• Bell, S. S., S. S. Chand, K. J. Tory, and C. Turville, 2018: Statistical assessment of the OWZ tropical cyclone tracking scheme in ERA-Interim. J. Climate, 31, 22172232, https://doi.org/10.1175/JCLI-D-17-0548.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bell, S. S., S. S. Chand, K. J. Tory, A. J. Dowdy, C. Turville, and H. Ye, 2019a: Projections of Southern Hemisphere tropical cyclone track density using CMIP5 models. Climate Dyn., 52, 60656079, https://doi.org/10.1007/s00382-018-4497-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bell, S. S., S. S. Chand, K. J. Tory, C. Turville, and H. Ye, 2019b: Eastern North Pacific tropical cyclone activity in historical and future CMIP5 experiments: Assessment with a model-independent tracking scheme. Climate Dyn., https://doi.org/10.1007/S00382-019-04830-0.

    • Search Google Scholar
    • Export Citation
  • Bengtsson, L., K. I. Hodges, M. Esch, N. Keenlyside, L. Kornblueh, J.-J. Luo, and T. Yamagata, 2007: How may tropical cyclones change in a warmer climate? Tellus, 59A, 539561, https://doi.org/10.1111/j.1600-0870.2007.00251.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bi, D., and et al. , 2012: The ACCESS coupled model: Description, control climate and evaluation. Aust. Meteor. Oceanogr. J., 63, 4164, https://doi.org/10.22499/2.6301.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., 2013: Global and regional aspects of tropical cyclone activity in the CMIP5 models. J. Climate, 26, 98809902, https://doi.org/10.1175/JCLI-D-12-00549.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., and S. E. Zebiak, 2002: Improving the detection and tracking of tropical cyclones in atmospheric general circulation models. Wea. Forecasting, 17, 11521162, https://doi.org/10.1175/1520-0434(2002)017<1152:ITDATO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., A. W. Robertson, S. J. Gaffney, P. Smyth, and M. Ghil, 2007a: Cluster analysis of typhoon tracks. Part I: General properties. J. Climate, 20, 36353653, https://doi.org/10.1175/JCLI4188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., A. W. Robertson, S. J. Gaffney, P. Smyth, and M. Ghil, 2007b: Cluster analysis of typhoon tracks: Part II: Large-scale circulation and ENSO. J. Climate, 20, 36543676, https://doi.org/10.1175/JCLI4203.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., A. H. Sobel, A. D. Delgenio, J. A. Jonas, M. Kelley, Y. Lu, D. A. Shaevitz, and N. Henderson, 2016: Tropical cyclones in the GISS ModelE2. Tellus, 68A, 31494, https://doi.org/10.3402/tellusa.v68.31494.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chand, S. S., K. J. Tory, H. Ye, and K. J. E. Walsh, 2017: Projected increase in El Niño-driven tropical cyclone frequency in the Pacific. Nat. Climate Change, 7, 123127, https://doi.org/10.1038/nclimate3181.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colbert, A. J., B. J. Soden, and B. P. Kirtman, 2015: The impact of natural and anthropogenic climate change on western North Pacific tropical cyclone tracks. J. Climate, 28, 18061823, https://doi.org/10.1175/JCLI-D-14-00100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collier, M. A., and et al. , 2011: The CSIRO-Mk3.6.0 atmosphere–ocean GCM: Participation in CMIP5 and data publication. Proc. 19th Int. Congress on Modelling and Simulation, Perth, Australia, 2691–2697, http://mssanz.org.au/modsim2011.

  • Davis, C. A., 2018: Resolving tropical cyclone intensity in models. Geophys. Res. Lett., 45, 20822087, https://doi.org/10.1002/2017GL076966.

  • Donner, L. J., and et al. , 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J. Climate, 24, 34843519, https://doi.org/10.1175/2011JCLI3955.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunkerton, T. J., M. T. Montgomery, and Z. Wang, 2009: Tropical cyclogenesis in a tropical wave critical layer: Easterly waves. Atmos. Chem. Phys., 9, 55875646, https://doi.org/10.5194/acp-9-5587-2009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 2013: Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century. Proc. Natl. Acad. Sci. USA, 110, 12 21912 224, https://doi.org/10.1073/pnas.1301293110.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gaffney, S. J., 2004: Probabilistic curve-aligned clustering and prediction with regression mixture models. Ph.D. thesis, University of California, Irvine, CA, 281 pp., http://www.ics.uci.edu/pub/sgaffney/outgoing/sgaffney_thesis.pdf.

  • Gaffney, S. J., A. W. Robertson, P. Smyth, S. J. Camargo, and M. Ghil, 2007: Probabilistic clustering of extratropical cyclones using regression mixture models. Climate Dyn., 29, 423440, https://doi.org/10.1007/s00382-007-0235-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gao, S., Z. Chen, and W. Zhang, 2018: Impacts of tropical North Atlantic SST on western North Pacific landfalling tropical cyclones. J. Climate, 31, 853862, https://doi.org/10.1175/JCLI-D-17-0325.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gent, P. R., and et al. , 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991, https://doi.org/10.1175/2011JCLI4083.1.

    • 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
  • Gray, W. M., 1975: Tropical cyclone genesis. Dept. of Atmospheric Science Paper 234, Colorado State University, 121 pp.

  • Harr, P. A., and R. L. Elsberry, 1995: Large-scale circulation variability over the tropical western North Pacific. Part I: Spatial patterns and tropical cyclone characteristics. Mon. Wea. Rev., 123, 12251246, https://doi.org/10.1175/1520-0493(1995)123<1225:LSCVOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hawkins, E., T. M. Osbourne, C. K. Ho, and A. J. Challinor, 2013: Calibration and bias correction of climate projections for crop modelling: An idealised case study over Europe. Agric. For. Meteor., 170, 1931, https://doi.org/10.1016/j.agrformet.2012.04.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Held, I. M., and M. Zhao, 2011: The response of tropical cyclone statistics to an increase in CO2 with fixed sea surface temperatures. J. Climate, 24, 53535364, https://doi.org/10.1175/JCLI-D-11-00050.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ho, C. K., D. B. Stephenson, M. Collins, C. A. T. Ferro, and S. J. Brown, 2012: A source of additional uncertainty in climate change projections. Bull. Amer. Meteor. Soc., 93, 2126, https://doi.org/10.1175/2011BAMS3110.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Horn, M., and et al. , 2014: Tracking scheme dependence of simulated tropical cyclone response to idealized climate simulations. J. Climate, 27, 91979213, https://doi.org/10.1175/JCLI-D-14-00200.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, C.-S., D.-H. Cha, M.-S. Suh, S.-Y. Hong, H.-S. Kang, and C.-H. Ho, 2016: Evaluation of climatological tropical cyclone activity over the western North Pacific in the CORDEX-East Asia multi-RCM simulations. Climate Dyn., 47, 765778, https://doi.org/10.1007/s00382-015-2869-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C. D., and et al. , 2011: The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci. Model Dev., 4, 543570, https://doi.org/10.5194/gmd-4-543-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • JTWC, 2017: JTWC best track dataset. Subset used: January 1979–December 2013, accessed 7 September 2017, Joint Typhoon Warning Center, https://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc/best_tracks/.

  • Knutson, T. R., and et al. , 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, https://doi.org/10.1175/JCLI-D-15-0129.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knutti, R., D. Masson, and A. Gettelman, 2013: Climate model genealogy: Generation CMIP5 and how we got there. Geophys. Res. Lett., 40, 11941199, https://doi.org/10.1002/grl.50256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kossin, J. P., K. A. Emanuel, and S. J. Camargo, 2016: Past and projected changes in western North Pacific tropical cyclone exposure. J. Climate, 29, 57255739, https://doi.org/10.1175/JCLI-D-16-0076.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., C. Covey, T. Delworth, M. Latif, B. McAvaney, J. F. B. Mitchell, R. J. Stouffer, and K. R. Taylor, 2007: THE WCRP CMIP3 multimodel dataset: A new era in climate change research. Bull. Amer. Meteor. Soc., 88, 13831394, https://doi.org/10.1175/BAMS-88-9-1383.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moise, A., and et al. , 2015: Evaluation of CMIP3 and CMIP5 models over the Australian region to inform confidence in projections. Aust. Meteor. Oceanogr. J., 65, 1953, https://doi.org/10.22499/2.6501.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mori, M., and et al. , 2013: Hindcast prediction and near-future projection of tropical cyclone activity over the western North Pacific using CMIP5 near-term experiments with MIROC. J. Meteor. Soc. Japan, 91, 431452, https://doi.org/10.2151/jmsj.2013-402.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murakami, H., B. Wang, and A. Kitoh, 2011: Future change of western North Pacific typhoons: Projections by a 20-km-mesh global atmospheric model. J. Climate, 24, 11541169, https://doi.org/10.1175/2010JCLI3723.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murakami, H., R. Mizuta, and E. Shindo, 2012a: Future changes in tropical cyclone activity projected by multi-physics and multi-SST ensemble experiments using the 60-km-mesh MRI-AGCM. Climate Dyn., 39, 25692584, https://doi.org/10.1007/s00382-011-1223-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murakami, H., and et al. , 2012b: Future changes in tropical cyclone activity projected by the new high-resolution MRI-AGCM. J. Climate, 25, 32373260, https://doi.org/10.1175/JCLI-D-11-00415.1.

    • Crossref
    • 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, https://doi.org/10.1175/JCLI-D-15-0216.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nakamura, J., and et al. , 2017: Western North Pacific tropical cyclone model tracks in present and future climates. J. Geophys. Res. Atmos., 122, 97219744, https://doi.org/10.1002/2017JD02700.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Okubo, A., 1970: Horizontal dispersion of floatable particles in the vicinity of velocity singularities such as convergences. Deep-Sea Res., 17, 445454, https://doi.org/10.1016/0011-7471(70)90059-8.

    • Search Google Scholar
    • Export Citation
  • Park, D.-S. R., C.-H. Ho, J. C. L. Chan, K.-J. Ha, H.-S. Kim, J. Kim, and J.-H. Kim, 2017: Asymmetric response of tropical cyclone activity to global warming over the North Atlantic and western North Pacific from CMIP5 model projections. Sci. Rep., 7, 41354, https://doi.org/10.1038/srep41354.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Patricola, C. M., S. J. Camargo, P. J. Klotzbach, R. Saravanan, and P. Chang, 2018: The influence of ENSO flavors on western North Pacific tropical cyclone activity. J. Climate, 31, 53955416, https://doi.org/10.1175/JCLI-D-17-0678.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Riahi, K., and et al. , 2011: RCP 8.5—A scenario of comparatively high greenhouse gas emissions. Climatic Change, 109, 3357, https://doi.org/10.1007/s10584-011-0149-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sanderson, B., R. Knutti, and P. Caldwell, 2015: A representative democracy to reduce interdependency in a multimodel ensemble. J. Climate, 28, 51715194, https://doi.org/10.1175/JCLI-D-14-00362.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scoccimarro, E., and et al. , 2011: Effects of tropical cyclones on ocean heat transport in a high-resolution coupled general circulation model. J. Climate, 24, 43684384, https://doi.org/10.1175/2011JCLI4104.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shaevitz, D. A., and et al. , 2014: Characteristics of tropical cyclones in high-resolution models of the present climate. J. Adv. Model. Earth Syst., 6, 11541172, https://doi.org/10.1002/2014MS000372.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stowasser, M., Y. Wang, and K. Hamilton, 2007: Tropical cyclone changes in the western North Pacific in a global warming scenario. J. Climate, 20, 23782396, https://doi.org/10.1175/JCLI4126.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Strachan, J., P. L. Vidale, K. Hodges, M. Roberts, and M.-E. Demory, 2013: Investigating global tropical cyclone activity with a hierarchy of AGCMs: The role of model resolution. J. Climate, 26, 133152, https://doi.org/10.1175/JCLI-D-12-00012.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sugi, M., H. Murakami, and J. Yoshimura, 2009: A reduction in global tropical cyclone frequency due to global warming. SOLA, 5, 164167, https://doi.org/10.2151/SOLA.2009-042.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, https://doi.org/10.1175/BAMS-D-11-00094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tory, K. J., and R. A. Dare, 2015: Sea surface temperature thresholds for tropical cyclone formation. J. Climate, 28, 81718183, https://doi.org/10.1175/JCLI-D-14-00637.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tory, K. J., R. A. Dare, N. E. Davidson, J. L. McBride, and S. S. Chand, 2013a: The importance of low-deformation vorticity in tropical cyclone formation. Atmos. Chem. Phys., 13, 21152132, https://doi.org/10.5194/acp-13-2115-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tory, K. J., S. S. Chand, R. A. Dare, and J. L. McBride, 2013b: The development and assessment of a model-, grid-, and basin independent tropical cyclone detection scheme. J. Climate, 26, 54935507, https://doi.org/10.1175/JCLI-D-12-00510.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tory, K. J., S. S. Chand, J. L. McBride, H. Ye, and R. A. Dare, 2013c: Projected changes in late-twenty-first-century tropical cyclone frequency in 13 coupled climate models from phase 5 of the Coupled Model Intercomparison Project. J. Climate, 26, 99469959, https://doi.org/10.1175/JCLI-D-13-00010.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tory, K. J., S. S. Chand, J. L. McBride, H. Ye, and R. A. Dare, 2014: Projected changes in late 21st century tropical cyclone frequency in CMIP5 models. Proc. 31st Conf. on Hurricanes and Tropical Meteorology, San Diego, CA, Amer. Meteor. Soc., 7C.4, https://ams.confex.com/ams/31Hurr/webprogram/Paper245100.html.

  • Tory, K. J., H. Ye, and R. A. Dare, 2018: Understanding the geographic distribution of tropical cyclone formation for applications in climate models. Climate Dyn., 50, 24892512, https://doi.org/10.1007/s00382-017-3752-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tsou, C.-H., P.-Y. Huang, C.-Y. Tu, C.-T. Chen, T.-P. Tzeng, and C. T. Cheng, 2016: Present simulation and future typhoon activity projection over western North Pacific and Taiwan/east coast of China in 20-km HiRAM climate model. Terr. Atmos. Oceanic Sci., 27, 687703, https://doi.org/10.3319/TAO.2016.06.13.04.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Vuuren, D. P., and et al. , 2011: The representative concentration pathways: An overview. Climatic Change, 109, 531, https://doi.org/10.1007/s10584-011-0148-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vecchi, G. A., S. Fueglistaler, I. M. Held, T. R. Knutson, and M. Zhao, 2013: Impacts of atmospheric temperature trends on tropical cyclone activity. J. Climate, 26, 38773891, https://doi.org/10.1175/JCLI-D-12-00503.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vecchi, G. A., and et al. , 2014: On the seasonal forecasting of regional tropical cyclone activity. J. Climate, 27, 79948016, https://doi.org/10.1175/JCLI-D-14-00158.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voldoire, A., and et al. , 2013: The CNRM-CM5.1 global climate model: Description and basic evaluation. Climate Dyn., 40, 20912121, https://doi.org/10.1007/s00382-011-1259-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Walsh, K. J. E., M. Fiorino, C. W. Landsea, and K. L. McInnes, 2007: Objectively determined resolution-dependent threshold criteria for the detection of tropical cyclones in climate models and reanalyses. J. Climate, 20, 23072314, https://doi.org/10.1175/JCLI4074.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Walsh, K. J. E., S. Lavender, E. Scoccimarro, and H. Murakami, 2013: Resolution dependence of tropical cyclone formation in CMIP3 and finer resolution models. Climate Dyn., 40, 585599, https://doi.org/10.1007/s00382-012-1298-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., and L. Wu, 2015: Influence of future tropical cyclone track changes on their basin-wide intensity over the western North Pacific: Downscaled CMIP5 projections. Adv. Atmos. Sci., 32, 613623, https://doi.org/10.1007/s00376-014-4105-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, R., L. Wu, and C. Wang, 2011: Typhoon track changes associated with global warming. J. Climate, 24, 37483752, https://doi.org/10.1175/JCLI-D-11-00074.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and et al. , 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 63126335, https://doi.org/10.1175/2010JCLI3679.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wehner, M., Prabhat, K. A. Reed, D. Stone, W. D. Collins, and J. Bacmeister, 2015: Resolution dependence of future tropical cyclone projections of CAM5.1 in the U.S. CLIVAR Hurricane Working Group idealized configurations. J. Climate, 28, 39053925, https://doi.org/10.1175/JCLI-D-14-00311.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weiss, J., 1991: The dynamics of enstrophy transfer in two-dimensional hydrodynamics. Physica D, 48, 273294, https://doi.org/10.1016/0167-2789(91)90088-Q.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, M. C., W. L. Chang, and W. M. Leung, 2004: Impacts of El Niño–Southern Oscillation events on tropical cyclone landfalling activity in the western North Pacific. J. Climate, 17, 14191428, https://doi.org/10.1175/1520-0442(2004)017<1419:IOENOE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, T., and et al. , 2014: An overview of BCC climate system model development and application for climate change studies. J. Meteor. Res., 28, 3456, http://dx.doi.org/10.1007/S13351-014-3041-7.

    • Search Google Scholar
    • Export Citation
  • Yokoi, S., Y. N. Takayabu, and H. Murakami, 2013: Attribution of projected future changes in tropical cyclone passage frequency over the western North Pacific. J. Climate, 26, 40964111, https://doi.org/10.1175/JCLI-D-12-00218.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zarzycki, C. M., and P. A. Ullrich, 2017: Assessing sensitivities in algorithmic detection of tropical cyclones in climate data. Geophys. Res. Lett., 44, 11411149, https://doi.org/10.1002/2016GL071606.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, W., G. A. Vecchi, G. Villarini, H. Murakami, R. Gudgel, and X. Yang, 2017: Statistical–dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the GFDL FLOR coupled climate model. J. Climate, 30, 22092232, https://doi.org/10.1175/JCLI-D-16-0487.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, W.-Q., L.-G. Wu, and X.-K. Zou, 2018: Changes of tropical cyclone tracks in the western North Pacific over 1979–2016. Adv. Climate Change Res., 9, 170176, https://doi.org/10.1016/J.ACCRE.2018.06.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, M., I. M. Held, S.-J. Lin, and G. A. Vecchi, 2009: Simulations of global hurricane climatology, interannual variability, and response to global warming using a 50-km resolution GCM. J. Climate, 22, 66536678, https://doi.org/10.1175/2009JCLI3049.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Western North Pacific Tropical Cyclone Tracks in CMIP5 Models: Statistical Assessment Using a Model-Independent Detection and Tracking Scheme

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  • 1 Centre for Informatics and Applied Optimization, Federation University Australia, Ballarat, Australia
  • | 2 Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York
  • | 3 Research and Development Branch, Bureau of Meteorology, Melbourne, Australia
  • | 4 Centre for Informatics and Applied Optimization, Federation University Australia, Ballarat, Australia
  • | 5 Research and Development Branch, Bureau of Meteorology, Melbourne, Australia
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Abstract

Past studies have shown that tropical cyclone (TC) projection results can be sensitive to different types of TC tracking schemes, and that the relative adjustments of detection criteria to accommodate different models may not necessarily provide a consistent platform for comparison of projection results. Here, future climate projections of TC activity in the western North Pacific basin (WNP, defined from 0°–50°N and 100°E–180°) are assessed with a model-independent detection and tracking scheme. This scheme is applied to models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) forced under the historical and representative concentration pathway 8.5 (RCP8.5) conditions. TC tracks from the observed records and independent models are analyzed simultaneously with a curve-clustering algorithm, allowing observed and model tracks to be projected onto the same set of clusters (k = 9). Four of the nine clusters were projected to undergo significant changes in TC frequency. Straight-moving TCs in the South China Sea were projected to significantly decrease. Projected increases in TC frequency were found poleward of 20°N and east of 160°E, consistent with changes in ascending motion, as well as vertical wind shear and relative humidity respectively. Projections of TC track exposure indicated significant reductions for southern China and the Philippines and significant increases for the Korean peninsula and Japan, although very few model TCs reached the latter subtropical regions in comparison to the observations. The use of a fundamentally different detection methodology that overcomes the detector/tracker bias gives increased certainty to projections as best as low-resolution simulations can offer.

© 2019 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: Samuel S. Bell, ss.bell@federation.edu.au

Abstract

Past studies have shown that tropical cyclone (TC) projection results can be sensitive to different types of TC tracking schemes, and that the relative adjustments of detection criteria to accommodate different models may not necessarily provide a consistent platform for comparison of projection results. Here, future climate projections of TC activity in the western North Pacific basin (WNP, defined from 0°–50°N and 100°E–180°) are assessed with a model-independent detection and tracking scheme. This scheme is applied to models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) forced under the historical and representative concentration pathway 8.5 (RCP8.5) conditions. TC tracks from the observed records and independent models are analyzed simultaneously with a curve-clustering algorithm, allowing observed and model tracks to be projected onto the same set of clusters (k = 9). Four of the nine clusters were projected to undergo significant changes in TC frequency. Straight-moving TCs in the South China Sea were projected to significantly decrease. Projected increases in TC frequency were found poleward of 20°N and east of 160°E, consistent with changes in ascending motion, as well as vertical wind shear and relative humidity respectively. Projections of TC track exposure indicated significant reductions for southern China and the Philippines and significant increases for the Korean peninsula and Japan, although very few model TCs reached the latter subtropical regions in comparison to the observations. The use of a fundamentally different detection methodology that overcomes the detector/tracker bias gives increased certainty to projections as best as low-resolution simulations can offer.

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Corresponding author: Samuel S. Bell, ss.bell@federation.edu.au
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