Trends in winter circulation over the British Isles and central Europe in twenty-first century projections by 25 CMIP5 GCMs

Climate Dynamics volume 52, pages1063–1075(2019)Cite this article

Abstract

Winter midlatitude atmospheric circulation has been extensively studied for its tight link to surface weather, and automated circulation classifications have often been used to this end. Here, eight such classifications are applied to daily sea level pressure patterns simulated by an ensemble of CMIP5 GCMs twenty-first century projections for the British Isles and central Europe in order to robustly estimate future changes in frequency, persistence, and strength of synoptic-scale circulation there. All methods are able to identify present-day biases of models reported before, such as an overestimated occurrence of zonal flow and underestimation of anticyclonic conditions and easterly advection, although the strength of these biases varies among the methods. In future, models show that the zonal flow will become more frequent while the strength of the mean flow is not projected to change. Over the British Isles, the models that better simulate the latitude of zonal flow over the historical period indicate a slight equatorward shift of westerlies in their projections, while the poleward expansion of circulation—expected in future at global scale—is apparent in those models that have large errors. Over central Europe, some classifications indicate an increase in persistence and especially in frequency of anticyclonic types, which is, however, shown to be rather an artifact of some methods than a real feature. On the other hand, the easterly flow is robustly projected to become markedly weaker in central Europe, which we hypothesize might be an important factor contributing to the projected decrease of cold extremes there.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

38,45 €

Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Addor N, Rohrer M, Furrer R, Seibert J (2016) Propagation of biases in climate models from the synoptic to the regional scale: implications for bias adjustment. J Geophys Res Atmos 121:2075–2089. https://doi.org/10.1002/2015JD024040

    Article  Google Scholar 

  2. Allen RJ, Sherwood SC, Norris JR, Zender CS (2012) Recent Northern Hemisphere tropical expansion primarily driven by black carbon and tropospheric ozone. Nature 485:350–354. https://doi.org/10.1038/nature11097

    Article  Google Scholar 

  3. Allen RJ, Norris JR, Kovilakam M (2014) Influence of anthropogenic aerosols and the Pacific Decadal Oscillation on tropical belt width. Nat Geosci 7:270–274. https://doi.org/10.1038/NGEO2091

    Article  Google Scholar 

  4. Ayarzagüena B, Screen JA (2016) Future Arctic sea ice loss reduces severity of cold air outbreaks in midlatitudes. Geophys Res Lett 43:2801–2809. https://doi.org/10.1002/2016GL068092

    Article  Google Scholar 

  5. Barnes EA, Polvani LM (2013) Response of the midlatitude jets, and of their variability, to increased greenhouse gases in the CMIP5 models. J Clim 26:7117–7135. https://doi.org/10.1175/JCLI-D-12-00536.1

    Article  Google Scholar 

  6. Barnes EA, Polvani LM (2015) Projections of Arctic Amplification, of the North American/North Atlantic circulation, and of their relationship. J Clim 28:5254–5271. https://doi.org/10.1175/JCLI-D-14-00589.1

    Article  Google Scholar 

  7. Barnes EA, Screen JA (2015) The impact of Arctic warming on the midlatitude jet-stream: can it? Has it? Will it? WIREs Clim Chang 6:277–286. https://doi.org/10.1002/wcc.337

    Article  Google Scholar 

  8. Beck C, Jacobeit J, Jones PD (2007) Frequency and within-type variations of large-scale circulation types and their effects on low-frequency climate variability in central Europe since 1780. Int J Climatol 27:473–491. https://doi.org/10.1002/joc.1410

    Article  Google Scholar 

  9. Belleflamme A, Fettweis X, Erpicum M (2015) Do global warming-induced circulation pattern changes affect temperature and precipitation over Europe during summer? Int J Climatol 35:1484–1499. https://doi.org/10.1002/joc.4070

    Article  Google Scholar 

  10. Bender FA-M, Ramanathan V, Tselioudis G (2012) Changes in extratropical storm track cloudiness 1983–2008: observational support for a poleward shift. Clim Dyn 38:2037–2053. https://doi.org/10.1007/s00382-011-1065-6

    Article  Google Scholar 

  11. Blenkinsop S, Jones PD, Dorling SR, Osborn TJ (2009) Observed and modelled influence of atmospheric circulation on central England temperature extremes. Int J Climatol 29:1642–1660. https://doi.org/10.1002/joc.1807

    Article  Google Scholar 

  12. Blenkinsop S, Chan SC, Kendon EJ, Roberts NM, Fowler HJ (2015) Temperature influences on intense UK hourly precipitation and dependency on large-scale circulation. Environ Res Lett 10:054021. https://doi.org/10.1088/1748-9326/10/5/054021

    Article  Google Scholar 

  13. Boland EJD, Bracegirdle TJ, Shuckburgh EF (2017) Assessment of sea ice-atmosphere links in CMIP5 models. Clim Dyn 49:683–702. https://doi.org/10.1007/s00382-016-3367-1

    Article  Google Scholar 

  14. Borodina A, Fischer EM, Knutti R (2017) Emergent constraints in climate projections: a case study of changes in high-latitude temperature variability. J Clim 30:3655–3670. https://doi.org/10.1175/JCLI-D-16-0662.1

    Article  Google Scholar 

  15. Brands S, Herrera S, Fernández J, Gutiérrez JM (2013) How well do CMIP5 Earth System Models simulate present climate conditions in Europe and Africa? Clim Dyn 41:803–817. https://doi.org/10.1007/s00382-013-1742-8

    Article  Google Scholar 

  16. Broderick C, Fealy R (2015) An analysis of the synoptic and climatological applicability of circulation type classifications for Ireland. Int J Climatol 35:481–505. https://doi.org/10.1002/joc.3996

    Article  Google Scholar 

  17. 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 A 63:212–222. https://doi.org/10.1111/j.1600-0870.2010.00492.x

    Article  Google Scholar 

  18. Cahynová M, Huth R (2009) Enhanced lifetime of atmospheric circulation types over Europe: fact or fiction? Tellus 61A:407–416. https://doi.org/10.1111/j.1600-0870.2009.00393.x

    Article  Google Scholar 

  19. Cahynová M, Huth R (2016) Atmospheric circulation influence on climatic trends in Europe: an analysis of circulation type classifications from the COST733 catalogue. Int J Climatol 36:2743–2760. https://doi.org/10.1002/joc.4003

    Article  Google Scholar 

  20. Calvo N, Polvani LM, Solomon S (2015) On the surface impact of Arctic stratospheric ozone extremes. Environ Res Lett 10:094003. https://doi.org/10.1088/1748-9326/10/9/094003

    Article  Google Scholar 

  21. Cassou C, Cattiaux J (2016) Disruption of the European climate seasonal clock in a warming world. Nat Clim Chang 6:589–594. https://doi.org/10.1038/nclimate2969

    Article  Google Scholar 

  22. Cattiaux J, Yiou P, Vautard R (2012) Dynamics of future seasonal temperature trends and extremes in Europe: a multi-model analysis from CMIP3. Clim Dyn 38:1949–1964. https://doi.org/10.1007/s00382-011-1211-1

    Article  Google Scholar 

  23. Cattiaux J, Douville H, Peings Y (2013a) European temperatures in CMIP5: origins of present-day biases and future uncertainties. Clim Dyn 41:2889–2907. https://doi.org/10.1007/s00382-013-1731-y

    Article  Google Scholar 

  24. Cattiaux J, Quesada B, Arakélian A, Codron F, Vautard R, Yiou P (2013b) North-Atlantic dynamics and European temperature extremes in the IPSL model: sensitivity to atmospheric resolution. Clim Dyn 40:2293–2310. https://doi.org/10.1007/s00382-012-1529-3

    Article  Google Scholar 

  25. Cattiaux J, Peings Y, Saint-Martin D, Trou-Kechout N, Vavrus SJ (2016) Sinuosity of midlatitude atmospheric flow in a warming world. Geophys Res Lett 43:8259–8268. https://doi.org/10.1002/2016GL070309

    Article  Google Scholar 

  26. Charlton-Perez AJ et al (2013) On the lack of stratospheric dynamical variability in low-top versions of the CMIP5 models. J Geophys Res Atmos 118:2494–2505. https://doi.org/10.1002/jgrd.50125

    Article  Google Scholar 

  27. Compo GP et al (2011) The twentieth century reanalysis project. Q J R Meteorol Soc 137:1–28. https://doi.org/10.1002/qj.776

    Article  Google Scholar 

  28. Demuzere M, Werner M, Van Lipzig N, Roeckner E (2009) An analysis of present and future ECHAM5 pressure fields using a classification of circulation patterns. Int J Climatol 29:1796–1810. https://doi.org/10.1002/joc.1821

    Article  Google Scholar 

  29. Dunn-Sigouin E, Son S-W (2013) Northern Hemisphere blocking frequency and duration in the CMIP5 models. J Geophys Res Atmos 118:1179–1188. https://doi.org/10.1002/jgrd.50143

    Article  Google Scholar 

  30. Enke W, Spekat A (1997) Downscaling climate model outputs into local and regional weather elements by classification and regression. Clim Res 8:195–207

    Article  Google Scholar 

  31. Francis JA, Vavrus SJ, Cohen J (2017) Amplified Arctic warming and mid-latitude weather: new perspectives on emerging connections. WIREs Clim Chang 8:e474. https://doi.org/10.1002/wcc.474

    Article  Google Scholar 

  32. Furtado JC, Cohen JL, Butler AH, Riddle EE, Kumar A (2015) Eurasian snow cover variability and links to winter climate in the CMIP5 models. Clim Dyn 45:2591–2605. https://doi.org/10.1007/s00382-015-2494-4

    Article  Google Scholar 

  33. Grise KM, Polvani LM (2014) The response of midlatitude jets to increased CO2: distinguishing the roles of sea surface temperature and direct radiative forcing. Geophys Res Lett 41:6863–6871. https://doi.org/10.1002/2014GL061638

    Article  Google Scholar 

  34. Han Z, Luo F, Li S, Gao Y, Furevik T, Svendsen L (2016) Simulation by CMIP5 models of the Atlantic Multidecadal Oscillation and its climate impacts. Adv Atmos Sci 33:1329–1342. https://doi.org/10.1007/s00376-016-5270-4

    Article  Google Scholar 

  35. Horton DE, Johnson NC, Singh D, Swain DL, Rajaratnam B, Diffenbaugh NS (2015) Contribution of changes in atmospheric circulation patterns to extreme temperature trends. Nature 522:465–469. https://doi.org/10.1038/nature14550

    Article  Google Scholar 

  36. Hoskins B, Woolings T (2015) Persistent extratropical regimes and climate extremes. Curr Clim Chang Rep 1:115–124. https://doi.org/10.1007/s40641-015-0020-8

    Article  Google Scholar 

  37. Huth R (1996) Properties of the circulation classification scheme based on the rotated principal component analysis. Meteorol Atmos Phys 59:217–233

    Article  Google Scholar 

  38. Huth R, Beck C, Philipp A, Demuzere M, Ustrnul Z, Cahynová M, Kyselý J, Tveito OE (2008) Classifications of atmospheric circulation patterns. Recent advances and applications. Ann N Y Acad Sci 1146:105–152. https://doi.org/10.1196/annals.1446.019

    Article  Google Scholar 

  39. James PM (2006) An assessment of European synoptic variability in Hadley Centre Global Environmental models based on an objective classification of weather regimes. Clim Dyn 27:215–231. https://doi.org/10.1007/s00382-006-0133-9

    Article  Google Scholar 

  40. Jones PD, Harpham C, Briffa KR (2013) Lamb weather types derived from reanalysis products. Int J Climatol 33:1129–1139. https://doi.org/10.1002/joc.3498

    Article  Google Scholar 

  41. Kalnay E et al. (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–470. https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2

    Article  Google Scholar 

  42. Kaufman L, Rousseeuw PJ (1990) Finding groups in data: an introduction to cluster analysis Wiley Series in probability and mathematical statistics: applied probability and statistics. Wiley, New York

    Google Scholar 

  43. Kidston J, Cairns CW, Paga P (2013) Variability in the width of the tropics and the annular modes. Geophys Res Lett 40:2328–2332. https://doi.org/10.1029/2012GL054165

    Article  Google Scholar 

  44. Kobayashi S et al (2015) The JRA-55 reanalysis: general specifications and basic characteristics. J Meteorol Soc Jpn 93:5–48. https://doi.org/10.2151/jmsj.2015-001

    Article  Google Scholar 

  45. Kyselý J (2007) Implications of enhanced persistence of atmospheric circulation for the occurrence and severity of temperature extremes. Int J Climatol 27:689–695. https://doi.org/10.1002/joc.1478

    Article  Google Scholar 

  46. Kyselý J (2008) Influence of the persistence of circulation patterns on warm and cold temperature anomalies in Europe: analysis over the 20th century. Glob Planet Chang 62:147–163. https://doi.org/10.1016/j.gloplacha.2008.01.003

    Article  Google Scholar 

  47. Lamb HH (1972) British Isles weather types and register of daily sequence of circulation patterns, 1861–1971. Her Majesty’s Stationery Office, London

    Google Scholar 

  48. Lee Y, Black RX (2015) The structure and dynamics of the stratospheric northern annular mode in CMIP5 simulations. J Clim 28:86–107. https://doi.org/10.1175/JCLI-D-13-00570.1

    Article  Google Scholar 

  49. Lorenzo MN, Ramos AM, Taboada JJ, Gimeno L (2011) Changes in present and future circulation types frequency in northwest Iberian Peninsula. PLoS One 6:e16201. https://doi.org/10.1371/journal.pone.0016201

    Article  Google Scholar 

  50. Lund IA (1963) Map-pattern classification by statistical methods. J Appl Meteorol 2:56–65

    Article  Google Scholar 

  51. Manzini E et al (2014) Northern winter climate change: assessment of uncertainty in CMIP5 projections related to stratosphere–troposphere coupling. J Geophys Res Atmos 119:7979–7998. https://doi.org/10.1002/2013JD021403

    Article  Google Scholar 

  52. Marshall J, Kushnir Y, Batisti D, Chang P, Czaja R, Dicson R, Hurrell J, McCartney M, Saravanan R, Visbeck M (2001) North Atlantic climate variability: phenomena, impacts and mechanisms. J Climatol 21:1863–1898. https://doi.org/10.1002/joc.693

    Article  Google Scholar 

  53. Masato G, Woollings T, Hoskins BJ (2014) Structure and impact of atmospheric blocking over the Euro-Atlantic region in present-day and future simulations. Geophys Res Lett 41:1051–1058. https://doi.org/10.1002/2013GL058570

    Article  Google Scholar 

  54. Meehl GA, Covey C, Taylor KE, Delworth T, Stouffer RJ, Latif M, McAvaney B, Mitchell JFB (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394. https://doi.org/10.1175/BAMS-88-9-1383

    Article  Google Scholar 

  55. Notz D (2015) How well must climate models agree with observations? Philos Trans R Soc A 373:20140164. https://doi.org/10.1098/rsta.2014.0164

    Article  Google Scholar 

  56. O’Sullivan J, Sweeney C, Nolan P, Gleeson E (2016) A high-resolution, multi-model analysis of Irish temperatures for the mid-21st century. Int J Climatol 36:1256–1267. https://doi.org/10.1002/joc.4419

    Article  Google Scholar 

  57. Otero N, Sillmann J, Butler T (2017) Assessment of an extended version of the Jenkinson–Collison classification on CMIP5 models over Europe. Clim Dyn. https://doi.org/10.1007/s00382-017-3705-y

    Google Scholar 

  58. Pastor MA, Casado MJ (2012) Use of circulation types classifications to evaluate AR4 climate models over the Euro-Atlantic region. Clim Dyn 39:2059–2077. https://doi.org/10.1007/s00382-012-1449-2

    Article  Google Scholar 

  59. Peings Y, Simpkins G, Magnusdottir G (2016) Multidecadal fluctuations of the North Atlantic Ocean and feedback on the winter climate in CMIP5 control simulations. J Geophys Res Atmos 121:2571–2592. https://doi.org/10.1002/2015JD024107

    Article  Google Scholar 

  60. Peings Y, Cattiaux J, Vavrus S, Magnusdottir G (2017) Late twenty-first-century changes in the midlatitude atmospheric circulation in the CESM large ensemble. J Clim 30:5943–5960. https://doi.org/10.1175/JCLI-D-16-0340.1

    Article  Google Scholar 

  61. Perez J, Menendez M, Mendez FJ, Losada IJ (2014) Evaluating the performance of CMIP3 and CMIP5 global climate models over the north-east Atlantic region. Clim Dyn 43:2663–2680. https://doi.org/10.1007/s00382-014-2078-8

    Article  Google Scholar 

  62. Philipp A, Della-Marta PM, Jacobeit J, Fereday DR, Jones PD, Moberg A, Wanner H (2007) Long-term variability of daily North Atlantic–European pressure patterns since 1850 classified by simulated annealing clustering. J Clim 20:4065–4095. https://doi.org/10.1175/JCLI4175.1

    Article  Google Scholar 

  63. Philipp A et al (2010) Cost733cat—a database of weather and circulation type classifications. Phys Chem Earth 35:360–373. https://doi.org/10.1016/j.pce.2009.12.010

    Article  Google Scholar 

  64. Philipp A, Beck C, Huth R, Jacobeit J (2016) Development and comparison of circulation type classifications using the COST 733 dataset and software. Int J Climatol 36:2671–2809. https://doi.org/10.1002/joc.3920

    Article  Google Scholar 

  65. Plavcová E, Kyselý J (2013) Projected evolution of circulation types and their temperatures over Central Europe in climate models. Theor Appl Climatol 114:625–634. https://doi.org/10.1007/s00704-013-0874-4

    Article  Google Scholar 

  66. Plavcová E, Kyselý J (2016) Overly persistent circulation in climate models contributes to overestimated frequency and duration of heat waves and cold spells. Clim Dyn 46:2805–2820. https://doi.org/10.1007/s00382-015-2733-8

    Article  Google Scholar 

  67. Plavcová E, Kyselý J, Štěpánek P (2014) Links between circulation types and precipitation in Central Europe in the observed data and regional climate model simulations. Int J Climatol 34:2885–2898. https://doi.org/10.1002/joc.3882

    Google Scholar 

  68. Poli P et al (2016) ERA-20C: an atmospheric reanalysis of the twentieth century. J Clim 29:4083–4097. https://doi.org/10.1175/JCLI-D-15-0556.1

    Article  Google Scholar 

  69. Previdi M, Liepert BG (2007) Annular modes and Hadley cell expansion under global warming. Geophys Res Lett 34:L22701. https://doi.org/10.1029/2007GL031243

    Article  Google Scholar 

  70. Reichler T (2016) Poleward expansion of the atmospheric circulation. In: Letcher TM (ed) Climate change: observed impacts on planet earth. Elsevier, Oxford

    Google Scholar 

  71. Rhines A, McKinnon KA, Tingley MP, Huybers P (2017) Seasonally resolved distributional trends of North American temperatures show contraction of winter variability. J Clim 30:1139–1157. https://doi.org/10.1175/JCLI-D-16-0363.1

    Article  Google Scholar 

  72. Richman MB (1986) Rotation of principal components. J Climatol 6:293–335. https://doi.org/10.1002/joc.3370060305

    Article  Google Scholar 

  73. Rohrer M, Croci-Maspoli M, Appenzeller C (2017) Climate change and circulation types in the Alpine region. Meteorol Z 26:83–92. https://doi.org/10.1127/metz/2016/0681

    Article  Google Scholar 

  74. Röthlisberger M, Pfahl S, Martius O (2016) Regional-scale jet waviness modulates the occurrence of midlatitude weather extremes. Geophys Res Lett 43:10989–10997. https://doi.org/10.1002/2016GL070944

    Article  Google Scholar 

  75. Rust HW, Vrac M, Lengaigne M, Sultan B (2010) Quantifying differences in circulation patterns based on probabilistic models: IPCC AR4 multimodel comparison for the North Atlantic. J Clim 23:6573–6589. https://doi.org/10.1175/2010JCLI3432.1

    Article  Google Scholar 

  76. Shepherd TG (2014) Atmospheric circulation as a source of uncertainty in climate change projections. Nat Geosci 7:703–708. https://doi.org/10.1038/ngeo2253

    Article  Google Scholar 

  77. Sillmann J, Kharin VV, Zwiers FW, Zhang X, Bronaugh D (2013) Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J Geophys Res Atmos 118:2473–2493. https://doi.org/10.1002/jgrd.50188

    Article  Google Scholar 

  78. Simpson IR, Shaw TA, Seager R (2014) A diagnosis of the seasonally and longitudinally varying midlatitude circulation response to global warming. J Atmos Sci 71:2489–2515. https://doi.org/10.1175/JAS-D-13-0325.1

    Article  Google Scholar 

  79. Smith KL, Polvani LM (2014) The surface impacts of Arctic stratospheric ozone anomalies. Environ Res Lett 9:074015. https://doi.org/10.1088/1748-9326/9/7/074015

    Article  Google Scholar 

  80. Stryhal J, Huth R (2017) Classifications of winter Euro-Atlantic circulation patterns: an intercomparison of five atmospheric reanalyses. J Clim 30:7847–7861. https://doi.org/10.1175/JCLI-D-17-0059.1

    Article  Google Scholar 

  81. Tao L, Hu Y, Liu J (2016) Anthropogenic forcing on the Hadley circulation in CMIP5 simulations. Clim Dyn 46:3337–3350. https://doi.org/10.1007/s00382-015-2772-1

    Article  Google Scholar 

  82. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. https://doi.org/10.1175/BAMS-D-11-00094.1

    Article  Google Scholar 

  83. Uppala SM et al (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131:2961–3012. https://doi.org/10.1256/qj.04.176

    Article  Google Scholar 

  84. Wang C, Zhang L, Lee S-K, Wu L, Mechoso CR (2014) A global perspective on CMIP5 climate model biases. Nat Clim Chang 4:201–205. https://doi.org/10.1038/nclimate2118

    Article  Google Scholar 

  85. Wójcik R (2015) Reliability of CMIP5 GCM simulations in reproducing atmospheric circulation over Europe and the North Atlantic: a statistical downscaling perspective. Int J Climatol 35:714–732. https://doi.org/10.1002/joc.4015

    Article  Google Scholar 

  86. Woolings T, Harvey B, Masato G (2014) Arctic warming, atmospheric blocking and cold European winters in CMIP5 models. Environ Res Lett 9:014002. https://doi.org/10.1088/1748-9326/9/1/014002

    Article  Google Scholar 

  87. Zappa G, Masato G, Shaffrey L, Woollings T, Hodges K (2014) Linking Northern Hemisphere blocking and storm track biases in the CMIP5 climate models. Geophys Res Lett 41:135–139. https://doi.org/10.1002/2013GL058480

    Article  Google Scholar 

Download references

Acknowledgements

The work was funded by the Grant Agency of Charles University, Project 188214. We acknowledge all modeling groups for providing their GCM data and the Earth System Grid-Center for Enabling Technologies (ESG-CET) for enabling access to it. We thank NOAA/OAR/ESRL PSD, Boulder, Colorado, for the NCEP–NCAR reanalysis and Twentieth Century Reanalysis, version 2; ECMWF for ERA-40 and ERA-20C; and JMA for JRA-55. All developers of the COST733 software are greatly acknowledged, and so is the Institute of Geography, University of Augsburg, Germany, for maintaining the software and providing access to it.

Author information

Affiliations

  1. Department of Physical Geography and Geoecology, Faculty of Science, Charles University, Albertov 6, 128 43, Prague 2, Czechia

    Jan Stryhal & Radan Huth

  2. Institute of Atmospheric Physics, Czech Academy of Sciences, Boční II, 141 31, Prague 4, Czechia

    Jan Stryhal & Radan Huth

Authors
  1. Jan Stryhal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Radan Huth
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jan Stryhal.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 4 KB)

Supplementary material 2 (DOCX 19 KB)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Stryhal, J., Huth, R. Trends in winter circulation over the British Isles and central Europe in twenty-first century projections by 25 CMIP5 GCMs. Clim Dyn 52, 1063–1075 (2019). https://doi.org/10.1007/s00382-018-4178-3

Download citation

Keywords

  • Global climate models
  • CMIP5
  • Projections
  • Atmospheric circulation
  • Circulation classifications