Abstract
The future changes of atmospheric blocking over the Euro-Atlantic sector, diagnosed from an ensemble of 17 global-climate simulations obtained with the ECHAM5/MPI-OM model, are shown to be largely explainable from the change of the 500 hPa mean zonal circulation and its variance. The reduction of the blocking frequency over the Atlantic and the increased frequency of easterly upper-level flow poleward of 60°N are well explained by the changes of mean zonal circulation. In winter and autumn an additional downstream shift of the frequency maximum is simulated. This is also seen in a subset of the CMIP5 models with RCP8.5. To explain this downstream shift requires the inclusion of the changing variance. It is suggested that the increased downstream variance is caused by the stronger, more eastward extending future jet, which promotes Rossby wave breaking and blocking to occur further downstream. The same relation between jet-strength and central-blocking longitude is found in the variability of the current climate.
Similar content being viewed by others
Notes
Note that these criteria are the same as in Tibaldi and Molteni (1990), but transformed to the variable UG500.
References
Altenhoff AM, Martius O, Croci-Maspoli M, Schwierz C, Davies HC (2008) Linkage of atmospheric blocks and synoptic-scale Rossby waves: a climatological analysis. Tellus A60:1053–1063
Barnes EA, Hartmann DL (2010) Influence of eddy-driven jet latitude on North Atlantic jet persistence and blocking frequency in CMIP3 integrations. Geophys Res Lett 37:L23802. doi:10.1029/2010GL045700
Barnes EA, Slingo J, Woollings T (2012) A methodology for the comparison of blocking climatologies across indices, models and climate scenarios. Clim Dyn 38:2467–2481. doi:10.1007/s00382-011-1243-6
Barriopedro D, Garcia-Herrera R, Lupo AR, Hernandez E (2006) A climatology of northern hemisphere blocking. J Clim 19:1042–1063
Barriopedro D, Garcia-Herrera R, Trigo RM (2010a) Application of blocking diagnosis methods to general circulation models. Part I: a novel detection scheme. Clim Dyn 35:1373–1391. doi:10.1007/s00382-010-0767-5
Barriopedro D, Garcia-Herrera R, Trigo RM (2010b) Application of blocking diagnosis methods to general circulation models. Part II: model simulations. Clim Dyn 35:1393–1409. doi:10.1007/s00382-010-0766-6
Buehler T, Raible CC, Stocker TF (2011) The relationship of winter season North Atlantic blocking frequencies to extreme cold or dry spells in the ERA-40. Tellus 63(2):212–222. doi:10.1111/j.1600-0870.2010.00492.x
Cattiaux J, Vautard R, Cassou C, Yiou P, Masson-Delmotte V, Codron F (2010) Winter 2010 in Europe: a cold extreme in a warming climate. Geophys Res Lett 37:L20704. doi:10.1029/2010GL044613
de Vries H, Haarsma RJ, Hazeleger W (2012) Western European cold spells in current and future climate. Geophys Res Lett 39:L04706. doi:10.1029/2011GL050665
Francis JA, Vavrus SJ (2012) Evidence linking arctic amplification to extreme weather in mid-latitudes. Geophys Res Lett 39(6):L06801. doi:10.1029/2012GL051000
Illari L (1984) A diagnostic study of the potential vorticity in a warm blocking anticyclone. J Atmos Sci 41:3518–3525
Meinshausen M, Smith S, Calvin K, Daniel J, Kainuma M, Lamarque JF, Matsumoto K, Montzka S, Raper S, Riahi K, Thomson A, Velders G, van Vuuren D (2011) The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim Change 109:213–241. doi:10.1007/s10584-011-0156-z
Pelly JL, Hoskins BJ (2003) A new perspective on blocking. J Atmos Sci 60:743–755
Rex DF (1951) The effect of Atlantic blocking action upon European climate. Tellus 3:1–16. doi:10.1111/j.2153-3490.1951.tb00784.x
Rex DR (1950) Blocking action in the middle troposphere and its effect upon regional climate. Tellus 2:169–211
Scaife AA, Woollings T, Knight J, Martin G, Hinton T (2010) Atmospheric blocking and mean biases in climate models. J Clim 23:6143–6152. doi:10.1175/2010JCLI3728.1
Scaife AA, Copsey D, Gordon C, Harris C, Hinton T, Keeley S, O’Neill A, Roberts M, Williams K (2011) Improved Atlantic winter blocking in a climate model. Geophys Res Lett 38:L23703. doi:10.1029/2011GL049573
Shutts GJ (1983) The propagation of eddies in diffluent jetstreams: eddy vorticity forcing of ‘blocking’ flow fields. Quart J R Meteorol Soc 109:737–761
Sillmann J, Croci-Maspoli M (2009) Present and future atmospheric blocking and its impact on European mean and extreme climate. Geophys Res Lett 36:L10702. doi:10.1029/2009GL038259
Sillmann J, Croci-Maspoli M, M K, Kats RW (2011) Extreme cold winter temperatures in Europe under the influence of north Atlantic atmospheric blocking. J Clim 24:5899–5913. doi:10.1175/2011JCLI4075.1
Sterl A, Severijns C, Dijkstra H et al (2008) When can we expect extremely high surface temperatures? Geophys Res Lett 35:L14703. doi:10.1029/2008GL034071
Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of cmip5 and the experiment design. Bull Am Meteor Soc 93:485–498. doi:10.1175/BAMS-D-11-00094.1
Tibaldi S, Molteni F (1990) On the operational predictability of blocking. Tellus 42A:343–365. doi:10.1034/j.1600-0870.1990.t01-2-00003.x
Trigo R, Trigo I, DaCamara C, Osborn TJ (2004) Climate impact of the European winter blocking episodes from the NCEP/NCAR reanalysis. Clim Dyn 23:17–28. doi:10.1007/s00382-004-0410-4
Uppala SM, Kallberg PW, Simmons et al AJ (2005) The ERA-40 re-analysis. Quart J R Meteorol Soc 131:2961–3012. doi:10.1256/qj.04.176
Vial J, Osborn T (2012) Assessment of atmosphere-ocean general circulation model simulations of winter northern hemisphere atmospheric blocking. Clim Dyn 39:95–112. doi:10.1007/s00382-011-1177-z
von Storch H, Zwiers FW (2003) Statistical analysis in climate research, 1st edn. Cambridge University Press, Cambridge
Wilks DS (2006) Statistical methods in the atmospheric sciences, international geophysics series, vol 91, 2nd edn. Academic Press, London
Woollings T (2010) Dynamical influences on European climate: an uncertain future. Phil Trans R Soc A 368:3733–3756. doi:10.1098/rsta.2010.0040
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
1.1 Uncertainty estimation
Non-parametric bootstrap (von Storch and Zwiers 2003) is used to determine confidence intervals for seasonal mean blocking frequencies. For each period, 1,000 artificial 17-member ensembles were generated by randomly selecting (with replacement) seasonal blocking frequency patterns from the Essence ensemble. The underlying assumption for the bootstrap is that seasonal blocking frequencies are uncorrelated. Also 10,000 artificial 1-member ensembles were generated in the same way, to estimate uncertainties in 30-year blocking frequencies.
1.2 TM-index for other latitudes
Figures 9 and 10 show the two-dimensional blocking frequency patterns obtained for the TM-index.
Rights and permissions
About this article
Cite this article
de Vries, H., Woollings, T., Anstey, J. et al. Atmospheric blocking and its relation to jet changes in a future climate. Clim Dyn 41, 2643–2654 (2013). https://doi.org/10.1007/s00382-013-1699-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00382-013-1699-7