Projected Changes in European and North Atlantic Seasonal Wind Climate Derived from CMIP5 Simulations

Kimmo Ruosteenoja Finnish Meteorological Institute, Helsinki, Finland

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Timo Vihma Finnish Meteorological Institute, Helsinki, Finland

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Ari Venäläinen Finnish Meteorological Institute, Helsinki, Finland

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Abstract

Future changes in geostrophic winds over Europe and the North Atlantic region were studied utilizing output data from 21 CMIP5 global climate models (GCMs). Changes in temporal means, extremes, and the joint distribution of speed and direction were considered. In concordance with previous research, the time mean and extreme scalar wind speeds do not change pronouncedly in response to the projected climate change; some degree of weakening occurs in the majority of the domain. Nevertheless, substantial changes in high wind speeds are identified when studying the geostrophic winds from different directions separately. In particular, in northern Europe in autumn and in parts of northwestern Europe in winter, the frequency of strong westerly winds is projected to increase by up to 50%. Concurrently, easterly winds become less common. In addition, we evaluated the potential of the GCMs to simulate changes in the near-surface true wind speeds. In ocean areas, changes in the true and geostrophic winds are mainly consistent and the emerging differences can be explained (e.g., by the retreat of Arctic sea ice). Conversely, in several GCMs the continental wind speed response proved to be predominantly determined by fairly arbitrary changes in the surface properties rather than by changes in the atmospheric circulation. Accordingly, true wind projections derived directly from the model output should be treated with caution since they do not necessarily reflect the actual atmospheric response to global warming.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0023.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kimmo Ruosteenoja, kimmo.ruosteenoja@fmi.fi

Abstract

Future changes in geostrophic winds over Europe and the North Atlantic region were studied utilizing output data from 21 CMIP5 global climate models (GCMs). Changes in temporal means, extremes, and the joint distribution of speed and direction were considered. In concordance with previous research, the time mean and extreme scalar wind speeds do not change pronouncedly in response to the projected climate change; some degree of weakening occurs in the majority of the domain. Nevertheless, substantial changes in high wind speeds are identified when studying the geostrophic winds from different directions separately. In particular, in northern Europe in autumn and in parts of northwestern Europe in winter, the frequency of strong westerly winds is projected to increase by up to 50%. Concurrently, easterly winds become less common. In addition, we evaluated the potential of the GCMs to simulate changes in the near-surface true wind speeds. In ocean areas, changes in the true and geostrophic winds are mainly consistent and the emerging differences can be explained (e.g., by the retreat of Arctic sea ice). Conversely, in several GCMs the continental wind speed response proved to be predominantly determined by fairly arbitrary changes in the surface properties rather than by changes in the atmospheric circulation. Accordingly, true wind projections derived directly from the model output should be treated with caution since they do not necessarily reflect the actual atmospheric response to global warming.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0023.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kimmo Ruosteenoja, kimmo.ruosteenoja@fmi.fi

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  • Alvarez, I., M. N. Lorenzo, M. deCastro, and M. Gomez-Gesteira, 2017: Coastal upwelling trends under future warming scenarios from the CORDEX project along the Galician coast (NW Iberian Peninsula). Int. J. Climatol., 37, 34273438, https://doi.org/10.1002/joc.4927.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anttila, P., U. Makkonen, H. Hellén, K. Kyllönen, S. Leppänen, H. Saari, and H. Hakola, 2008: Impact of the open biomass fires in spring and summer of 2006 on the chemical composition of background air in south-eastern Finland. Atmos. Environ., 42, 64726486, https://doi.org/10.1016/j.atmosenv.2008.04.020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blocken, B., and J. Carmeliet, 2004: A review of wind-driven rain research in building science. J. Wind Eng. Ind. Aerodyn., 92, 10791130, https://doi.org/10.1016/j.jweia.2004.06.003.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brönnimann, S., O. Martius, H. von Waldow, C. Welker, J. Luterbacher, G. Compo, P. Sardeshmukh, and T. Usbeck, 2012: Extreme winds at northern mid-latitudes since 1871. Meteor. Z., 21, 1327, https://doi.org/10.1127/0941-2948/2012/0337.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Butler, A. H., D. W. J. Thompson, and R. Heikes, 2010: The steady-state atmospheric circulation response to climate change–like thermal forcings in a simple general circulation model. J. Climate, 23, 34743496, https://doi.org/10.1175/2010JCLI3228.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chang, E. K.-M., 2018: CMIP5 projected change in Northern Hemisphere winter cyclones with associated extreme winds. J. Climate, 31, 65276542, https://doi.org/10.1175/JCLI-D-17-0899.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coen, J., 2018: Some requirements for simulating wildland fire behavior using insight from coupled weather–wildland fire models. Fire, 1, 6, https://doi.org/10.3390/fire1010006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, M., and Coauthors, 2013: Long-term climate change: Projections, commitments and irreversibility. Climate Change 2013: The Physical Science Basis. T. F. Stocker et al., Eds., Cambridge University Press, 1029–1136.

  • de Winter, R. C., A. Sterl, and B. G. Ruessink, 2013: Wind extremes in the North Sea Basin under climate change: An ensemble study of 12 CMIP5 GCMs. J. Geophys. Res. Atmos., 118, 16011612, https://doi.org/10.1002/JGRD.50147.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunne, J. P., and Coauthors, 2013: GFDL’s ESM2 global coupled climate–carbon Earth System Models. Part II: Carbon system formulation and baseline simulation characteristics. J. Climate, 26, 22472267, https://doi.org/10.1175/JCLI-D-12-00150.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feser, F., M. Barcikowska, O. Krueger, F. Schenk, R. Weisse, and L. Xia, 2015: Storminess over the North Atlantic and northwestern Europe—A review. Quart. J. Roy. Meteor. Soc., 141, 350382, https://doi.org/10.1002/qj.2364.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Flato, G., and Coauthors, 2013: Evaluation of climate models. Climate Change 2013: The Physical Science Basis. T. F. Stocker et al., Eds., Cambridge University Press, 741–866.

  • Ganske, A., B. Tinz, G. Rosenhagen, and H. Heinrich, 2016: Interannual and multidecadal changes of wind speed and directions over the North Sea from climate model results. Meteor. Z., 25, 463478, https://doi.org/10.1127/metz/2016/0673.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gaslikova, L., I. Grabemann, and N. Groll, 2013: Changes in North Sea storm surge conditions for four transient future climate realizations. Nat. Hazards, 66, 15011518, https://doi.org/10.1007/s11069-012-0279-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gastineau, G., and B. J. Soden, 2009: Model projected changes of extreme wind events in response to global warming. Geophys. Res. Lett., 36, L10810, https://doi.org/10.1029/2009GL037500.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goubanova, K., V. Echevin, B. Dewitte, F. Codron, K. Takahashi, P. Terray, and M. Vrac, 2011: Statistical downscaling of sea-surface wind over the Peru–Chile upwelling region: Diagnosing the impact of climate change from the IPSL-CM4 model. Climate Dyn., 36, 13651378, https://doi.org/10.1007/s00382-010-0824-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gregow, H., K. Ruosteenoja, N. Pimenoff, and K. Jylhä, 2012: Changes in the mean and extreme geostrophic wind speeds in Northern Europe until 2100 based on nine global climate models. Int. J. Climatol., 32, 18341846, https://doi.org/10.1002/joc.2398.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gregow, H., A. Laaksonen, and M. E. Alper, 2017: Increasing large scale windstorm damage in Western, Central and Northern European forests, 1951–2010. Sci. Rep., 7, 46397, https://doi.org/10.1038/srep46397.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hurtt, G. C., and Coauthors, 2011: Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Climatic Change, 109, 117161, https://doi.org/10.1007/s10584-011-0153-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johansson, M. M., H. Pellikka, K. K. Kahma, and K. Ruosteenoja, 2014: Global sea level rise scenarios adapted to the Finnish coast. J. Mar. Syst., 129, 3546, https://doi.org/10.1016/j.jmarsys.2012.08.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kahma, K. K., and H. Pettersson, 2005: Wind-wave systems. Measuring and Analysing the Directional Spectrum of Ocean Waves, D. Hauser et al., Eds., Office for Official Publications of the European Communities, COST Action 714, Working Group 3, chap. 1.3, Part I, 11–14.

  • Karpechko, A. Y., and E. Manzini, 2017: Arctic stratosphere dynamical response to global warming. J. Climate, 30, 70717086, https://doi.org/10.1175/JCLI-D-16-0781.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kirtman, B., and Coauthors, 2013: Near-term climate change: Projections and predictability. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 953–1028.

  • Knox, J. A., J. D. Frye, J. D. Durkee, and C. M. Fuhrmann, 2011: Non-convective high winds associated with extratropical cyclones. Geogr. Compass, 5, 6389, https://doi.org/10.1111/j.1749-8198.2010.00395.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kohler, M., J. Metzger, and N. Kalthoff, 2018: Trends in temperature and wind speed from 40 years of observations at a 200-m high meteorological tower in Southwest Germany. Int. J. Climatol., 38, 2334, https://doi.org/10.1002/joc.5157.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Krueger, O., and H. von Storch, 2011: Evaluation of an air pressure–based proxy for storm activity. J. Climate, 24, 26122619, https://doi.org/10.1175/2011JCLI3913.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kudela, R., S. Seeyave, and W. Cochlan, 2010: The role of nutrients in regulation and promotion of harmful algal blooms in upwelling systems. Prog. Oceanogr., 85, 122135, https://doi.org/10.1016/j.pocean.2010.02.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, D., V. Mishra, and A. R. Ganguly, 2015: Evaluating wind extremes in CMIP5 climate models. Climate Dyn., 45, 441453, https://doi.org/10.1007/s00382-014-2306-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Laapas, M., and A. Venäläinen, 2017: Homogenization and trend analysis of monthly mean and maximum wind speed time series in Finland, 1959–2015. Int. J. Climatol., 37, 48034813, https://doi.org/10.1002/joc.5124.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Z., L. Song, H. Ma, J. Xiao, K. Wang, and L. Chen, 2018: Observed surface wind speed declining induced by urbanization in East China. Climate Dyn., 50, 735749, https://doi.org/10.1007/s00382-017-3637-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Luomaranta, A., K. Ruosteenoja, K. Jylhä, H. Gregow, J. Haapala, and A. Laaksonen, 2014: Multimodel estimates of the changes in the Baltic Sea ice cover during the present century. Tellus, 66A, 22617, https://doi.org/10.3402/tellusa.v66.22617.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mäll, M., Ü. Suursaar, R. Nakamura, and T. Shibayama, 2017: Modelling a storm surge under future climate scenarios: Case study of extratropical cyclone Gudrun (2005). Nat. Hazards, 89, 11191144, https://doi.org/10.1007/s11069-017-3011-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Manzini, E., and Coauthors, 2014: Northern winter climate change: Assessment of uncertainty in CMIP5 projections related to stratosphere–troposphere coupling. J. Geophys. Res. Atmos., 119, 79797998, https://doi.org/10.1002/2013JD021403.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McGraw, M. C., and E. A. Barnes, 2016: Seasonal sensitivity of the eddy-driven jet to tropospheric heating in an idealized AGCM. J. Climate, 29, 52235240, https://doi.org/10.1175/JCLI-D-15-0723.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McInnes, K. L., T. A. Erwin, and J. M. Bathols, 2011: Global climate model projected changes in 10 m wind speed and direction due to anthropogenic climate change. Atmos. Sci. Lett., 12, 325333, https://doi.org/10.1002/asl.341.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mellado-Cano, J., D. Barriopedro, R. García-Herrera, R. M. Trigo, and M. C. Álvarez-Castro, 2018: Euro-Atlantic atmospheric circulation during the Late Maunder Minimum. J. Climate, 31, 38493863, https://doi.org/10.1175/JCLI-D-17-0261.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Minder, J. R., 2010: The sensitivity of mountain snowpack accumulation to climate warming. J. Climate, 23, 26342650, https://doi.org/10.1175/2009JCLI3263.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mioduszewski, J., S. Vavrus, and M. Wang, 2018: Diminishing Arctic Sea ice promotes stronger surface winds. J. Climate, 31, 81018119, https://doi.org/10.1175/JCLI-D-18-0109.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mölter, T., D. Schindler, A. T. Albrecht, and U. Kohnle, 2016: Review on the projections of future storminess over the North Atlantic European region. Atmosphere, 7, 60, https://doi.org/10.3390/atmos7040060.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Notaro, M., V. Bennington, and S. Vavrus, 2015: Dynamically downscaled projections of lake-effect snow in the Great Lakes basin. J. Climate, 28, 16611684, https://doi.org/10.1175/JCLI-D-14-00467.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peltola, H., S. Kellomäki, H. Väisänen, and V. P. Ikonen, 1999: A mechanistic model for assessing the risk of wind and snow damage to single trees and stands of Scots pine, Norway spruce and birch. Can. J. For. Res., 29, 647661, https://doi.org/10.1139/x99-029.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pettersson, H., K. K. Kahma, and L. Tuomi, 2010: Wave directions in a narrow bay. J. Phys. Oceanogr., 40, 155169, https://doi.org/10.1175/2009JPO4220.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pryor, S. C., R. J. Barthelmie, N. E. Clausen, M. Drews, N. MacKellar, and E. Kjellström, 2012: Analyses of possible changes in intense and extreme wind speeds over northern Europe under climate change scenarios. Climate Dyn., 38, 189208, https://doi.org/10.1007/s00382-010-0955-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ronkainen, I., J. Lehtiranta, M. Lensu, E. Rinne, J. Haapala, and C. Haas, 2018: Interannual sea ice thickness variability in the Bay of Bothnia. Cryosphere, 12, 34593476, https://doi.org/10.5194/tc-12-3459-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Särkkä, J., K. Kahma, M. Kämäräinen, M. Johansson, and S. Saku, 2017: Simulated extreme sea levels at Helsinki. Boreal Environ. Res., 22, 299315.

    • Search Google Scholar
    • Export Citation
  • Schwierz, C., P. Köllner-Heck, E. Zenklusen Mutter, D. N. Bresch, P.-L. Vidale, M. Wild, and C. Schär, 2010: Modelling European winter wind storm losses in current and future climate. Climatic Change, 101, 485514, https://doi.org/10.1007/s10584-009-9712-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seiler, C., and F. W. Zwiers, 2016: How will climate change affect explosive cyclones in the extratropics of the Northern Hemisphere? Climate Dyn., 46, 36333644, https://doi.org/10.1007/s00382-015-2791-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sempreviva, A. M., R. J. Barthelmie, and S. C. Pryor, 2008: Review of methodologies for offshore wind resource assessment in European seas. Surv. Geophys., 29, 471497, https://doi.org/10.1007/s10712-008-9050-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Simpson, I. R., T. A. Shaw, and R. Seager, 2014: A diagnosis of the seasonally and longitudinally varying midlatitude circulation response to global warming. J. Atmos. Sci., 71, 24892515, https://doi.org/10.1175/JAS-D-13-0325.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Soukissian, T., F. Karathanasi, P. Axaopoulos, E. Voukouvalas, and V. Kotroni, 2018: Offshore wind climate analysis and variability in the Mediterranean Sea. Int. J. Climatol., 38, 384402, https://doi.org/10.1002/joc.5182.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stössel, A., Z. Zhang, and T. Vihma, 2011: The effect of alternative real-time wind forcing on Southern Ocean sea ice simulations. J. Geophys. Res. Oceans, 116, C11021, https://doi.org/10.1029/2011JC007328.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Suvanto, S., H. M. Henttonen, P. Nöjd, and H. Mäkinen, 2018: High-resolution topographical information improves tree-level storm damage models. Can. J. For. Res., 48, 721728, https://doi.org/10.1139/cjfr-2017-0315.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tammelin, B., and Coauthors, 2013: Production of the Finnish Wind Atlas. Wind Energy, 16, 1935, https://doi.org/10.1002/we.517.

  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 29613012, https://doi.org/10.1256/qj.04.176.

  • van Vuuren, D. P., and Coauthors, 2011: The representative concentration pathways: an overview. Climatic Change, 109, 531, https://doi.org/10.1007/s10584-011-0148-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vautard, R., J. Cattiaux, P. Yiou, J.-N. Thépaut, and P. Ciais, 2010: Northern Hemisphere atmospheric stilling partly attributed to an increase in surface roughness. Nat. Geosci., 3, 756761, https://doi.org/10.1038/ngeo979.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Venäläinen, A., and Coauthors, 2017: Estimation of the high-spatial-resolution variability in extreme wind speeds for forestry applications. Earth Syst. Dyn., 8, 529545, https://doi.org/10.5194/esd-8-529-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Willison, J., W. A. Robinson, and G. M. Lackmann, 2015: North Atlantic storm-track sensitivity to warming increases with model resolution. J. Climate, 28, 45134524, https://doi.org/10.1175/JCLI-D-14-00715.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woollings, T., and M. Blackburn, 2012: The North Atlantic jet stream under climate change and its relation to the NAO and EA patterns. J. Climate, 25, 886902, https://doi.org/10.1175/JCLI-D-11-00087.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woollings, T., J. M. Gregory, J. G. Pinto, M. Reyers, and D. J. Brayshaw, 2012: Response of the North Atlantic storm track to climate change shaped by ocean atmosphere coupling. Nat. Geosci., 5, 313317, https://doi.org/10.1038/ngeo1438.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zappa, G., L. C. Shaffrey, and K. I. Hodges, 2013a: The ability of CMIP5 models to simulate North Atlantic extratropical cyclones. J. Climate, 26, 53795396, https://doi.org/10.1175/JCLI-D-12-00501.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zappa, G., L. C. Shaffrey, K. I. Hodges, P. G. Sansom, and D. B. Stephenson, 2013b: A multimodel assessment of future projections of North Atlantic and European extratropical cyclones in the CMIP5 climate models. J. Climate, 26, 58465862, https://doi.org/10.1175/JCLI-D-12-00573.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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