• Chen, X., , Y. Wang, , and K. Zhao, 2015: Synoptic flow patterns and large-scale characteristics associated with rapidly intensifying tropical cyclones in the South China Sea. Mon. Wea. Rev., 143, 6487, doi:10.1175/MWR-D-13-00338.1.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., 2009: A simplified dynamical system for tropical cyclone intensity prediction. Mon. Wea. Rev., 137, 6882, doi:10.1175/2008MWR2513.1.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., , and J. Kaplan, 1994: Sea surface temperature and the maximum intensity of Atlantic tropical cyclones. J. Climate, 7, 13241334, doi:10.1175/1520-0442(1994)007<1324:SSTATM>2.0.CO;2.

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

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1986: An air–sea interaction theory of tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci., 43, 585604, doi:10.1175/1520-0469(1986)043<0585:AASITF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1988: The maximum intensity of hurricanes. J. Atmos. Sci., 45, 11431155, doi:10.1175/1520-0469(1988)045<1143:TMIOH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1991: The theory of hurricanes. Annu. Rev. Fluid Mech., 23, 179196, doi:10.1146/annurev.fl.23.010191.001143.

  • Emanuel, K. A., 1995: The behavior of a simple hurricane model using a convective scheme based on subcloud-layer entropy equilibrium. J. Atmos. Sci., 52, 39603968, doi:10.1175/1520-0469(1995)052<3960:TBOASH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1997: Some aspects of hurricane inner-core dynamics and energetics. J. Atmos. Sci., 54, 10141026, doi:10.1175/1520-0469(1997)054<1014:SAOHIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., , C. DesAutels, , C. Holloway, , and R. Korty, 2004: Environmental control of tropical cyclone intensity. J. Atmos. Sci., 61, 843858, doi:10.1175/1520-0469(2004)061<0843:ECOTCI>2.0.CO;2.

    • 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
  • Holland, G. J., 1997: The maximum potential intensity of tropical cyclones. J. Atmos. Sci., 54, 25192541, doi:10.1175/1520-0469(1997)054<2519:TMPIOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kaplan, J., , M. DeMaria, , and J. A. Knaff, 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
  • Kleinschmidt, E., Jr., 1951: Grundlagen einer Theorie der tropischen Zyklonen. Arch. Meteor. Geophys. Bioklimatol., 4A, 5372, doi:10.1007/BF02246793.

    • Search Google Scholar
    • Export Citation
  • Kurihara, Y., , M. A. Bender, , and R. J. Ross, 1993: An initialization scheme of hurricane models by vortex specification. Mon. Wea. Rev., 121, 20302045, doi:10.1175/1520-0493(1993)121<2030:AISOHM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Malkus, J. S., , and H. Riehl, 1960: On the dynamics and energy transformations in steady-state hurricane. Tellus, 12, 120, doi:10.1111/j.2153-3490.1960.tb01279.x.

    • Search Google Scholar
    • Export Citation
  • Merrill, R. T., 1988: Environmental influences on hurricane intensification. J. Atmos. Sci., 45, 16781687, doi:10.1175/1520-0469(1988)045<1678:EIOHI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Miller, B. I., 1958: On the maximum intensity of hurricanes. J. Meteor., 15, 184195, doi:10.1175/1520-0469(1958)015<0184:OTMIOH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Murakami, H., and et al. , 2015: Simulation and prediction of category 4 and 5 hurricanes in the high-resolution GFDL HiFLOR coupled climate model. J. Climate, 28, 90589079, doi:10.1175/JCLI-D-15-0216.1.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., , N. A. Rayner, , T. M. Smith, , D. C. Stokes, , and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 16091625, doi:10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., , T. M. Smith, , C. Liu, , D. B. Chelton, , K. S. Casey, , and M. G. Schlax, 2007: Daily high-resolution-blended analyses for sea surface temperature. J. Climate, 20, 54735496, doi:10.1175/2007JCLI1824.1.

    • Search Google Scholar
    • Export Citation
  • Stevenson, S. N., , K. L. Corbosiero, , and S. F. Abarca, 2016: Lightning in eastern North Pacific tropical cyclones: A comparison to the North Atlantic. Mon. Wea. Rev., 144, 225239, doi:10.1175/MWR-D-15-0276.1.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., 2012: Recent research progress on tropical cyclone structure and intensity. Trop. Cyclone Res. Rev., 1, 254275.

  • Wang, Y., , and C.-C. Wu, 2004: Current understanding of tropical cyclone structure and intensity changes—A review. Meteor. Atmos. Phys., 87, 257278, doi:10.1007/s00703-003-0055-6.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., , Y. Rao, , Z.-M. Tan, , and D. Schönemann, 2015: A statistical analysis of the effects of vertical wind shear on tropical cyclone intensity change over the western North Pacific. Mon. Wea. Rev., 143, 34343453, doi:10.1175/MWR-D-15-0049.1.

    • Search Google Scholar
    • Export Citation
  • Xu, J., , and Y. Wang, 2015: A statistical analysis on the dependence of tropical cyclone intensification rate on the storm intensity and size in the North Atlantic. Wea. Forecasting, 30, 692701, doi:10.1175/WAF-D-14-00141.1.

    • Search Google Scholar
    • Export Citation
  • Zeng, Z., , Y. Wang, , and C.-C. Wu, 2007: Environmental dynamical control of tropical cyclone intensity—An observational study. Mon. Wea. Rev., 135, 3859, doi:10.1175/MWR3278.1.

    • Search Google Scholar
    • Export Citation
  • Zeng, Z., , L.-S. Chen, , and Y. Wang, 2008: An observational study of environmental dynamical control of tropical cyclone intensity in the North Atlantic. Mon. Wea. Rev., 136, 33073322, doi:10.1175/2008MWR2388.1.

    • Search Google Scholar
    • Export Citation
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The Relationship between Sea Surface Temperature and Maximum Intensification Rate of Tropical Cyclones in the North Atlantic

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  • 1 State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, China
  • | 2 International Pacific Research Center, and Department of Atmospheric Sciences, University of Hawai‘i at Mānoa, Honolulu, Hawaii
  • | 3 Key Laboratory of Mesoscale Severe Weather, Ministry of Education, and School of the Atmospheric Sciences, Nanjing University, Nanjing, China
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Abstract

An empirical relationship between sea surface temperature (SST) and the maximum potential intensification rate (MPIR) of tropical cyclones (TCs) over the North Atlantic has been developed based on the best-track TC data and the observed SST during 1988–2014. Similar to the empirical relationship between SST and the maximum potential intensity of TCs previously documented, results from this study show a nonlinear increasing trend of the MPIR with increasing SST, with a more rapid increasing trend when SST is higher than 27°C. Further analyses indicate that about 28% of intensifying TCs over the North Atlantic reached 50% of their MPIR and only 7% reached 80% of their MPIR at the time when they were at their lifetime maximum intensification rates. Moreover, a TC tended to have a larger intensification rate when it was located in regions with higher SST and lower vertical wind shear (VWS). This indicates that although the MPIR–SST relationship is much stronger than that for the IR rate versus SST for most TCs, the actual intensification rate of a TC is determined by not only the SST but also other environmental effects, such as VWS. Additional results from a simplified dynamical system previously developed for TC intensity prediction suggest an SST-dependent TC MPIR, similar to that fitted from observations. However, the MPIR obtained from the observational fitting seems to underestimate the MPIR in regions with low SST at higher latitudes where VWS is often large. Nevertheless, this study provides the observational evidence for the existence of the MPIR for TCs.

Corresponding author address: Prof. Yuqing Wang, Room 404A, IPRC/SOEST, University of Hawai‘i at Mānoa, 1680 East-West Road, Honolulu, HI 96822. E-mail: yuqing@hawaii.edu

Abstract

An empirical relationship between sea surface temperature (SST) and the maximum potential intensification rate (MPIR) of tropical cyclones (TCs) over the North Atlantic has been developed based on the best-track TC data and the observed SST during 1988–2014. Similar to the empirical relationship between SST and the maximum potential intensity of TCs previously documented, results from this study show a nonlinear increasing trend of the MPIR with increasing SST, with a more rapid increasing trend when SST is higher than 27°C. Further analyses indicate that about 28% of intensifying TCs over the North Atlantic reached 50% of their MPIR and only 7% reached 80% of their MPIR at the time when they were at their lifetime maximum intensification rates. Moreover, a TC tended to have a larger intensification rate when it was located in regions with higher SST and lower vertical wind shear (VWS). This indicates that although the MPIR–SST relationship is much stronger than that for the IR rate versus SST for most TCs, the actual intensification rate of a TC is determined by not only the SST but also other environmental effects, such as VWS. Additional results from a simplified dynamical system previously developed for TC intensity prediction suggest an SST-dependent TC MPIR, similar to that fitted from observations. However, the MPIR obtained from the observational fitting seems to underestimate the MPIR in regions with low SST at higher latitudes where VWS is often large. Nevertheless, this study provides the observational evidence for the existence of the MPIR for TCs.

Corresponding author address: Prof. Yuqing Wang, Room 404A, IPRC/SOEST, University of Hawai‘i at Mānoa, 1680 East-West Road, Honolulu, HI 96822. E-mail: yuqing@hawaii.edu
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