Editorial Type:
Article
Article Type:
Research Article

Investigating Global Tropical Cyclone Activity with a Hierarchy of AGCMs: The Role of Model Resolution

Jane Strachan National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, United Kingdom

Search for other papers by Jane Strachan in
Current site
Google Scholar
PubMed Close
,
Pier Luigi Vidale National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, United Kingdom

Search for other papers by Pier Luigi Vidale in
Current site
Google Scholar
PubMed Close
,
Kevin Hodges NERC Centre for Earth Observation, University of Reading, Reading, United Kingdom

Search for other papers by Kevin Hodges in
Current site
Google Scholar
PubMed Close
,
Malcolm Roberts Met Office, Hadley Centre, Exeter, United Kingdom

Search for other papers by Malcolm Roberts in
Current site
Google Scholar
PubMed Close
, and
Marie-Estelle Demory National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, United Kingdom

Search for other papers by Marie-Estelle Demory in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jan 2013
DOI:
https://doi.org/10.1175/JCLI-D-12-00012.1
Page(s):
133–152
Restricted access

Abstract

The ability to run general circulation models (GCMs) at ever-higher horizontal resolutions has meant that tropical cyclone simulations are increasingly credible. A hierarchy of atmosphere-only GCMs, based on the Hadley Centre Global Environmental Model version 1 (HadGEM1) with horizontal resolution increasing from approximately 270 to 60 km at 50°N, is used to systematically investigate the impact of spatial resolution on the simulation of global tropical cyclone activity, independent of model formulation. Tropical cyclones are extracted from ensemble simulations and reanalyses of comparable resolutions using a feature-tracking algorithm. Resolution is critical for simulating storm intensity and convergence to observed storm intensities is not achieved with the model hierarchy. Resolution is less critical for simulating the annual number of tropical cyclones and their geographical distribution, which are well captured at resolutions of 135 km or higher, particularly for Northern Hemisphere basins. Simulating the interannual variability of storm occurrence requires resolutions of 100 km or higher; however, the level of skill is basin dependent. Higher resolution GCMs are increasingly able to capture the interannual variability of the large-scale environmental conditions that contribute to tropical cyclogenesis. Different environmental factors contribute to the interannual variability of tropical cyclones in the different basins: in the North Atlantic basin the vertical wind shear, potential intensity, and low-level absolute vorticity are dominant, whereas in the North Pacific basins midlevel relative humidity and low-level absolute vorticity are dominant. Model resolution is crucial for a realistic simulation of tropical cyclone behavior, and high-resolution GCMs are found to be valuable tools for investigating the global location and frequency of tropical cyclones.

Corresponding author address: Jane Strachan, National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading RG6 6BB, United Kingdom. E-mail: j.strachan@reading.ac.uk

Abstract

The ability to run general circulation models (GCMs) at ever-higher horizontal resolutions has meant that tropical cyclone simulations are increasingly credible. A hierarchy of atmosphere-only GCMs, based on the Hadley Centre Global Environmental Model version 1 (HadGEM1) with horizontal resolution increasing from approximately 270 to 60 km at 50°N, is used to systematically investigate the impact of spatial resolution on the simulation of global tropical cyclone activity, independent of model formulation. Tropical cyclones are extracted from ensemble simulations and reanalyses of comparable resolutions using a feature-tracking algorithm. Resolution is critical for simulating storm intensity and convergence to observed storm intensities is not achieved with the model hierarchy. Resolution is less critical for simulating the annual number of tropical cyclones and their geographical distribution, which are well captured at resolutions of 135 km or higher, particularly for Northern Hemisphere basins. Simulating the interannual variability of storm occurrence requires resolutions of 100 km or higher; however, the level of skill is basin dependent. Higher resolution GCMs are increasingly able to capture the interannual variability of the large-scale environmental conditions that contribute to tropical cyclogenesis. Different environmental factors contribute to the interannual variability of tropical cyclones in the different basins: in the North Atlantic basin the vertical wind shear, potential intensity, and low-level absolute vorticity are dominant, whereas in the North Pacific basins midlevel relative humidity and low-level absolute vorticity are dominant. Model resolution is crucial for a realistic simulation of tropical cyclone behavior, and high-resolution GCMs are found to be valuable tools for investigating the global location and frequency of tropical cyclones.

Corresponding author address: Jane Strachan, National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading RG6 6BB, United Kingdom. E-mail: j.strachan@reading.ac.uk
Save
Cover Journal of Climate
Journal of Climate

  • Aiyyer, A., and C. Thorncroft, 2011: Interannual-to-multidecadal variability of vertical wind shear and tropical cyclone activity. J. Climate, 24, 2949–2462.

    • 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, 917–946.

    • Search Google Scholar
    • Export Citation

  • Bengtsson, L., M. Botzet, and M. Esch, 1995: Hurricane-type vortices in a general circulation model. Tellus, 47A, 175–196.

  • Bengtsson, L., K. I. Hodges, and S. Hagemann, 2004: Sensitivity of large-scale atmospheric analyses to humidity observations and its impact on the global water cycle and tropical and extratropical weather systems in ERA40. Tellus, 56A, 202–217.

    • Search Google Scholar
    • Export Citation

  • Bengtsson, L., K. I. Hodges, and M. Esch, 2007: Tropical cyclones in a T159 resolution global climate model: Comparison with observations and re-analysis. Tellus, 59A, 396–416.

    • Search Google Scholar
    • Export Citation

  • Bister, M., and K. A. Emanuel, 1998: Dissipative heating and hurricane intensity. Meteor. Atmos. Phys., 52, 233–240.

  • Blender, R., and M. Schubert, 2000: Cyclone tracking in different spatial and temporal resolutions. Mon. Wea. Rev., 128, 377–384.

  • Broccoli, A. J., and S. Manabe, 1990: Can existing climate models be used to study anthropogenic changes in tropical cyclone climate? Geophys. Res. Lett., 17, 1917–1920.

    • Search Google Scholar
    • Export Citation

  • Camargo, S. J., and A. H. Sobel, 2005: Western North Pacific tropical cyclone intensity and ENSO. J. Climate, 18, 2996–3006.

  • Camargo, S. J., K. A. Emanuel, and A. H. Sobel, 2007: Use of a genesis potential index to diagnose ENSO effects on tropical cyclone genesis. J. Climate, 20, 4819–4834.

    • Search Google Scholar
    • Export Citation

  • Chan, J. C. L., and K. S. Liu, 2004: Global warming and western North Pacific typhoon activity from an observational perspective. J. Climate, 17, 4590–4602.

    • Search Google Scholar
    • Export Citation

  • Chia, H. H., and C. F. Ropelewski, 2002: The interannual variability of genesis location of tropical cyclones in the northwest Pacific. J. Climate, 15, 2934–2944.

    • Search Google Scholar
    • Export Citation

  • Emanuel, K. A., 1995: Sensitivity of tropical cyclones to surface exchange coefficients and a revised steady-state model incorporating eye dynamics. J. Atmos. Sci., 52, 3969–3976.

    • Search Google Scholar
    • Export Citation

  • Emanuel, K. A., 2008: The hurricane–climate connection. Bull. Amer. Meteor. Soc., 87, 299–314.

  • Emanuel, K. A., 2010: Stratospheric cooling and tropical cyclones. Preprints, 29th Conf. on Hurricanes and Tropical Meteorology, Tucson, AZ, Amer. Meteor. Soc., 4A.4. [Available online at http://ams.confex.com/ams/pdfpapers/168302.pdf.]

  • Emanuel, K. A., and D. S. Nolan, 2004: Tropical cyclone activity and global climate. Preprints, 26th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 240–241.

  • Evan, T. A., and S. J. Camargo, 2011: A climatology of Arabian Sea cyclonic storms. J. Climate, 24, 140–158.

  • Gentry, M. S., and G. M. Lackmann, 2010: Sensitivity of simulated tropical cyclone structure and intensity to horizontal resolution. Mon. Wea. Rev., 138, 688–704.

    • Search Google Scholar
    • Export Citation

  • Godbole, R. V., 1977: The composite structure of the monsoon depression. Tellus, 29, 25–40.

  • Gray, W. M., 1979: Hurricanes: Their formation, structure, and likely role in the tropical circulation. Meteorology over the Tropical Oceans, D. B. Shaw, Ed., Royal Meteorological Society, 155–218.

  • Gray, W. M., 1984: Atlantic seasonal hurricane frequency. Part I: El Niño and 30 mb quasi-biennial oscillation influences. Mon. Wea. Rev., 112, 1649–1668.

    • Search Google Scholar
    • Export Citation

  • Guilyardi, E., and Coauthors, 2004: Representing El Niño in coupled ocean–atmosphere GCMs: The dominant role of the atmospheric component. J. Climate, 17, 4623–4629.

    • Search Google Scholar
    • Export Citation

  • Haarsma, R. J., J. F. B. Mitchell, and C. A. Senior, 1992: Tropical disturbances in a GCM. Climate Dyn., 8, 247–257.

  • Henderson-Sellers, A., and Coauthors, 1998: Tropical cyclones and global climate change: A post-IPCC assessment. Bull. Amer. Meteor. Soc., 79, 19–38.

    • Search Google Scholar
    • Export Citation

  • Hodges, K. I., 1995: Feature tracking on a unit sphere. Mon. Wea. Rev., 123, 3458–3465.

  • Hodges, K. I., 1996: Spherical nonparametric estimators applied to the UGAMP model integration for AMIP. Mon. Wea. Rev., 124, 2914–2932.

    • Search Google Scholar
    • Export Citation

  • Hodges, K. I., 1999: Adaptive constraints for feature tracking. Mon. Wea. Rev., 127, 1362–1373.

  • Holland, G., and P. Webster, 2007: Heightened tropical cyclone activity in the North Atlantic: Natural variability or climate trend? Philos. Trans. Roy. Soc., 365, 2695–2716.

    • Search Google Scholar
    • Export Citation

  • Hoskins, B. J., and K. I. Hodges, 2002: New perspectives on the Northern Hemisphere winter storm tracks. J. Atmos. Sci., 59, 1041–1061.

    • Search Google Scholar
    • Export Citation

  • Johns, T. C., and Coauthors, 2006: The new Hadley Centre climate model (HadGEM1): Evaluation of coupled simulations. J. Climate, 19, 1327–1353.

    • Search Google Scholar
    • Export Citation

  • Knapp, K. R., M. C. Kruk, D. H. Levinson, H. J. Diamond, and C. J. Neumann, 2010: The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying tropical cyclone best track data. Bull. Amer. Meteor. Soc., 91, 363–376.

    • Search Google Scholar
    • Export Citation

  • Kobayashi, C., and M. Sugi, 2004: Impact of horizontal resolution on the simulation of the Asian summer monsoon and tropical cyclones in the JMA global model. Climate Dyn., 23, 165–176.

    • Search Google Scholar
    • Export Citation

  • Landsea, C. W., 1993: A climatology of intense (or major) Atlantic hurricanes. Mon. Wea. Rev., 121, 1703–1713.

  • Landsea, C. W., 2007: Counting Atlantic tropical cyclones back to 1900. Eos, Trans. Amer. Geophys. Union, 88, 197–208.

  • Landsea, C. W., B. A. Harper, K. Hoarau, and J. A. Knaff, 2006: Can we detect trends in extreme tropical cyclones? Science, 28, 452–454.

    • Search Google Scholar
    • Export Citation

  • LaRow, T. E., Y. K. Lim, D. W. Shin, E. P. Chassignet, and S. Cooke, 2008: Atlantic basin seasonal hurricane simulations. J. Climate, 21, 3191–3206.

    • Search Google Scholar
    • Export Citation

  • Manabe, S., J. L. Holloway, and H. M. Stone, 1970: Tropical circulation in a time-integration of a global model of the atmosphere. J. Atmos. Sci., 27, 580–613.

    • Search Google Scholar
    • Export Citation

  • Manganello, J. V., and Coauthors, 2012: Tropical cyclone climatology in a 10-km global atmospheric GCM: Toward weather-resolving climate modeling. J. Climate, 25, 3867–3893.

    • Search Google Scholar
    • Export Citation

  • Martin, G. M., M. A. Ringer, V. D. Pope, A. Jones, C. Dearden, and T. J. Hinton, 2006: The physical properties of the atmosphere in the new Hadley Centre Global Environmental Model (HadGEM1). Part I: Model description and global climatology. J. Climate, 19, 1274–1301.

    • Search Google Scholar
    • Export Citation

  • Murakami, H., and M. Sugi, 2010: Effect of model resolution on tropical cyclone climate projections. SOLA, 6, 73–76.

  • Murakami, H., and B. Wang, 2010: Future change of North Atlantic tropical cyclone tracks: Projection by a 20-km-mesh global atmospheric model. J. Climate, 23, 2699–2721.

    • Search Google Scholar
    • Export Citation

  • Oouchi, K., J. Yoshimura, H. Yoshimura, R. Mizuta, S. Kusunoki, and A. Noda, 2006: Tropical cyclone climatology in a global-warming climate as simulated in a 20 km-mesh global atmospheric model: Frequency and wind intensity analysis. J. Meteor. Soc. Japan, 84, 259–276.

    • Search Google Scholar
    • Export Citation

  • Pielke, R. A., Jr., and R. A. Pielke Sr., 1997: Hurricanes: Their Nature and Impacts on Society.Wiley, 279 pp.

  • Ren, F., J. Liang, G. Wu, W. Dong, and X. Yang, 2011: Reliability analysis of climate change of tropical cyclone activity over the western North Pacific. J. Climate, 24, 5887–5898.

    • Search Google Scholar
    • Export Citation

  • Rienecker, M. M., and Coauthors, 2011: MERRA: NASA’s modern-era retrospective analysis for research and applications. J. Climate, 24, 3624–3648.

    • Search Google Scholar
    • Export Citation

  • Ringer, M. A., and Coauthors, 2006: The physical properties of the atmosphere in the new Hadley Centre Global Environmental Model (HadGEM1). Part II: Aspects of variability and regional climate. J. Climate, 19, 1302–1326.

    • Search Google Scholar
    • Export Citation

  • Roberts, M. J., and Coauthors, 2009: Impact of resolution in the tropical Pacific circulation in a matrix of coupled models. J. Climate, 22, 2541–2556.

    • Search Google Scholar
    • Export Citation

  • Schade, L. R., and K. A. Emanuel, 1999: The ocean’s effect on the intensity of tropical cyclones: Results from a simple coupled atmosphere–ocean model. J. Atmos. Sci., 56, 642–651.

    • Search Google Scholar
    • Export Citation

  • Shaffrey, L. C., and Coauthors, 2009: U.K. HiGEM: The new U.K. high-resolution global environment model—model description and basic evaluation. J. Climate, 22, 1861–1896.

    • Search Google Scholar
    • Export Citation

  • Simmons, A., S. Uppala, D. Dee, and S. Kobayashi, 2007: ERA-Interim: New ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter, No. 110, ECMWF, Reading, United Kingdom, 25–35.

  • Solomon, S., D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. Tignor, H. L. Miller, Jr., and Z. Chen, Eds., 2007: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.

  • Southern, R., 1979: The global socio-economic impact of tropical cyclones. Aust. Meteor. Mag., 27, 175–195.

  • Taylor, K., D. Williamson, and F. Zwiers, 2000: The sea surface temperature and sea-ice concentration boundary conditions for AMIP II simulations. PCMDI Tech. Rep. 60, 28 pp.

  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 2961–3012.

  • Villarini, G., G. A. Vecchi, and J. A. Smith, 2010: Modeling the dependence of tropical storm counts in the North Atlantic basin on climate indices. Mon. Wea. Rev., 138, 2681–2705.

    • Search Google Scholar
    • Export Citation

  • Vitart, F., and T. N. Stockdale, 2001: Seasonal forecasting of tropical storms using coupled GCM integrations. Mon. Wea. Rev., 129, 2521–2537.

    • Search Google Scholar
    • Export Citation

  • Waliser, D. E., K. M. Lau, and J. H. Kim, 1999: The influence of coupled sea surface temperatures on the Madden–Julian oscillation: A model perturbation experiment. J. Atmos. Sci., 56, 333–358.

    • 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 reanalysis. J. Climate, 20, 2307–2314.

    • Search Google Scholar
    • Export Citation

  • Walsh, K. J. E., S. Lavender, E. Scoccimarro, and H. Murakami, 2012: Resolution dependence of tropical cyclone formation in CMIP3 and finer resolution models. Climate Dyn., doi:10.1007/s00382-012-1298-z, in press.

    • Search Google Scholar
    • Export Citation

  • Zehnder, J. A., D. M. Powell, and D. L. Ropp, 1999: The interaction of easterly waves, orography, and the intertropical convergence zone in the genesis of eastern Pacific tropical cyclones. Mon. Wea. Rev., 127, 1566–1585.

    • Search Google Scholar
    • Export Citation

  • Zhao, M., and I. M. Held, 2010: An analysis of the effect of global warming on the intensity of Atlantic hurricanes using a GCM with statistical refinement. J. Climate, 23, 6382–6393.

    • Search Google Scholar
    • Export Citation

  • Zhao, M., and I. M. Held, 2012: TC-permitting GCM simulations of hurricane frequency response to sea surface temperature anomalies projected for the late-twenty-first century. J. Climate, 25, 2995–3009.

    • 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, 6653–6678.

    • Search Google Scholar
    • Export Citation

  • Zhao, M., I. M. Held, and S.-J. Lin, 2012: Some counterintuitive dependencies of tropical cyclone frequency on parameters in a GCM. J. Atmos. Sci., 69, 2272–2283.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1422 421 40
PDF Downloads 999 215 20