• Balaguru, K., G. R. Foltz, L. R. Leung, E. D’Asaro, K. A. Emanuel, H. Liu, and S. E. Zedler, 2015: Dynamic Potential Intensity: An improved representation of the ocean’s impact on tropical cyclones. Geophys. Res. Lett., 42, 67396746, https://doi.org/10.1002/2015GL064822.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bender, M. A., and I. Ginis, 2000: Real-case simulations of hurricane–ocean interaction using a high-resolution coupled model: Effects on hurricane intensity. Mon. Wea. Rev., 128, 917946, https://doi.org/10.1175/1520-0493(2000)128<0917:RCSOHO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carton, J. A., and Z. Zhou, 1997: Annual cycle of sea surface temperature in the tropical Atlantic Ocean. J. Geophys. Res., 102, 2781327824, https://doi.org/10.1029/97JC02197.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carton, J. A., and B. S. Giese, 2008: A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA). Mon. Wea. Rev., 136, 29993017, https://doi.org/10.1175/2007MWR1978.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chan, J. C. L., and W. M. Gray, 1982: Tropical cyclone movement and surrounding flow relationships. Mon. Wea. Rev., 110, 13541374, https://doi.org/10.1175/1520-0493(1982)110<1354:TCMASF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chavas, D. R., and K. A. Emanuel, 2010: A QuikSCAT climatology of tropical cyclone size. Geophys. Res. Lett., 37, L18816, https://doi.org/10.1029/2010GL044558.

    • Crossref
    • 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. Naval Research Laboratory Tech. Rep. NRL/MR/7540-02-16, http://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc/best_tracks/TC_bt_report.html.

  • Cione, J. J., and E. W. Uhlhorn, 2003: Sea surface temperature variability in hurricanes: Implications with respect to intensity change. Mon. Wea. Rev., 131, 17831796, https://doi.org/10.1175//2562.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, K. H., 1999: Generation of the African easterly jet and its role in determining West African precipitation. J. Climate, 12, 11651184, https://doi.org/10.1175/1520-0442(1999)012<1165:GOTAEJ>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and et al. , 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeMaria, M., 1996: The effect of vertical shear on tropical cyclone intensity change. J. Atmos. Sci., 53, 20762088, https://doi.org/10.1175/1520-0469(1996)053<2076:TEOVSO>2.0.CO;2.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeMaria, M., and J. Kaplan, 1994b: A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic basin. Wea. Forecasting, 9, 209220, https://doi.org/10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeMaria, M., and J. Kaplan, 1999: An updated Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic and eastern North Pacific basins. Wea. Forecasting, 14, 326337, https://doi.org/10.1175/1520-0434(1999)014<0326:AUSHIP>2.0.CO;2.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Szoeke, S., and S.-P. Xie, 2008: The tropical eastern Pacific seasonal cycle: Assessment of errors and mechanisms in IPCC AR4 coupled ocean–atmosphere general circulation models. J. Climate, 21, 25732590, https://doi.org/10.1175/2007JCLI1975.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1999: Thermodynamic control of hurricane intensity. Nature, 401, 665669, https://doi.org/10.1038/44326.

  • Fitzpatrick, P. J., 1997: Understanding and forecasting tropical cyclone intensity change with the Typhoon Intensity Prediction Scheme (TIPS). Wea. Forecasting, 12, 826846, https://doi.org/10.1175/1520-0434(1997)012<0826:UAFTCI>2.0.CO;2.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Held, I. M., and A. Y. Hou, 1980: Nonlinear axially symmetric circulations in a nearly inviscid atmosphere. J. Atmos. Sci., 37, 515533, https://doi.org/10.1175/1520-0469(1980)037<0515:NASCIA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holland, G. J., 1983: Tropical cyclone motion: Environmental interaction plus a beta effect. J. Atmos. Sci., 40, 328342, https://doi.org/10.1175/1520-0469(1983)040<0328:TCMEIP>2.0.CO;2.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koch, P. , H. Wernli, and H.C. Davies, 2006: An event-based jet-stream climatology and typology. Int. J. Climatol., 26, 283301, https://doi.org/10.1002/joc.1255.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuang, X., and Y. Zhang, 2005: Seasonal variation of the East Asian Subtropical Westerly Jet and its association with the heating field over East Asia. Adv. Atmos. Sci., 22, 831840, https://doi.org/10.1007/BF02918683.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landsea, C. W., and J. L. Franklin, 2013: Atlantic hurricane database uncertainty and presentation of a new database format. Mon. Wea. Rev., 141, 35763592, https://doi.org/10.1175/MWR-D-12-00254.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lau, K.-M., H.-T. Wu, and S. Bony, 1997: The role of large-scale atmospheric circulation in the relationship between tropical convection and sea surface temperature. J. Climate, 10, 381392, https://doi.org/10.1175/1520-0442(1997)010<0381:TROLSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, C.-Y., M. K. Tippett, S. J. Camargo, and A. H. Sobel, 2015: Probabilistic multiple linear regression modeling for tropical cyclone intensity. Mon. Wea. Rev., 143, 933954, https://doi.org/10.1175/MWR-D-14-00171.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, I. I., and et al. , 2013: An ocean coupling potential intensity index for tropical cyclones. Geophys. Res. Lett., 40, 18781882, https://doi.org/10.1002/grl.50091.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, N., R. Jing, Y. Y. Wang, E. Yonekura, J. Q. Fan, and L. Z. Xue, 2017: A statistical investigation of the dependence of tropical cyclone intensity change on the surrounding environment. Mon. Wea. Rev., 145, 28132831, https://doi.org/10.1175/MWR-D-16-0368.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lloyd, I. D., and G. A. Vecchi, 2011: Observational evidence for oceanic controls on hurricane intensity. J. Climate, 24, 11381153, https://doi.org/10.1175/2010JCLI3763.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Malkus, J. S., and H. Riehl, 1960: On the dynamics and energy transformations in steady-state hurricanes. Tellus, 12 (1), 120, https://doi.org/10.3402/tellusa.v12i1.9351.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mei, W., C. Pasquero, and F. Primeau, 2012: The effect of translation speed upon the intensity of tropical cyclones over the tropical ocean. Geophys. Res. Lett., 39, L07801, https://doi.org/10.1029/2011GL050765.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neetu, S., and et al. , 2017: Global assessment of tropical cyclone intensity statistical–dynamical hindcasts. Quart. J. Roy. Meteor. Soc., 143, 21432156, https://doi.org/10.1002/qj.3073.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Palmén, E., 1948: On the formation and structure of tropical hurricanes. Geophysica, 3, 2639.

  • Price, J. F., 1981: Upper ocean response to a hurricane. J. Phys. Oceanogr., 11, 153175, https://doi.org/10.1175/1520-0485(1981)011<0153:UORTAH>2.0.CO;2.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vincent, E. M., M. Lengaigne, J. Vialard, G. Madec, N. C. Jourdain, and S. Masson, 2012: Assessing the oceanic control on the amplitude of sea surface cooling induced by tropical cyclones. J. Geophys. Res., 117, C05023, https://doi.org/10.1029/2011JC007705.

    • Search Google Scholar
    • Export Citation
  • Whitney, L. D., and J. S. Hobgood, 1997: The relationship between sea surface temperatures and maximum intensities of tropical cyclones in the eastern North Pacific Ocean. J. Climate, 10, 29212930, https://doi.org/10.1175/1520-0442(1997)010<2921:TRBSST>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, J., Y. Q. Wang, and Z. M. Tan, 2016: The relationship between sea surface temperature and maximum intensification rate of tropical cyclones in the North Atlantic. J. Atmos. Sci., 73, 49794988, https://doi.org/10.1175/JAS-D-16-0164.1.

    • Crossref
    • 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, https://doi.org/10.1175/MWR3278.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Interbasin Differences in the Relationship between SST and Tropical Cyclone Intensification

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  • 1 NOAA/Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida
  • | 2 Marine Sciences Laboratory, Pacific Northwest National Laboratory, Seattle, Washington
  • | 3 Pacific Northwest National Laboratory, Richland, Washington
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ABSTRACT

Sea surface temperature (SST) is one of the most important parameters for tropical cyclone (TC) intensification. Here, it is shown that the relationship between SST and TC intensification varies considerably from basin to basin, with SST explaining less than 4% of the variance in TC intensification rates in the Atlantic, 12% in the western North Pacific, and 23% in the eastern Pacific. Several factors are shown to be responsible for these interbasin differences. First, variability of SST along TCs’ tracks is lower in the Atlantic. This is due to smaller horizontal SST gradients in the Atlantic, compared to the Pacific, and stronger damping of prestorm SST’s contribution to TC intensification by the storm-induced cold SST wake in the Atlantic. The damping occurs because SST tends to vary in phase with TC-induced SST cooling: in the Gulf of Mexico and northwestern Atlantic, where SSTs are highest, TCs tend to be strongest and their translations slowest, resulting in the strongest storm-induced cooling. The tendency for TCs to be more intense over the warmest SST in the Atlantic also limits the usefulness of SST as a predictor since stronger storms are less likely to experience intensification. Finally, SST tends to vary out of phase with vertical wind shear and outflow temperature in the western Pacific. This strengthens the relationship between SST and TC intensification more in the western Pacific than in the eastern Pacific or Atlantic. Combined, these factors explain why prestorm SST is such a poor predictor of TC intensification in the Atlantic, compared to the eastern and western North Pacific.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Gregory Foltz, gregory.foltz@noaa.gov

ABSTRACT

Sea surface temperature (SST) is one of the most important parameters for tropical cyclone (TC) intensification. Here, it is shown that the relationship between SST and TC intensification varies considerably from basin to basin, with SST explaining less than 4% of the variance in TC intensification rates in the Atlantic, 12% in the western North Pacific, and 23% in the eastern Pacific. Several factors are shown to be responsible for these interbasin differences. First, variability of SST along TCs’ tracks is lower in the Atlantic. This is due to smaller horizontal SST gradients in the Atlantic, compared to the Pacific, and stronger damping of prestorm SST’s contribution to TC intensification by the storm-induced cold SST wake in the Atlantic. The damping occurs because SST tends to vary in phase with TC-induced SST cooling: in the Gulf of Mexico and northwestern Atlantic, where SSTs are highest, TCs tend to be strongest and their translations slowest, resulting in the strongest storm-induced cooling. The tendency for TCs to be more intense over the warmest SST in the Atlantic also limits the usefulness of SST as a predictor since stronger storms are less likely to experience intensification. Finally, SST tends to vary out of phase with vertical wind shear and outflow temperature in the western Pacific. This strengthens the relationship between SST and TC intensification more in the western Pacific than in the eastern Pacific or Atlantic. Combined, these factors explain why prestorm SST is such a poor predictor of TC intensification in the Atlantic, compared to the eastern and western North Pacific.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Gregory Foltz, gregory.foltz@noaa.gov
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