Editorial Type:
Article
Article Type:
Research Article

Atlantic Basin Seasonal Hurricane Simulations

T. E. LaRow Center for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, Florida

Search for other papers by T. E. LaRow in
Current site
Google Scholar
PubMed Close
,
Y-K. Lim Center for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, Florida

Search for other papers by Y-K. Lim in
Current site
Google Scholar
PubMed Close
,
D. W. Shin Center for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, Florida

Search for other papers by D. W. Shin in
Current site
Google Scholar
PubMed Close
,
E. P. Chassignet Center for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, Florida

Search for other papers by E. P. Chassignet in
Current site
Google Scholar
PubMed Close
, and
S. Cocke Center for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, Florida

Search for other papers by S. Cocke in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jul 2008
DOI:
https://doi.org/10.1175/2007JCLI2036.1
Page(s):
3191–3206
Restricted access

Abstract

An ensemble of seasonal Atlantic hurricane simulations is conducted using The Florida State University/Center for Ocean–Atmospheric Prediction Studies (FSU–COAPS) global spectral model (Cocke and LaRow) at a resolution of T126L27 (a Gaussian grid spacing of 0.94°). Four integrations comprising the ensembles were generated using the European Centre for Medium-Range Weather Forecasts (ECMWF) time-lagged initial atmospheric conditions centered on 1 June for the 20 yr from 1986 to 2005. The sea surface temperatures (SSTs) were updated weekly using the Reynolds et al. observed data. An objective-tracking algorithm obtained from the ECMWF and modified for this model’s resolution was used to detect and track the storms. It was found that the model’s composite storm structure and track lengths are realistic. In addition, the 20-yr interannual variability was well simulated by the ensembles with a 0.78 ensemble mean rank correlation. The ensembles tend to overestimate (underestimate) the numbers of storms during July (September) and produced only one CAT4–level storm on the Saffir–Simpson scale. Similar problems are noted in other global model simulations. All ensembles did well in simulating the large number of storms forming in the Atlantic basin during 1995 and showed an increase in the number of storms during La Niña and a decrease during El Niño events. The results are found to be sensitive to the choices of convection schemes and diffusion coefficients. The overall conclusion is that models such as the one used here are needed to better hindcast the interannual variability; however, going to an even higher resolution does not guarantee better interannual variability, tracks, or intensity. Improved physical parameterizations, such as using an explicit convection scheme and better representation of surface roughness at high wind speeds, are likely to more accurately represent hurricane intensity.

Corresponding author address: T. E. LaRow, Center for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, FL 32306-2840. Email: tlarow@coaps.fsu.edu

Abstract

An ensemble of seasonal Atlantic hurricane simulations is conducted using The Florida State University/Center for Ocean–Atmospheric Prediction Studies (FSU–COAPS) global spectral model (Cocke and LaRow) at a resolution of T126L27 (a Gaussian grid spacing of 0.94°). Four integrations comprising the ensembles were generated using the European Centre for Medium-Range Weather Forecasts (ECMWF) time-lagged initial atmospheric conditions centered on 1 June for the 20 yr from 1986 to 2005. The sea surface temperatures (SSTs) were updated weekly using the Reynolds et al. observed data. An objective-tracking algorithm obtained from the ECMWF and modified for this model’s resolution was used to detect and track the storms. It was found that the model’s composite storm structure and track lengths are realistic. In addition, the 20-yr interannual variability was well simulated by the ensembles with a 0.78 ensemble mean rank correlation. The ensembles tend to overestimate (underestimate) the numbers of storms during July (September) and produced only one CAT4–level storm on the Saffir–Simpson scale. Similar problems are noted in other global model simulations. All ensembles did well in simulating the large number of storms forming in the Atlantic basin during 1995 and showed an increase in the number of storms during La Niña and a decrease during El Niño events. The results are found to be sensitive to the choices of convection schemes and diffusion coefficients. The overall conclusion is that models such as the one used here are needed to better hindcast the interannual variability; however, going to an even higher resolution does not guarantee better interannual variability, tracks, or intensity. Improved physical parameterizations, such as using an explicit convection scheme and better representation of surface roughness at high wind speeds, are likely to more accurately represent hurricane intensity.

Corresponding author address: T. E. LaRow, Center for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, FL 32306-2840. Email: tlarow@coaps.fsu.edu

Save
Cover Journal of Climate
Journal of Climate

  • Atlas, R., and Coauthors, 2005: Hurricane forecasting with the high-resolution NASA finite volume general circulation model. Geophys. Res. Lett., 32 .L03807, doi:10.1029/2004GL021513.

    • Search Google Scholar
    • Export Citation

  • Bengtsson, L., H. Bottger, and M. Kanamitsu, 1982: Simulation of hurricane-type vortices in a general circulation model. Tellus, 34 , 440–457.

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

    • Search Google Scholar
    • Export Citation

  • Bengtsson, L., K. I. Hodges, M. Esch, N. Keenlyside, L. Kornblueh, J-J. Luo, and T. Yamagata, 2007b: How may tropical cyclones change in a warmer climate? Tellus, 59A , 539–561.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Camargo, S. J., and S. Zebiak, 2002: Improving the detection and tracking of tropical storms in atmospheric general circulation models. Wea. Forecasting, 17 , 1152–1162.

    • Search Google Scholar
    • Export Citation

  • Camargo, S. J., A. Barnston, and S. Zebiak, 2005: A statistical assessment of tropical cyclone activity in atmospheric general circulation models. Tellus, 57A , 589–604.

    • Search Google Scholar
    • Export Citation

  • Camargo, S. J., H. Li, and L. Sun, 2007: Feasibility study for downscaling seasonal tropical cyclone activity using the NCEP regional spectral model. Int. J. Climatol., 27 , 311–325.

    • Search Google Scholar
    • Export Citation

  • Chauvin, F., J-F. Royer, and M. Déqué, 2006: Response of hurricane-type vortices to global warming as simulated by ARPEGE-Climat at high resolution. Climate Dyn., 27 , 377–399.

    • Search Google Scholar
    • Export Citation

  • Cocke, S. D., and T. E. LaRow, 2000: Seasonal predictions using a regional spectral model embedded within a coupled ocean–atmosphere model. Mon. Wea. Rev., 128 , 689–708.

    • Search Google Scholar
    • Export Citation

  • Evans, J. L., 1992: Comment on “Can existing climate models be used to study anthropogenic changes in tropical cyclone climate?”. Geophys. Res. Lett., 19 , 1523–1524.

    • Search Google Scholar
    • Export Citation

  • 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 Meteor. Soc., 155–218.

    • Search Google Scholar
    • Export Citation

  • 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

  • Gray, W. M., C. W. Landsea, P. W. Mielke Jr., and K. J. Berry, 1992: Predicting Atlantic seasonal hurricane activity 6–11 months in advance. Wea. Forecasting, 7 , 440–455.

    • Search Google Scholar
    • Export Citation

  • Gray, W. M., C. W. Landsea, P. W. Mielke Jr., and K. J. Berry, 1993: Predicting Atlantic basin seasonal tropical cyclone activity by 1 August. Wea. Forecasting, 8 , 73–86.

    • Search Google Scholar
    • Export Citation

  • Gray, W. M., C. W. Landsea, P. W. Mielke Jr., and K. J. Berry, 1994: Predicting Atlantic basin seasonal tropical cyclone activity by 1 June. Wea. Forecasting, 9 , 103–115.

    • Search Google Scholar
    • Export Citation

  • Haarsma, R. J., J. F. B. Mitchell, and C. A. Senior, 1993: Tropical disturbances in a GCM. Climate Dyn., 8 , 247–257.

  • Hess, J. C., J. B. Elsner, and N. E. LaSeur, 1995: Improving seasonal hurricane predictions for the Atlantic basin. Wea. Forecasting, 10 , 425–432.

    • Search Google Scholar
    • Export Citation

  • Hogan, T. F., and T. E. Rosmond, 1991: The description of the Navy Operational Global Atmospheric Prediction System’s spectral forecast model. Mon. Wea. Rev., 119 , 1786–1815.

    • Search Google Scholar
    • Export Citation

  • Knutson, T. R., J. Sirutis, S. Garner, I. Held, and R. Tuleya, 2007: Simulation of the recent multidecadal increase of Atlantic hurricane activity using an 18-km-grid regional model. Bull. Amer. Meteor. Soc., 88 , 1549–1565.

    • Search Google Scholar
    • Export Citation

  • LaRow, T. E., and T. N. Krishnamurti, 1998: Initial conditions and ENSO prediction using a coupled ocean–atmosphere model. Tellus, 50A , 76–94.

    • Search Google Scholar
    • Export Citation

  • Lighthill, J., G. Holland, W. Gray, C. Landsea, G. Graig, J. Evans, Y. Kurihara, and C. Guard, 1994: Global climate change and tropical cyclones. Bull. Amer. Meteor. Soc., 75 , 2147–2157.

    • 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

  • McDonald, R. E., D. G. Bleaken, D. R. Cresswell, V. D. Pope, and C. A. Senior, 2005: Tropical stroms: Representation and diagnosis in climate models and the impacts of climate change. Climate Dyn., 25 , 19–36.

    • 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 analyses. J. Meteor. Soc. Japan, 84 , 259–276.

    • Search Google Scholar
    • Export Citation

  • Pan, H-L., and W-S. Wu, 1994: Implementing a mass-flux convective parameterization package for the NMC Medium-Range Forecast Model. Preprints, 10th Conf. on Numerical Weather Prediction, Portland, OR, Amer. Meteor. Soc., 96–98.

  • 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 , 1609–1625.

    • Search Google Scholar
    • Export Citation

  • Ryan, B. F., I. G. Watterson, and J. L. Evans, 1992: Tropical cyclone frequencies inferred from Gray’s yearly genesis parameter: Validation of GCM tropical climates. Geophys. Res. Lett., 19 , 1831–1834.

    • Search Google Scholar
    • Export Citation

  • Saunders, M. A., and A. R. Harris, 1997: Statistical evidence links exceptional 1995 Atlantic hurricane season to record sea warming. Geophys. Res. Lett., 24 , 1255–1258.

    • Search Google Scholar
    • Export Citation

  • Shapiro, L. J., 1987: Month-to-month variability of the Atlantic tropical circulation and its relationship to tropical storm formation. Mon. Wea. Rev., 115 , 2598–2614.

    • Search Google Scholar
    • Export Citation

  • Thorncroft, C., and I. Pytharoulis, 2001: A dynamical approach to seasonal prediction of Atlantic tropical cyclone activity. Wea. Forecasting, 16 , 725–734.

    • Search Google Scholar
    • Export Citation

  • Vitart, F., 2006: Seasonal forecasting of tropical storm frequency using a multi-model ensemble. Quart. J. Roy. Meteor. Soc., 132 , 647–666.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Vitart, F., J. L. Anderson, and W. F. Stern, 1997: Simulation of interannual variability of tropical storm frequency in an ensemble of GCM integrations. J. Climate, 10 , 745–760.

    • Search Google Scholar
    • Export Citation

  • Vitart, F., J. L. Anderson, J. Sirutis, and R. E. Tuleya, 2001: Sensitivity of tropical storms simulated by a general circulation model to changes in cumulus parameterization. Quart. J. Roy. Meteor. Soc., 127 , 25–51.

    • Search Google Scholar
    • Export Citation

  • Vitart, F., D. Anderson, and T. Stockdale, 2003: Seasonal forecasting of tropical cyclone landfall over Mozambique. J. Climate, 16 , 3932–3945.

    • Search Google Scholar
    • Export Citation

  • Vitart, F., and Coauthors, 2007: Dynamically-based seasonal forecasts of Atlantic tropical storms activity issued in June by EUROSIP. Geophys. Res. Lett., 34 .L16815, doi:10.1029/2007GL030740.

    • 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 , 2307–2314.

    • Search Google Scholar
    • Export Citation

  • Watterson, I. G., J. L. Evans, and B. F. Ryan, 1995: Seasonal and interannual variability of tropical cyclogenesis: Diagnostics from large-scale fields. J. Climate, 8 , 3042–3066.

    • Search Google Scholar
    • Export Citation

  • Wu, G., and N-C. Lau, 1992: A GCM simulation of the relationship between tropical-storm formation and ENSO. Mon. Wea. Rev., 120 , 958–977.

    • Search Google Scholar
    • Export Citation

  • Zhang, G. J., and N. A. McFarlane, 1995: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmos.–Ocean, 33 , 407–446.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 314 108 5
PDF Downloads 120 43 3