• Ahmad, K. A., , W. L. Jones, , T. Kasparis, , S. W. Vergara, , I. S. Adams, , and J. D. Park, 2005: Oceanic rain rate estimates from the QuikSCAT radiometer: A global precipitation mission pathfinder. J. Geophys. Res., 110, D11101, doi:10.1029/2004JD005560.

    • Search Google Scholar
    • Export Citation
  • Arakawa, H., 1952: Mame-Taifu or midget typhoon. Geophys. Mag., 23, 463474.

  • Bister, M., , and K. A. Emanuel, 1998: Dissipative heating and hurricane intensity. Meteor. Atmos. Phys., 65, 233240, doi:10.1007/BF01030791.

    • Search Google Scholar
    • Export Citation
  • Bister, M., , and K. A. Emanuel, 2002: Low frequency variability of tropical cyclone potential intensity. 2. Climatology for 1982–1995. J. Geophys. Res., 107, 4621, doi:10.1029/2001JD000780.

    • Search Google Scholar
    • Export Citation
  • Brand, S., 1972: Very large and very small typhoons of the western North Pacific Ocean. J. Meteor. Soc. Japan, 50, 332341.

  • Camargo, S. J., , M. Ting, , and Y. Kushnir, 2013: Influence of local and remote SST on North Atlantic tropical cyclone potential intensity. Climate Dyn., 40, 15151529, doi:10.1007/s00382-012-1536-4.

    • Search Google Scholar
    • Export Citation
  • Chan, J. C., 2005: The physics of tropical cyclone motion. Annu. Rev. Fluid Mech., 37, 99128, doi:10.1146/annurev.fluid.37.061903.175702.

    • Search Google Scholar
    • Export Citation
  • Chan, K. T., , and J. C. Chan, 2012: Size and strength of tropical cyclones as inferred from QuikSCAT data. Mon. Wea. Rev., 140, 811824, doi:10.1175/MWR-D-10-05062.1.

    • Search Google Scholar
    • Export Citation
  • Chan, K. T., , and J. C. Chan, 2015: Global climatology of tropical cyclone size as inferred from QuikSCAT data. Int. J. Climatol., 35, 48434848, doi:10.1002/joc.4307.

    • 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, doi:10.1029/2010GL044558.

    • Search Google Scholar
    • Export Citation
  • Chavas, D. R., , and K. A. Emanuel, 2014: Equilibrium tropical cyclone size in an idealized state of axisymmetric radiative–convective equilibrium. J. Atmos. Sci., 71, 16631680, doi:10.1175/JAS-D-13-0155.1.

    • Search Google Scholar
    • Export Citation
  • Chavas, D. R., , and J. Vigh, 2014: QSCAT-R: The QuikSCAT tropical cyclone radial structure dataset. NCAR Tech. Note TN-513+STR, 27 pp.

  • Chavas, D. R., , N. Lin, , and K. Emanuel, 2015: A model for the complete radial structure of the tropical cyclone wind field. Part I: Comparison with observed structure. J. Atmos. Sci., 72, 36473662, doi:10.1175/JAS-D-15-0014.1.

    • Search Google Scholar
    • Export Citation
  • Cocks, S. B., , and W. M. Gray, 2002: Variability of the outer wind profiles of western North Pacific typhoons: Classifications and techniques for analysis and forecasting. Mon. Wea. Rev., 130, 19892005, doi:10.1175/1520-0493(2002)130<1989:VOTOWP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Courtney, J., , and J. A. Knaff, 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
  • Davis, C. A., 2015: The formation of moist vortices and tropical cyclones in idealized simulations. J. Atmos. Sci., 72, 34993516, doi:10.1175/JAS-D-15-0027.1.

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

    • Search Google Scholar
    • Export Citation
  • Donelan, M., , B. Haus, , N. Reul, , W. Plant, , M. Stiassnie, , H. Graber, , O. Brown, , and E. Saltzman, 2004: On the limiting aerodynamic roughness of the ocean in very strong winds. Geophys. Res. Lett., 31, L18306, doi:10.1029/2004GL019460.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1986: An air–sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci., 43, 585605, doi:10.1175/1520-0469(1986)043<0585:AASITF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1987: The dependence of hurricane intensity on climate. Nature, 326, 483485, doi:10.1038/326483a0.

  • Emanuel, K. A., 1994: Atmospheric Convection. Oxford University Press, 580 pp.

  • Emanuel, K. A., 1995a: 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., 1995b: Sensitivity of tropical cyclones to surface exchange coefficients and a revised steady-state model incorporating eye dynamics. J. Atmos. Sci., 52, 39693976, doi:10.1175/1520-0469(1995)052<3969:SOTCTS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 2004: Tropical cyclone energetics and structure. Atmospheric Turbulence and Mesoscale Meteorology, E. Fedorovich, R. Rotunno, and B. Stevens, Eds., Cambridge University Press, 165–192.

  • Emanuel, K. A., , and R. Rotunno, 2011: Self-stratification of tropical cyclone outflow. Part I: Implications for storm structure. J. Atmos. Sci., 68, 22362249, doi:10.1175/JAS-D-10-05024.1.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., , J. David Neelin, , and C. S. Bretherton, 1994: On large-scale circulations in convecting atmospheres. Quart. J. Roy. Meteor. Soc., 120, 11111143, doi:10.1002/qj.49712051902.

    • Search Google Scholar
    • Export Citation
  • Frank, W. M., 1977: The structure and energetics of the tropical cyclone. I: Storm structure. Mon. Wea. Rev., 105, 11191135, doi:10.1175/1520-0493(1977)105<1119:TSAEOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hart, R. E., , and J. L. Evans, 2001: A climatology of the extratropical transition of Atlantic tropical cyclones. J. Climate, 14, 546564, doi:10.1175/1520-0442(2001)014<0546:ACOTET>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hill, K. A., , and G. M. Lackmann, 2009: Influence of environmental humidity on tropical cyclone size. Mon. Wea. Rev., 137, 32943315, doi:10.1175/2009MWR2679.1.

    • Search Google Scholar
    • Export Citation
  • Irish, J. L., , and D. T. Resio, 2010: A hydrodynamics-based surge scale for hurricanes. Ocean Eng., 37, 6981, doi:10.1016/j.oceaneng.2009.07.012.

    • Search Google Scholar
    • Export Citation
  • Khairoutdinov, M., , and K. Emanuel, 2013: Rotating radiative-convective equilibrium simulated by a cloud-resolving model. J. Adv. Model. Earth Syst., 5, 816825, doi:10.1002/2013MS000253.

    • Search Google Scholar
    • Export Citation
  • Kieu, C. Q., , H. Chen, , and D.-L. Zhang, 2010: An examination of the pressure–wind relationship for intense tropical cyclones. Wea. Forecasting, 25, 895907, doi:10.1175/2010WAF2222344.1.

    • Search Google Scholar
    • Export Citation
  • Kim, H.-S., , G. A. Vecchi, , T. R. Knutson, , W. G. Anderson, , T. L. Delworth, , A. Rosati, , F. Zeng, , and M. Zhao, 2014: Tropical cyclone simulation and response to CO2 doubling in the GFDL CM2.5 high-resolution coupled climate model. J. Climate, 27, 80348054, doi:10.1175/JCLI-D-13-00475.1.

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., , and R. M. Zehr, 2007: Reexamination of tropical cyclone wind–pressure relationships. Wea. Forecasting, 22, 7188, doi:10.1175/WAF965.1.

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., , C. R. Sampson, , M. DeMaria, , T. P. Marchok, , J. M. Gross, , and C. J. McAdie, 2007: Statistical tropical cyclone wind radii prediction using climatology and persistence. Wea. Forecasting, 22, 781791, doi:10.1175/WAF1026.1.

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., , S. P. Longmore, , and D. A. Molenar, 2014: An objective satellite-based tropical cyclone size climatology. J. Climate, 27, 455476, doi:10.1175/JCLI-D-13-00096.1; Corrigendum, 28, 86488651, doi:10.1175/JCLI-D-15-0610.1.

    • Search Google Scholar
    • Export Citation
  • Knutson, T., , J. Sirutis, , M. Zhao, , R. Tuleya, , M. Bender, , G. Vecchi, , G. Villarini, , and D. Chavas, 2015: Global projections of intense tropical cyclone activity for the late twenty-first century from dynamical downscaling of CMIP5/RCP4.5 scenarios. J. Climate, 28, 72037224, doi:10.1175/JCLI-D-15-0129.1.

    • Search Google Scholar
    • Export Citation
  • Kossin, J. P., , J. A. Knaff, , H. I. Berger, , D. C. Herndon, , T. A. Cram, , C. S. Velden, , R. J. Murnane, , and J. D. Hawkins, 2007: Estimating hurricane wind structure in the absence of aircraft reconnaissance. Wea. Forecasting, 22, 89101, doi:10.1175/WAF985.1.

    • Search Google Scholar
    • Export Citation
  • Kossin, J. P., , K. A. Emanuel, , and G. A. Vecchi, 2014: The poleward migration of the location of tropical cyclone maximum intensity. Nature, 509, 349352, doi:10.1038/nature13278.

    • Search Google Scholar
    • Export Citation
  • Lander, M. A., 1994: Description of a monsoon gyre and its effects on the tropical cyclones in the western North Pacific during August 1991. Wea. Forecasting, 9, 640654, doi:10.1175/1520-0434(1994)009<0640:DOAMGA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lee, C.-S., , K. K. Cheung, , W.-T. Fang, , and R. L. Elsberry, 2010: Initial maintenance of tropical cyclone size in the western North Pacific. Mon. Wea. Rev., 138, 32073223, doi:10.1175/2010MWR3023.1.

    • Search Google Scholar
    • Export Citation
  • Lin, N., , and D. Chavas, 2012: On hurricane parametric wind and applications in storm surge modeling. J. Geophys. Res., 117, D09120, doi:10.1029/2011JD017126.

    • Search Google Scholar
    • Export Citation
  • Lin, N., , and K. A. Emanuel, 2016: Grey swan tropical cyclones. Nat. Climate Change, 6, 106111, doi:10.1038/nclimate2777.

  • Lin, N., , K. A. Emanuel, , M. Oppenheimer, , and E. Vanmarcke, 2012: Physically based assessment of hurricane surge threat under climate change. Nat. Climate Change, 2, 462467, doi:10.1038/nclimate1389.

    • Search Google Scholar
    • Export Citation
  • Lin, N., , P. Lane, , K. A. Emanuel, , R. M. Sullivan, , and J. P. Donnelly, 2014: Heightened hurricane surge risk in northwest Florida revealed from climatological-hydrodynamic modeling and paleorecord reconstruction. J. Geophys. Res., 119, 86068623, doi:10.1002/2014JD021584.

    • Search Google Scholar
    • Export Citation
  • Lin, Y., , M. Zhao, , and M. Zhang, 2015: Tropical cyclone rainfall area controlled by relative sea surface temperature. Nat. Commun., 6, 6591, doi:10.1038/ncomms7591.

    • Search Google Scholar
    • Export Citation
  • Massey, F. J., Jr., 1951: The Kolmogorov–Smirnov test for goodness of fit. J. Amer. Stat. Assoc., 46, 6878, doi:10.1080/01621459.1951.10500769.

    • Search Google Scholar
    • Export Citation
  • Matyas, C. J., 2010: Associations between the size of hurricane rain fields at landfall and their surrounding environments. Meteor. Atmos. Phys., 106, 135148, doi:10.1007/s00703-009-0056-1.

    • Search Google Scholar
    • Export Citation
  • Merrill, R. T., 1984: A comparison of large and small tropical cyclones. Mon. Wea. Rev., 112, 14081418, doi:10.1175/1520-0493(1984)112<1408:ACOLAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mueller, K. J., , M. DeMaria, , J. Knaff, , J. P. Kossin, , and T. H. Vonder Haar, 2006: Objective estimation of tropical cyclone wind structure from infrared satellite data. Wea. Forecasting, 21, 9901005, doi:10.1175/WAF955.1.

    • Search Google Scholar
    • Export Citation
  • Pauluis, O., , and I. M. Held, 2002: Entropy budget of an atmosphere in radiative–convective equilibrium. Part I: Maximum work and frictional dissipation. J. Atmos. Sci., 59, 125139, doi:10.1175/1520-0469(2002)059<0125:EBOAAI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Pielke, R. A., Jr., , J. Gratz, , C. W. Landsea, , D. Collins, , M. A. Saunders, , and R. Musulin, 2008: Normalized hurricane damages in the United States: 1900–2005. Nat. Hazards Rev., 9, 2942, doi:10.1061/(ASCE)1527-6988(2008)9:1(29).

    • Search Google Scholar
    • Export Citation
  • Powell, M. D., , S. H. Houston, , L. R. Amat, , and N. Morisseau-Leroy, 1998: The HRD real-time hurricane wind analysis system. J. Wind Eng. Ind. Aerodyn., 77–78, 5364, doi:10.1016/S0167-6105(98)00131-7.

    • Search Google Scholar
    • Export Citation
  • Ramsay, H. A., , and A. H. Sobel, 2011: Effects of relative and absolute sea surface temperature on tropical cyclone potential intensity using a single-column model. J. Climate, 24, 183193, doi:10.1175/2010JCLI3690.1.

    • Search Google Scholar
    • Export Citation
  • Reasor, P. D., , M. T. Montgomery, , F. D. Marks Jr., , and J. F. Gamache, 2000: Low-wavenumber structure and evolution of the hurricane inner core observed by airborne dual-doppler radar. Mon. Wea. Rev., 128, 16531680, doi:10.1175/1520-0493(2000)128<1653:LWSAEO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Reed, K. A., , and D. R. Chavas, 2015: Uniformly rotating global radiative–convective equilibrium in the Community Atmosphere Model, version 5. J. Adv. Model. Earth Syst., 7, 19381955, doi:10.1002/2015MS000519.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., , and K. A. Emanuel, 1987: An air–sea interaction theory for tropical cyclones. Part II: Evolutionary study using a nonhydrostatic axisymmetric numerical model. J. Atmos. Sci., 44, 542561, doi:10.1175/1520-0469(1987)044<0542:AAITFT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., , and G. H. Bryan, 2012: Effects of parameterized diffusion on simulated hurricanes. J. Atmos. Sci., 69, 22842299, doi:10.1175/JAS-D-11-0204.1.

    • Search Google Scholar
    • Export Citation
  • Schwerdt, R. W., , F. P. Ho, , and R. R. Watkins, 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.

  • Shoemaker, D. N., 1989: Relationships between tropical cyclone deep convection and the radial extent of damaging winds. University of Colorado Department of Atmospheric Science Paper 457, 109 pp. [Available online at http://hdl.handle.net/10217/78813.]

  • Sitkowski, M., , J. P. Kossin, , and C. M. Rozoff, 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
  • Smith, R. K., , C. W. Schmidt, , and M. T. Montgomery, 2011: An investigation of rotational influences on tropical-cyclone size and intensity. Quart. J. Roy. Meteor. Soc., 137, 18411855, doi:10.1002/qj.862.

    • Search Google Scholar
    • Export Citation
  • Sobel, A. H., , and C. S. Bretherton, 2000: Modeling tropical precipitation in a single column. J. Climate, 13, 43784392, doi:10.1175/1520-0442(2000)013<4378:MTPIAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., 1990: On the relationship between water vapor over the oceans and sea surface temperature. J. Climate, 3, 634645, doi:10.1175/1520-0442(1990)003<0634:OTRBWV>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Stewart, S., 2014: National Hurricane Center annual summary: 2012 Atlantic hurricane season. National Hurricane Center Tropical Cyclone Rep., 11 pp. [Available online at http://www.nhc.noaa.gov/data/tcr/summary_atlc_2012.pdf.]

  • Stiles, B. W., , R. E. Danielson, , W. L. Poulsen, , M. J. Brennan, , S. Hristova-Veleva, , T.-P. Shen, , and A. G. Fore, 2014: Optimized tropical cyclone winds from QuikSCAT: A neural network approach, 52, 74187434, doi:10.1109/TGRS.2014.2312333.

    • Search Google Scholar
    • Export Citation
  • Tang, B., , and K. Emanuel, 2010: Midlevel ventilation’s constraint on tropical cyclone intensity. J. Atmos. Sci., 67, 18171830, doi:10.1175/2010JAS3318.1.

    • Search Google Scholar
    • Export Citation
  • Tang, B., , and K. Emanuel, 2012: A ventilation index for tropical cyclones. Bull. Amer. Meteor. Soc., 93, 19011912, doi:10.1175/BAMS-D-11-00165.1.

    • Search Google Scholar
    • Export Citation
  • Uhlhorn, E. W., , B. W. Klotz, , T. Vukicevic, , P. D. Reasor, , and R. F. Rogers, 2014: Observed hurricane wind speed asymmetries and relationships to motion and environmental shear. Mon. Wea. Rev., 142, 12901311, doi:10.1175/MWR-D-13-00249.1.

    • Search Google Scholar
    • Export Citation
  • Vecchi, G. A., , and B. J. Soden, 2007: Effect of remote sea surface temperature change on tropical cyclone potential intensity. Nature, 450, 10661070, doi:10.1038/nature06423.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., 2009: How do outer spiral rainbands affect tropical cyclone structure and intensity? J. Atmos. Sci., 66, 12501273, doi:10.1175/2008JAS2737.1.

    • Search Google Scholar
    • Export Citation
  • Weatherford, C., , and W. Gray, 1988: Typhoon structure as revealed by aircraft reconnaissance. Part I: Data analysis and climatology. Mon. Wea. Rev., 116, 10321043, doi:10.1175/1520-0493(1988)116<1032:TSARBA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhai, A. R., , and J. H. Jiang, 2014: Dependence of U.S. hurricane economic loss on maximum wind speed and storm size. Environ. Res. Lett., 9, 064019, doi:10.1088/1748-9326/9/6/064019.

    • Search Google Scholar
    • Export Citation
  • Zhou, W., , I. M. Held, , and S. T. Garner, 2014: Parameter study of tropical cyclones in rotating radiative–convective equilibrium with column physics and resolution of a 25-km GCM. J. Atmos. Sci., 71, 10581069, doi:10.1175/JAS-D-13-0190.1.

    • Search Google Scholar
    • Export Citation
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Observed Tropical Cyclone Size Revisited

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  • 1 Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey
  • | 2 Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China
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Abstract

This work revisits the statistics of observed tropical cyclone outer size in the context of recent advances in our theoretical understanding of the storm wind field. The authors create a new dataset of the radius of 12 m s−1 winds based on a recently updated version of the QuikSCAT ocean wind vector database and apply an improved analytical outer wind model to estimate the outer radius of vanishing wind. The dataset is then applied to analyze the statistical distributions of the two size metrics as well as their dependence on environmental parameters, with a specific focus on testing recently identified parameters possessing credible theoretical relationships with tropical cyclone size. The ratio of the potential intensity to the Coriolis parameter is found to perform poorly in explaining variation of size, with the possible exception of its upper bound, the latter of which is in line with existing theory. The rotating radiative–convective equilibrium scaling of Khairoutdinov and Emanuel is also found to perform poorly. Meanwhile, mean storm size is found to increase systematically with the relative sea surface temperature, in quantitative agreement with the results of a recent study of storm size based on precipitation area. Implications of these results are discussed in the context of existing tropical climate theory. Finally, an empirical dependence of the central pressure deficit on outer size is found in line with past work.

Denotes Open Access content.

Current affiliation: Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana.

Corresponding author address: Daniel R. Chavas, Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, 550 Stadium Mall Drive, HAMP 3221, West Lafayette, IN 47907. E-mail: drchavas@gmail.com

Abstract

This work revisits the statistics of observed tropical cyclone outer size in the context of recent advances in our theoretical understanding of the storm wind field. The authors create a new dataset of the radius of 12 m s−1 winds based on a recently updated version of the QuikSCAT ocean wind vector database and apply an improved analytical outer wind model to estimate the outer radius of vanishing wind. The dataset is then applied to analyze the statistical distributions of the two size metrics as well as their dependence on environmental parameters, with a specific focus on testing recently identified parameters possessing credible theoretical relationships with tropical cyclone size. The ratio of the potential intensity to the Coriolis parameter is found to perform poorly in explaining variation of size, with the possible exception of its upper bound, the latter of which is in line with existing theory. The rotating radiative–convective equilibrium scaling of Khairoutdinov and Emanuel is also found to perform poorly. Meanwhile, mean storm size is found to increase systematically with the relative sea surface temperature, in quantitative agreement with the results of a recent study of storm size based on precipitation area. Implications of these results are discussed in the context of existing tropical climate theory. Finally, an empirical dependence of the central pressure deficit on outer size is found in line with past work.

Denotes Open Access content.

Current affiliation: Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana.

Corresponding author address: Daniel R. Chavas, Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, 550 Stadium Mall Drive, HAMP 3221, West Lafayette, IN 47907. E-mail: drchavas@gmail.com
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