan J. C. L. , 2004: Tropical cyclone intensity in vertical wind shear. J. Atmos. Sci., 61, 18591876, doi:10.1175/1520-0469(2004)061<1859:TCIIVW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, D.-L., and Chen H. , 2012: Importance of the upper-level warm core in the rapid intensification of a tropical cyclone. Geophys. Res. Lett., 39, L02806, doi:10.1029/2011GL050578.

    • Search Google Scholar
    • Export Citation
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Reassessing the Use of Inner-Core Hot Towers to Predict Tropical Cyclone Rapid Intensification

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  • 1 School of Atmospheric Sciences, and Key Laboratory of Mesoscale Severe Weather of Ministry of Education, Nanjing University, Nanjing, China
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Abstract

The hot tower (HT) in the inner core plays an important role in tropical cyclone (TC) rapid intensification (RI). With the help of Tropical Rainfall Measurement Mission (TRMM) data and the Statistical Hurricane Intensity Prediction Scheme dataset, the potential of HTs in operational RI prediction is reassessed in this study. The stand-alone HT-based RI prediction scheme showed little skill in the northern Atlantic (NA) and eastern and central Pacific (ECP), but yielded skill scores of >0.3 in the southern Indian Ocean (SI) and western North Pacific (WNP) basins. The inaccurate predictions are due to four scenarios: 1) RI events may have already begun prior to the TRMM overpass. 2) RI events are driven by non-HT factors. 3) The HT has already dissipated or has not occurred at the TRMM overpass time. 4) Large false alarms result from the unfavorable environment. When the HT was used in conjunction with the TC’s previous 12-h intensity change, the potential intensity, the percentage area from 50 to 200 km of cloud-top brightness temperatures lower than −10°C, and the 850–200-hPa vertical shear magnitude with the vortex removed, the predictive skill score in the SI was 0.56. This score was comparable to that of the RI index scheme, which is considered the most advanced RI prediction method. When the HT information was combined with the aforementioned four environmental factors in the NA, ECP, South Pacific, and WNP, the skill scores were 0.23, 0.32, 0.42, and 0.42, respectively.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/WAF-D-15-0024.s1.

Corresponding author address: Yuan Wang, School of Atmospheric Sciences, and Key Laboratory of Mesoscale Severe Weather of Ministry of Education, Nanjing University, Nanjing 210023, China. E-mail: yuanasm@nju.edu.cn

Abstract

The hot tower (HT) in the inner core plays an important role in tropical cyclone (TC) rapid intensification (RI). With the help of Tropical Rainfall Measurement Mission (TRMM) data and the Statistical Hurricane Intensity Prediction Scheme dataset, the potential of HTs in operational RI prediction is reassessed in this study. The stand-alone HT-based RI prediction scheme showed little skill in the northern Atlantic (NA) and eastern and central Pacific (ECP), but yielded skill scores of >0.3 in the southern Indian Ocean (SI) and western North Pacific (WNP) basins. The inaccurate predictions are due to four scenarios: 1) RI events may have already begun prior to the TRMM overpass. 2) RI events are driven by non-HT factors. 3) The HT has already dissipated or has not occurred at the TRMM overpass time. 4) Large false alarms result from the unfavorable environment. When the HT was used in conjunction with the TC’s previous 12-h intensity change, the potential intensity, the percentage area from 50 to 200 km of cloud-top brightness temperatures lower than −10°C, and the 850–200-hPa vertical shear magnitude with the vortex removed, the predictive skill score in the SI was 0.56. This score was comparable to that of the RI index scheme, which is considered the most advanced RI prediction method. When the HT information was combined with the aforementioned four environmental factors in the NA, ECP, South Pacific, and WNP, the skill scores were 0.23, 0.32, 0.42, and 0.42, respectively.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/WAF-D-15-0024.s1.

Corresponding author address: Yuan Wang, School of Atmospheric Sciences, and Key Laboratory of Mesoscale Severe Weather of Ministry of Education, Nanjing University, Nanjing 210023, China. E-mail: yuanasm@nju.edu.cn

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