Editorial Type:
Article
Article Type:
Research Article

The Ability of CMIP5 Models to Simulate North Atlantic Extratropical Cyclones

Giuseppe Zappa Department of Meteorology, and National Centre for Atmospheric Science, University of Reading, Reading, United Kingdom

Search for other papers by Giuseppe Zappa in
Current site
Google Scholar
PubMed Close
,
Len C. Shaffrey Department of Meteorology, and National Centre for Atmospheric Science, University of Reading, Reading, United Kingdom

Search for other papers by Len C. Shaffrey in
Current site
Google Scholar
PubMed Close
, and
Kevin I. Hodges National Centre for Earth Observation, University of Reading, Reading, United Kingdom

Search for other papers by Kevin I. Hodges in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Aug 2013
DOI:
https://doi.org/10.1175/JCLI-D-12-00501.1
Page(s):
5379–5396
Restricted access

Abstract

The ability of the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) to simulate North Atlantic extratropical cyclones in winter [December–February (DJF)] and summer [June–August (JJA)] is investigated in detail. Cyclones are identified as maxima in T42 vorticity at 850 hPa and their propagation is tracked using an objective feature-tracking algorithm. By comparing the historical CMIP5 simulations (1976–2005) and the ECMWF Interim Re-Analysis (ERA-Interim; 1979–2008), the authors find that systematic biases affect the number and intensity of North Atlantic cyclones in CMIP5 models. In DJF, the North Atlantic storm track tends to be either too zonal or displaced southward, thus leading to too few and weak cyclones over the Norwegian Sea and too many cyclones in central Europe. In JJA, the position of the North Atlantic storm track is generally well captured but some CMIP5 models underestimate the total number of cyclones. The dynamical intensity of cyclones, as measured by either T42 vorticity at 850 hPa or mean sea level pressure, is too weak in both DJF and JJA. The intensity bias has a hemispheric character, and it cannot be simply attributed to the representation of the North Atlantic large-scale atmospheric state. Despite these biases, the representation of Northern Hemisphere (NH) storm tracks has improved since CMIP3 and some CMIP5 models are able of representing well both the number and the intensity of North Atlantic cyclones. In particular, some of the higher-atmospheric-resolution models tend to have a better representation of the tilt of the North Atlantic storm track and of the intensity of cyclones in DJF.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-12-00501.s1.

Corresponding author address: Giuseppe Zappa, Department of Meteorology, University of Reading, Earley Gate, P.O. Box 243, Reading RG6 6BP, United Kingdom. E-mail: g.zappa@reading.ac.uk

Abstract

The ability of the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) to simulate North Atlantic extratropical cyclones in winter [December–February (DJF)] and summer [June–August (JJA)] is investigated in detail. Cyclones are identified as maxima in T42 vorticity at 850 hPa and their propagation is tracked using an objective feature-tracking algorithm. By comparing the historical CMIP5 simulations (1976–2005) and the ECMWF Interim Re-Analysis (ERA-Interim; 1979–2008), the authors find that systematic biases affect the number and intensity of North Atlantic cyclones in CMIP5 models. In DJF, the North Atlantic storm track tends to be either too zonal or displaced southward, thus leading to too few and weak cyclones over the Norwegian Sea and too many cyclones in central Europe. In JJA, the position of the North Atlantic storm track is generally well captured but some CMIP5 models underestimate the total number of cyclones. The dynamical intensity of cyclones, as measured by either T42 vorticity at 850 hPa or mean sea level pressure, is too weak in both DJF and JJA. The intensity bias has a hemispheric character, and it cannot be simply attributed to the representation of the North Atlantic large-scale atmospheric state. Despite these biases, the representation of Northern Hemisphere (NH) storm tracks has improved since CMIP3 and some CMIP5 models are able of representing well both the number and the intensity of North Atlantic cyclones. In particular, some of the higher-atmospheric-resolution models tend to have a better representation of the tilt of the North Atlantic storm track and of the intensity of cyclones in DJF.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-12-00501.s1.

Corresponding author address: Giuseppe Zappa, Department of Meteorology, University of Reading, Earley Gate, P.O. Box 243, Reading RG6 6BP, United Kingdom. E-mail: g.zappa@reading.ac.uk

Supplementary Materials

    • Supplemental Materials (PDF 1.93 MB)
Save
Cover Journal of Climate
Journal of Climate

  • Bengtsson, L., K. I. Hodges, and E. Roeckner, 2006: Storm tracks and climate change. J. Climate, 19, 3518–3543.

  • Bengtsson, L., K. I. Hodges, and N. Keenlyside, 2009: Will extratropical storms intensify in a warmer climate? J. Climate, 22, 2276–2301.

    • Search Google Scholar
    • Export Citation

  • Blackmon, M., 1976: A climatological spectral study of the 500 mb geopotential height of the Northern Hemisphere. J. Atmos. Sci., 33, 1607–1623.

    • Search Google Scholar
    • Export Citation

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

  • Boer, G., and S. Lambert, 2008: The energy cycle in atmospheric models. Climate Dyn., 30, 371–390.

  • Bracegirdle, T. J., and D. B. Stephenson, 2012: Higher precision estimates of regional polar warming by ensemble regression of climate model projections. Climate Dyn., 39, 2805–2821, doi:10.1007/s00382-012-1330-3.

    • Search Google Scholar
    • Export Citation

  • Brayshaw, D. J., B. Hoskins, and M. Blackburn, 2009: The basic ingredients of the North Atlantic storm track. Part I: Land–sea contrast and orography. J. Atmos. Sci., 66, 2539–2558.

    • Search Google Scholar
    • Export Citation

  • Catto, J., L. Shaffrey, and K. I. Hodges, 2010: Can climate models capture the structure of extratropical cyclones? J. Climate, 23, 1621–1635.

    • Search Google Scholar
    • Export Citation

  • Catto, J., L. Shaffrey, and K. I. Hodges, 2011: Northern Hemisphere extratropical cyclones in a warming climate in the HiGEM high-resolution climate model. J. Climate, 24, 5336–5352.

    • Search Google Scholar
    • Export Citation

  • Chang, E. K. M., 2009: Are band-pass variance statistics useful measures of storm track activity? Re-examining storm track variability associated with the NAO using multiple storm track measures. Climate Dyn., 33, 277–296.

    • Search Google Scholar
    • Export Citation

  • Chang, E. K. M., Y. Guo, and X. Xia, 2012: CMIP5 multi-model ensemble projection of storm track change under global warming. J. Geophys. Res., 117, D23118, doi:10.1029/2012JD018578.

    • Search Google Scholar
    • Export Citation

  • Chang, E. K. M., Y. Guo, X. Xia, and M. Zheng, 2013: Storm track activity in IPCC AR4/CMIP3 model simulations. J. Climate, 26, 246–260.

    • Search Google Scholar
    • Export Citation

  • Duchon, C. E., 1979: Lanczos filtering in one and two dimensions. J. Appl. Meteor., 18, 1016–1022.

  • Fink, A., T. Brücher, V. Ermert, A. Krüger, and J. G. Pinto, 2009: The European storm Kyrill in January 2007: Synoptic evolution, meteorological impacts and some considerations with respect to climate change. Nat. Hazards Earth Syst. Sci., 9, 405–423.

    • Search Google Scholar
    • Export Citation

  • Greeves, C., V. Pope, R. Stratton, and G. M. Martin, 2007: Representation of Northern Hemisphere winter storm tracks in climate models. Climate Dyn., 28, 683–702.

    • Search Google Scholar
    • Export Citation

  • Hodges, K. I., 1994: A general method for tracking analysis and its application to meteorological data. Mon. Wea. Rev., 122, 2573–2586.

    • Search Google Scholar
    • Export Citation

  • Hodges, K. I., 1995: Feature tracking on the 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.

  • Hodges, K. I., R. W. Lee, and L. Bengtsson, 2011: A comparison of extratropical cyclones in recent reanalyses ERA-Interim, NASA MERRA, NCEP CFSR, and JRA-25. J. Climate, 24, 4888–4906.

    • Search Google Scholar
    • Export Citation

  • Hoskins, B., and P. Valdes, 1990: On the existence of storm-tracks. J. Atmos. Sci., 47, 1854–1864.

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

  • Hoskins, B., I. James, and G. White, 1983: The shape, propagation and mean-flow interaction of large-scale weather systems. J. Atmos. Sci., 40, 1595–1612.

    • Search Google Scholar
    • Export Citation

  • Inatsu, M., and B. Hoskins, 2004: The zonal asymmetry of the Southern Hemisphere winter storm track. J. Climate, 17, 4882–4892.

  • Jung, T., and Coauthors, 2012: High-resolution global climate simulations with the ECMWF model in Project Athena: Experimental design, model climate and seasonal forecast skill. J. Climate, 25, 3155–3172.

    • Search Google Scholar
    • Export Citation

  • Keeley, S. P. E., R. T. Sutton, and L. C. Shaffrey, 2012: The impact of North Atlantic sea surface temperature errors on the simulation of North Atlantic European region climate. Quart. J. Roy. Meteor. Soc., 138, 1774–1783, doi:10.1002/qj.1912.

    • Search Google Scholar
    • Export Citation

  • Kidston, J., and E. P. Gerber, 2010: Intermodel variability of the poleward shift of the austral jet stream in the CMIP3 integrations linked to biases in 20th century climatology. Geophys. Res. Lett.,37, L09708, doi:10.1029/2010GL042873.

  • Laîné, A., M. Kageyama, D. Salas-Mélia, G. Ramstein, S. Planton, S. Denvil, and S. Tyteca, 2009: An energetics study of wintertime Northern Hemisphere storm tracks under 4 × CO2 conditions in two ocean–atmosphere coupled models. J. Climate, 22, 819–839.

    • Search Google Scholar
    • Export Citation

  • Lamb, H., 1991: Historic Storms of the North Sea, British Isles and Northwest Europe. Cambridge University Press, 204 pp.

  • Lambert, S. J., and J. C. Fyfe, 2006: Changes in winter cyclone frequencies and strengths simulated in enhanced greenhouse warming experiments: Results from the models participating in the IPCC diagnostic exercise. Climate Dyn., 26, 713–728.

    • Search Google Scholar
    • Export Citation

  • Lambert, S. J., J. Sheng, and J. Boyle, 2002: Winter cyclone frequencies in thirteen models participating in the Atmospheric Model Intercomparison Project (AMIP1). Climate Dyn., 19, 1–16.

    • Search Google Scholar
    • Export Citation

  • Leckebusch, G. C., and U. Ulbrich, 2004: On the relationship between cyclones and extreme windstorm events over Europe under climate change. Global Planet. Change, 44, 181–193.

    • Search Google Scholar
    • Export Citation

  • Lucarini, V., S. Calmanti, A. Dell'Aquila, P. Ruti, and A. Speranza, 2007: Intercomparison of the Northern Hemisphere winter mid-latitude atmospheric variability of the IPCC models. Climate Dyn., 28, 829–848.

    • Search Google Scholar
    • Export Citation

  • Nakamura, H., and J. Wallace, 1993: Synoptic behavior of baroclinic eddies during the blocking onset. Mon. Wea. Rev., 121, 1892–1903.

  • Neu, U., and Coauthors, 2012: IMILAST—A community effort to intercompare extratropical cyclone detection and tracking algorithms: Assessing method-related uncertainties. Bull. Amer. Meteor. Soc., 94, 529–547.

    • Search Google Scholar
    • Export Citation

  • O'Gorman, P. A., 2010: Understanding the varied response of the extratropical storm tracks to climate change. Proc. Natl. Acad. Sci. USA, 107, 19 176–19 180.

    • Search Google Scholar
    • Export Citation

  • Onogi, K., and Coauthors, 2007: The JRA-25 Reanalysis. J. Meteor. Soc. Japan, 85, 369–432.

  • Peixoto, J., and A. Oort, 1992: Physics of Climate. American Institute of Physics, 520 pp.

  • Pinto, J., E. Fröhlich, G. Leckebusch, and U. Ulbrich, 2007a: Changing European storm loss potentials under modified climate conditions according to ensemble simulations of the ECHAM5/MPI-OM1 GCM. Nat. Hazards Earth Syst. Sci., 7, 165–175.

    • Search Google Scholar
    • Export Citation

  • Pinto, J., U. Ulbrich, G. Leckebusch, T. Spangehl, M. Reyers, and S. Zacharias, 2007b: Changes in storm track and cyclone activity in three SRES ensemble experiments with the ECHAM5/MPI-OM1 GCM. Climate Dyn., 29, 195–210.

    • Search Google Scholar
    • Export Citation

  • Raible, C., P. Della-Marta, C. Schwierz, H. Wernli, and R. Blender, 2008: Northern Hemisphere extratropical cyclones: A comparison of detection and tracking methods and different reanalyses. Mon. Wea. Rev., 136, 880–897.

    • Search Google Scholar
    • Export Citation

  • Randall, D., and Coauthors, 2007: Climate models and their evaluation. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 589–662.

  • 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

  • Saha, S., and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc., 91, 1015–1057.

  • Scaife, A., and Coauthors, 2011: Improved Atlantic winter blocking in a climate model. Geophys. Res. Lett.,38, L23703, doi:10.1029/2011GL049573.

  • Simmons, A., S. Uppala, D. Dee, and S. Kobayashi, 2007: ERA-Interim: New ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter, No. 100, ECMWF, Reading, United Kingdom, 25–35.

  • Sinclair, M., and I. Watterson, 1999: Objective assessment of extratropical weather systems in simulated climates. J. Climate, 12, 3467–3485.

    • Search Google Scholar
    • Export Citation

  • Taylor, K., R. Stouffer, and G. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485–498.

  • Thorncroft, C., B. Hoskins, and M. McIntyre, 1993: Two paradigms of baroclinicwave life-cycle behaviour. Quart. J. Roy. Meteor. Soc., 119, 17–55.

    • Search Google Scholar
    • Export Citation

  • Ulbrich, U., J. G. Pinto, H. Kupfer, G. C. Leckebusch, T. Spangehl, and M. Reyers, 2008: Changing Northern Hemisphere storm tracks in an ensemble of IPCC climate change simulations. J. Climate, 21, 1669–1679.

    • Search Google Scholar
    • Export Citation

  • Ulbrich, U., G. Leckebusch, and J. Pinto, 2009: Extra-tropical cyclones in the present and future climate: A review. Theor. Appl. Climatol., 96, 117–131.

    • Search Google Scholar
    • Export Citation

  • Wallace, J., G. Lim, and M. Blackmon, 1988: Relationship between cyclone tracks, anticyclone tracks and baroclinic waveguides. J. Atmos. Sci., 45, 439–462.

    • Search Google Scholar
    • Export Citation

  • Wang, X., V. Swail, and F. Zwiers, 2006: Climatology and changes of extratropical cyclone activity: Comparison of ERA-40 with NCEP–NCAR reanalysis for 1958–2001. J. Climate, 19, 3145–3166.

    • Search Google Scholar
    • Export Citation

  • Woollings, T., A. Hannachi, and B. Hoskins, 2010: Variability of the North Atlantic eddy-driven jet stream. Quart. J. Roy. Meteor. Soc., 136, 856–868.

    • Search Google Scholar
    • Export Citation

  • Zappa, G., L. C. Shaffrey, K. I. Hodges, P. Sansom, and D. B. Stephenson, 2013: A multimodel assessment of future projections of North Atlantic and European cyclones in the CMIP5 climate models. J. Climate, in press.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2775 789 56
PDF Downloads 1122 232 20