Tropical cyclones in a T159 resolution global climate model: comparison with observations and re-analyses

References

• Bender, M. A. and Ginis, I. 2000. Real case simulations of hurricane-ocean interaction using a high resolution coupled model: Effects on hurricane intensity. Mon. Wea. Re v. 126, 917–946.
   Web of Science ®Google Scholar
• Bengtsson, L., Botzet, M. and Esch, M. 1995. Hurricane-type vortices in a general circulation model. Tellus 47A, 175–196.
   Google Scholar
• Bengtsson, L., Botzet, M. and Esch, M. 1996. Will greenhouse gas-induced warming over the next 50 yr lead to higher frequency and greater intensity of hurricanes?. Tellus 48A, 57–73.
   Google Scholar
• Bengtsson, L., Botzet, M. and Esch, M. 1997. Numerical simulations of intense tropical storms. In: Hurricanes (eds H. E Diaz). R. S. Pulwarty Springer-Verlag, Berlin 1997, 67–90.
   Google Scholar
• Bengtsson, L., Hodges, K. I. and Roeckner, E. 2006. Storm tracks and climate change. J. Clim. V19, 3518–3543.
   Web of Science ®Google Scholar
• Bengtsson, L., Hodges, K. I., Esch, M., Keenlyside, N., Komblush, L., Luo, J. J., and Yamagata, T. 2007. How many tropical cyclones change in a warmer climate. Tellus, in press.
   Google Scholar
• Bister, M. and Emanuel, K. 1998. Dissipative heating and hurricane intensity. Meteorol. Atmos. Phys. 50, 233–240.
   Web of Science ®Google Scholar
• Broccoli, A. J. and Manabe, S. 1990. Can existing climate models be used to study anthropogenic changes in tropical cyclone climate?. Geophys. Res. Lett. 17, 1917–1920.
   Web of Science ®Google Scholar
• Camargo, S. J. and Zebiak, S. E. 2002. Improving the detection and tracking of tropical cyclones in atmospheric general circulation models. Wea. Forecast. 17, 1152–1162.
   Web of Science ®Google Scholar
• Chan, J. C. L. 2006. Comment on ‘Changes in Tropical Cyclone Number, Duration and Intensity in a Warming Environment’. Science 311, 1713.
   PubMed Web of Science ®Google Scholar
• Chauvin, F., Royer, J.-F. and Deque, M. 2006. Response of hurricane-type vortices to global warming as simulated by ARPEGE-Climat at high resolution. Clim. Dyn. 27, 377–399.
   Web of Science ®Google Scholar
• DeMaria, M., Mainelli, M., Shay, L. K., Knaff, J. A. and Kaplan, J. 2005. Further improvement to the statistical hurricane intensity prediction scheme (SHIPS). Weather Forecas. 20, 531–543.
   Web of Science ®Google Scholar
• Elsner, J. B., Tsonis, A. A. and Jagger, T. J. 2006. High-frequency variability in hurricane power dissipation and its relationship to global temperature. Bull. Am. Meteorol. Soc. 87, 763–768.
   Web of Science ®Google Scholar
• Emanuel, K. 2005. Increasing destructiveness of tropical cyclones over the past 30 yr. Nature 436, 686–688.
   PubMed Web of Science ®Google Scholar
• Fiorino, M. 2002. Analysis and forecasts of tropical cyclones in the ECMWF 40-yr re-analysis, extended abstract for paper presented at 25th Conference on Hurricanes and Tropical Meteorology, Am. Mete-orol. Soc., San Diego, Calif. 29 April-3 May.
   Google Scholar
• Haarsma, R. J., Mitchell, J. F. B. and Senior, C. A. 1993. Tropical disturbances in a GCM. Clim. Dyn. 8, 247–257.
   Web of Science ®Google Scholar
• Hatsushilca, H., Tsutsui, J., Fiorino, M. and Onogi, K. 2006. Impact of wind retrievals on the analysis of tropical cyclones in the JRA-25 Re-analysis. J. Meteorol. Soc. Japan 84, 891–905.
   Web of Science ®Google Scholar
• Henderson-Sellers, A., Zhang, H., Berz, G., Emanuel, K., Gray, W., and co-authors. 1998. Tropical cyclones and global climate change: a post-IPCC assessment. Bull. Am. Meteorol. Soc. 79, 19-38.
   Google Scholar
• Hodges, K. I. 1996. Spherical nonparameteric estimators applied to the UGAMP model integration for AMIP. Mon. Weather Re v. V124, 2914–2932.
   Web of Science ®Google Scholar
• Hodges, K. I., Hoskins, B. J., Boyle, J. and Thorncroft, C. 2003. A comparison of recent re-analysis datasets using objective feature tracking: storm tracks and tropical easterly waves. Mon. Weather Re v. V131, 2012–2037.
   Web of Science ®Google Scholar
• Klotzbach, P. J. 2006. Trends in global tropical cyclone activity over the past twenty years (1986-2005), 2006. Geophys. Res. Lett. 33, doi: 10.1029/2006GL025881.
   Google Scholar
• Krishnamurti, T. N., Pattnaik, S., Stefanova, L., Vijaya Kumar, T. S. V., Mackey, B. P., and co-authors. 2005. The Hurricane Intensity Issue. Mon. Wea. Rev. 133, 1886–1912.
   Web of Science ®Google Scholar
• Knutson, T. K. and Tuleya, R. E. 2004. Impact of CO2-induced warming on simulated hurricane intensity and precipitation: Sensitivity to the choice of climate model and convective parameterization. J. Clim. 17, 3477–3495.
   Web of Science ®Google Scholar
• Landsea, C. W. 2000. El Nino/Southern oscillation and the seasonal predictability of Tropical Cyclones. In: El Niiio and the Southern Oscillation: Multiscale Variability and Global and Regional Impacts (eds H. E Diaz and V. Markgraf). Cambridge University Press, 149-181.
   Google Scholar
• Nakicenovic, N., and co-authors. 2000. Special Report on Emissions Scenarios. Cambridge University Press, 599 pp.
   Google Scholar
• Ohfuchi, W., Nakamura, H., Yoshioka, M., Enomoto, T., Talcaya, K., and co-authors. 2004.10-km mesh meso-scale resolving global simulations of the atmosphere on the Earth Simulator – Preliminary out-comes of AFES (AGCM for the Earth Simulator). J. Earth Simulator 1, 8-34.
   Google Scholar
• van Oldenborgh, G. J., Philip, S. and Collins, M. 2005. El Nino in a changing climate: A multimodel study. Ocean Sci. Discuss. 2, 267-298.
   Google Scholar
• Onogi, K., Koide, H., Salcamoto, M., Kobayashi, S., Tsutsui, J., and co-authors. 2005. JRA-25: Japanese 25-yr re-anlysis project-progress and status. Meteorol, Q. J. R. Soc. 131, 3259-3268.
   Google Scholar
• Oouchi, K., Yoshimura, J.,Yoshimura, H., Mizuta, R., and co-authors. 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. Meteorol. Soc. Japan 84, 259-276.
   Google Scholar
• Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., and co-authors. 2003. The atmospheric general circulation model ECHAM 5. PART I: Model description MPI-Report 349,127 pp.
   Google Scholar
• Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kornblueh, L., and co-authors. 2006. Sensitivity of simulated climate to horizontal and vertical resolution in the echam5 atmospheric model. J. Clim. 19, 3771-3791.
   Google Scholar
• Shen, B.-W., Atlas, R., Chern, J.-D., Reale, O., Lin, S.-J., and co-authors. 2006a. The 0.125 degree finite-volume general circulation model on the NASA Columbia supercomputer: Preliminary simulations of mesoscale vortices. Geophys. Res. Lett. 33, doi: 10.1029/2005GL024594.
   Google Scholar
• Shen, B.-W., Atlas, R., Reale, O., Lin, S.-J., Chern, J.-D., and co-authors. 2006b. Hurricane forecasts with a global mesoscale-resolving model: Preliminary results with Hurricane Katrina (2005). Geophys. Res. Lett. 33, doi: 10.1029/2006GL026143.
   Google Scholar
• Sriver, R. and Huber, M. 2006. Low-frequency variability in globally integrated tropical cyclone power dissipation. Geo. Phys. Res. Letters 33, 11705–11710, doi: 10.1029/2006GL026167.
   Web of Science ®Google Scholar
• Sugi, M., Noda, A. and Sato, N. 2002. Influence of the global warming on tropical cyclone climatology: An experiment with the JMA global model. J. Meteorol. Soc. Japan 80, 249–272.
   Web of Science ®Google Scholar
• Thorncroft, C. and Hodges, K. 2001. African easterly wave variability and its relationship to atlantic tropical cyclone activity. J. Clim. V14, 1166–1179.
   Web of Science ®Google Scholar
• Uppala, S. M., Milberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. Da Costa, and co-authors. The ERA40 re-analysis. Q. J. R. Meteorol. Soc. 131, 2961-3012.
   Google Scholar
• Webster, P. J., Holland, G. J., Curry, J. A. and Chang, H. R. 2005. Changes in tropical cyclone number, duration and intensity in a warming environment. Science 309, 1844–1846.
   PubMed Web of Science ®Google Scholar
• WGNE, 1996. AMIP II guidelines. Atmospheric Model Intercomparison Project Newsletter, No. 8, AMIP Project Office, Livermore, CA, 24 pp. [Available from AMIP Project Office, PCMDI, L-264, LLNL, P.O. Box 808, Livermore, CA 945501
   Google Scholar
• Wu, G. and Lau, N.-C. 1992. A GCM simulation of the relationship between tropical-storm formation and ENSO. Mon. Wea. Re v. 120, 958–977.
   Web of Science ®Google Scholar