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Multidecadal to centennial surface wintertime wind variability over Northeastern North America via statistical downscaling

  • Etor E. Lucio-EceizaEmail author
  • J. Fidel González-Rouco
  • Elena García-Bustamante
  • Jorge Navarro
  • Hugo Beltrami
Article

Abstract

The variability of the surface wind field over Northeastern North America was analysed through a statistical downscaling (SD) approach, using the relationships among the main large-scale and observed wind circulation modes. The large-scale variables were provided by 12 global reanalyses. The observed zonal and meridional wind components come from a database of 525 sites spanning over 1953–2010. A large percentage of the regional variability was explained in terms of three major large- and regional/local-scale coupled circulation patterns, accounting for 55.3% (59.3%) of the large (regional/local) scale variability. The method delivered robust results regardless of the SD model configuration, albeit with sensitivity to the number of retained circulation modes and the large-scale window size, but not to the reanalysis chosen for the large-scale variables. The methodological uncertainty was larger for sites/wind components with larger variability. A parameter configuration chosen for yielding the best possible SD estimations showed high correlation values between these estimations and the observations for the majority of the sites (0.6–0.9, significant at \(p<0.05\)), and a realistic wind variance (standard deviation ratios between 0.6 and 1.0), with similar results regardless of the reanalysis. The reanalysis direct wind outputs showed higher correlations than the SD estimates (0.7–0.97, also significant). The skill in reproducing observational variance differed considerably from model to model (ratios between 0.5 and 3). The regional wind climatology was reconstructed back to 1850 with the help of century long reanalyses and two additional SLP gridded datasets allowing to estimate the variability at decadal and multidecadal timescales. Recent trends in the wind components are not unusual in the context of century-long reconstructed variability. Extreme values in both components tend to appear associated with high values in the first two modes of variability.

Keywords

Surface wind Statistical downscaling Spatial and temporal variability Sensitivity Reanalysis intercomparison Past reconstructions Extreme events 

Notes

Acknowledgements

EELE was supported by the Agreement of Cooperation 4164281 between the UCM and St. Francis Xavier University, and the ILMODELS (CGL2014-59644-R) and NEWA (PCIN-2014-017-C07-06) projects of the MINECO (Spain). Funding for 4164281 was provided by the Natural Sciences and Engineering Research Council of Canada (NSERC DG 140576948), the Canada Research Chairs Program (CRC 230687), and the Atlantic Innovation Fund (AIF-ACOA). HB holds a Canada Research Chair in Climate Dynamics. EGB and JFGR held James Chair visiting Professorships (2017) at StFX University. JN, EGB and JFGR were supported by NEWA (PCIN-2014-017-C07-03, PCIN-2014-017-C07-06) and NEWA2 (PCIN-2016-176, PCIN-2016-009) projects of the MINECO (Spain). This research has been conducted under the Joint Research Unit between UCM and CIEMAT, by the Colaboration Agreement 7158/2016. pecial thanks to Douglas Schuster for information regarding the assimilation of surface wind land observations in NCAR-R1, DOE-R2 and CFSR reanalyses.

Note: a version of the observational data used in this study will be made to the public. Likewise, the wind climatologies showed in the manuscript will also be available. Potential users interested in having the data are invited to contact the corresponding author.

References

  1. Allan R, Ansell T (2006) A new globally complete monthly historical gridded mean sea level pressure dataset (hadslp2): 1850–2004. J Clim 19(22):5816–5842CrossRefGoogle Scholar
  2. Athanasiadis PJ, Wallace JM, Wettstein JJ (2010) Patterns of wintertime jet stream variability and their relation to the storm tracks. J Atmos Sci 67(5):1361–1381.  https://doi.org/10.1175/2009JAS3270.1 CrossRefGoogle Scholar
  3. Barnett T, Preisendorfer R (1987) Origins and levels of monthly and seasonal forecast skill for united states surface air temperatures determined by canonical correlation analysis. Mon Weather Rev 115:1825–1850CrossRefGoogle Scholar
  4. Barnston AG, Livezey RE (1987) Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Mon Weather Rev 115(6):1083–1126CrossRefGoogle Scholar
  5. Befort DJ, Wild S, Kruschke T, Ulbrich U, Leckebusch GC (2016) Different long-term trends of extra-tropical cyclones and windstorms in ERA-20C and NOAA-20CR reanalyses. Atmos Sci Lett 17(11):586–595.  https://doi.org/10.1002/asl.694 CrossRefGoogle Scholar
  6. Benestad RE (2001) A comparison between two empirical downscaling strategies. Int J Climatol 21:1645–1668.  https://doi.org/10.1002/joc.703 CrossRefGoogle Scholar
  7. Bollmeyer C, Keller JD, Ohlwein C, Wahl S, Crewell S, Friederichs P, Hense A, Keune J, Kneifel S, Pscheidt I, Redl S, Steinke S (2015) Towards a high-resolution regional reanalysis for the european CORDEX domain. Q J R Meteorol Soc 141(686):1–15.  https://doi.org/10.1002/qj.2486 CrossRefGoogle Scholar
  8. Bonsal BR, Shabbar A (2008) Impacts of large-scale circulation variability on low streamflows over Canada: a review. Can Water Resour J/Revue canadienne des ressources hydriques 33(2):137–154.  https://doi.org/10.4296/cwrj3302137 CrossRefGoogle Scholar
  9. Booth JF, Rieder HE, Lee DE, Kushnir Y (2015) The path of extratropical cyclones associated with wintertime high-wind events in the northeastern United states. J Appl Meteorol Climatol 54:1871–1885.  https://doi.org/10.1175/JAMC-D-14-0320.1 CrossRefGoogle Scholar
  10. Brinckmann S, Krähenmann S, Bissolli P (2016) High-resolution daily gridded data sets of air temperature and wind speed for Europe. Earth Syst Sci Data 8(2):491–516.  https://doi.org/10.5194/essd-8-491-2016. https://www.earth-syst-sci-data.net/8/491/2016/. Accessed 9 Oct 2017
  11. Cane MA (1986) El Niño. Annu Rev Earth Planet Sci 14:43–70.  https://doi.org/10.1017/CBO9781107415324.004 CrossRefGoogle Scholar
  12. Cattell RB (1966) The scree test for the number of factors. Multivar Behav Res 1(2):245–276CrossRefGoogle Scholar
  13. Cavazos T, Hewitson BC (2005) Performance of NCEP NCAR reanalysis variables in statistical downscaling of daily precipitation. Clim Res 28(MARCH):95–107Google Scholar
  14. Cheng CS (2014) Evidence from the historical record to support projection of future wind regimes: an application to Canada. Atmos Ocean 52(3):232–241.  https://doi.org/10.1080/07055900.2014.902803 CrossRefGoogle Scholar
  15. Cheng CS, Lopes E, Fu C, Huang Z (2014) Possible impacts of climate change on wind gusts under downscaled future climate conditions: updated for Canada. J Clim 27(3):1255–1270.  https://doi.org/10.1175/JCLI-D-13-00020.1 CrossRefGoogle Scholar
  16. CISL RDA (1979) Data Support Section, Computational and Information Systems Laboratory, National Center for Atmospheric Research, University Corporation for Atmospheric Research and National Weather Service, NOAA, U.S. Department of Commerce and Dept. of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology and Met Office, Ministry of Defence, United Kingdom and National Climatic Data Center, NESDIS, NOAA, U.S. Department of Commerce and Naval Research Laboratory, Monterey, U.S. Navy, U. S. Department of Defense and National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce. Daily Northern Hemisphere Sea Level Pressure Grids, continuing from 1899. http://rda.ucar.edu/datasets/ds010.0/. Accessed 6 May 2015
  17. CISL RDA (2007) Japan Meteorological Agency/Japan, and Central Research Institute of Electric Power Industry/Japan. Japanese 25-year Reanalysis Project. http://rda.ucar.edu/datasets/ds625.0/. Accessed 22 May 2015
  18. CISL RDA (2008) Japan Meteorological Agency/Japan, and Central Research Institute of Electric Power Industry/Japan. Japanese 25-year Reanalysis Project, Monthly Means. http://rda.ucar.edu/datasets/ds625.1/. Accessed 24 May 2015
  19. CISL RDA (2010) Saha, S., et al.: NCEP Climate Forecast System Reanalysis (CFSR) Monthly Products, January 1979 to December 2010.  https://doi.org/10.5065/D6DN438J, http://rda.ucar.edu/datasets/ds093.2/. Accessed 25 May 2015
  20. CISL RDA (2013) Japan Meteorological Agency/Japan. JRA-55: Japanese 55-year Reanalysis, Monthly Means and Variances. https://rda.ucar.edu/datasets/ds628.1/. Accessed 23 April 2015
  21. CISL RDA (2015a) Gilbert P. Compo, et al.: NOAA/CIRES Twentieth Century Global Reanalysis Version 2c. Updated yearly.  https://doi.org/10.5065/D6N877TW, http://rda.ucar.edu/datasets/ds131.2/. Accessed 4 June 2015
  22. CISL RDA (2015b) Meteorological Research Institute/Japan Meteorological Agency/Japan. JRA-55C: Monthly Means and Variances. https://rda.ucar.edu/datasets/ds628.3/. Accessed 10 May 2017
  23. Cleugh H, Miller J, Böhm M (1998) Direct mechanical effects of wind on crops. Agrofor Syst 41(1):85–112CrossRefGoogle Scholar
  24. Compo GP, Whitaker JS, Sardeshmukh PD, Matsui N, Allan RJ, Yin X, Gleason BE, Vose RS, Rutledge G, Bessemoulin P, BroNnimann S, Brunet M, Crouthamel RI, Grant AN, Groisman PY, Jones PD, Kruk MC, Kruger AC, Marshall GJ, Maugeri M, Mok HY, Nordli O, Ross TF, Trigo RM, Wang XL, Woodruff SD, Worley SJ (2011) The twentieth century reanalysis project. Q J R Meteorol Soc 137(654):1–28.  https://doi.org/10.1002/qj.776 CrossRefGoogle Scholar
  25. Conrad CT (2009) Severe and hazardous weather in canada: the geography of extreme events. Oxford University Press, OxfordGoogle Scholar
  26. Cram T, Compo GP, Yin X, Allan RJ, McColl C, Vose RS, Whitaker JS, Matsui N, Ashcroft L, Auchmann R, Bessemoulin P, Brandsma T, Brohan P, Brunet M, Comeaux J, Crouthamel R, Gleason BE, Groisman PY, Hersbach H, Jones PD, Jónsson T, Jourdain S, Kelly G, Knapp KR, Kruger A, Kubota H, Lentini G, Lorrey A, Lott N, Lubker SJ, Luterbacher J, Marshall GJ, Maugeri M, Mock CJ, Mok HY, Oy N, Rodwell MJ, Ross TF, Schuster D, Srnec L, Valente MA, Vizi Z, Wang XL, Westcott N, Woollen JS, Worley SJ (2015) The international surface pressure databank version 2. Geosci Data J 2(1):31–46.  https://doi.org/10.1002/gdj3.25 CrossRefGoogle Scholar
  27. Culver AMR, Monahan AH (2013) The statistical predictability of surface winds over western and central Canada. J Clim 26(21):8305–8322.  https://doi.org/10.1175/JCLI-D-12-00425.1 CrossRefGoogle Scholar
  28. Curry CL, van der Kamp D, Monahan AH (2012) Statistical downscaling of historical monthly mean winds over a coastal region of complex terrain. I. Predicting wind components. Clim Dyn 38:1281–1299.  https://doi.org/10.1007/s00382-011-1175-1 CrossRefGoogle Scholar
  29. Darby LS (2005) Cluster analysis of surface winds in Houston, Texas, and the impact of wind patterns on ozone. J Appl Meteorol 44(12):1788–1806CrossRefGoogle Scholar
  30. Dee D, Uppala S, Simmons A, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda M, Balsamo G, Bauer P (2011) The era-interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597.  https://doi.org/10.1002/qj.828 CrossRefGoogle Scholar
  31. Ebita A, Kobayashi S, Ota Y, Moriya M, Kumabe R, Onogi K, Harada Y, Yasui S, Miyaoka K, Takahashi K, Kamahori H, Kobayashi C, Endo H, Soma M, Oikawa Y, Ishimizu T (2011) The Japanese 55-year Reanalysis jra-55: an interim report. Sola 7:149–152.  https://doi.org/10.2151/sola.2011-038 CrossRefGoogle Scholar
  32. Farquhar G, Roderick M (2005) Worldwide changes in evaporative demand. Water Environ 12:81–99Google Scholar
  33. Ferguson CR, Villarini G (2014) An evaluation of the statistical homogeneity of the twentieth century reanalysis. Clim Dyn 42(11–12):2841–2866.  https://doi.org/10.1007/s00382-013-1996-1 CrossRefGoogle Scholar
  34. Fowler H, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27(12):1547–1578.  https://doi.org/10.1002/joc.1556 CrossRefGoogle Scholar
  35. Frias MD, Zorita E, Fernandez J, Rodriguez-Puebla C (2006) Testing statistical downscaling methods in simulated climates. Geophys Res Lett 33(19):1–5.  https://doi.org/10.1029/2006GL027453 CrossRefGoogle Scholar
  36. Fujiwara M, Wright JS, Manney GL, Gray LJ, Anstey J, Birner T, Davis S, Gerber EP, Lynn Harvey V, Hegglin MI, Homeyer CR, Knox JA, Krüger K, Lambert A, Long CS, Martineau P, Molod A, Monge-Sanz BM, Santee ML, Tegtmeier S, Chabrillat S, Tan DG, Jackson DR, Polavarapu S, Compo GP, Dragani R, Ebisuzaki W, Harada Y, Kobayashi C, McCarty W, Onogi K, Pawson S, Simmons A, Wargan K, Whitaker JS, Zou CZ (2017) Introduction to the SPARC Reanalysis Intercomparison Project (S-RIP) and overview of the reanalysis systems. Atmos Chem Phys 17(2):1417–1452.  https://doi.org/10.5194/acp-17-1417-2017 CrossRefGoogle Scholar
  37. García-Bustamante E, González-Rouco JF, Pa J, Navarro J, Montávez JP (2008) The influence of the Weibull assumption in monthly wind energy estimation. Wind Energy 11(5):483–502.  https://doi.org/10.1002/we.270 CrossRefGoogle Scholar
  38. García-Bustamante E, González-Rouco J, Jiménez P, Navarro J, Montávez J (2009) A comparison of methodologies for monthly wind energy estimation. Wind Energy 12(7):640–659.  https://doi.org/10.1002/we.315 CrossRefGoogle Scholar
  39. García-Bustamante E, González-Rouco JF, Navarro J, Xoplaki E, Pa J, Montávez JP (2011) North Atlantic atmospheric circulation and surface wind in the Northeast of the Iberian Peninsula: uncertainty and long term downscaled variability. Clim Dyn 38(1–2):141–160.  https://doi.org/10.1007/s00382-010-0969-x CrossRefGoogle Scholar
  40. García-Bustamante E, González-Rouco JF, Navarro J, Xoplaki E, Luterbacher J, Jiménez PA, Montávez JP, Hidalgo A, Lucio-Eceiza EE (2012) Relationship between wind power production and North Atlantic atmospheric circulation over the northeastern Iberian Peninsula. Clim Dyn 40:935–949.  https://doi.org/10.1007/s00382-012-1451-8 CrossRefGoogle Scholar
  41. González-Rouco JF, Heyen H, Zorita E, Valero F (2000) Agreement between observed rainfall trends and climate change simulations in the Southwest of Europe. J Clim 13(17):3057–3065.  https://doi.org/10.1175/1520-0442(2000)013<3057:ABORTA>2.0.CO;2 CrossRefGoogle Scholar
  42. Grise KM, Son SW, Gyakum JR (2013) Intraseasonal and interannual variability in North American storm tracks and its relationship to equatorial pacific variability. Mon Weather Rev 141(10):3610–3625.  https://doi.org/10.1175/MWR-D-12-00322.1 CrossRefGoogle Scholar
  43. Gulev SK, Zolina O, Grigoriev S (2001) Extratropical cyclone variability in the Northern Hemisphere winter from the NCEP/NCAR reanalysis data. Clim Dyn 17(10):795–809.  https://doi.org/10.1007/s003820000145 CrossRefGoogle Scholar
  44. Hart RE, Evans JL (2001) A climatology of the extratropical transition of Atlantic tropical cyclones. J Clim 14(4):546–564.  https://doi.org/10.1175/1520-0442(2001)014<0546:ACOTET>2.0.CO;2 CrossRefGoogle Scholar
  45. Hayden BP (1981) Secular variation in atlantic coast extratropical cyclones. Mon Weather Rev 109(January):159–167CrossRefGoogle Scholar
  46. Hersbach H, Poli P, Dee D (2015) The observation feedback archive for the ICOADS and ISPD data sets (ERA-20C). Report Series 18. Tech. rep., ECMWFGoogle Scholar
  47. Hertig E, Jacobeit J (2014) Considering observed and future nonstationarities in statistical downscaling of Mediterranean precipitation. Theor Appl Climatol 122:667–683.  https://doi.org/10.1007/s00704-014-1314-9 CrossRefGoogle Scholar
  48. Hertig E, Paxian A, Vogt G, Seubert S, Paeth H, Jacobeit J (2012) Statistical and dynamical downscaling assessments of precipitation extremes in the Mediterranean area. Meteorologische Zeitschrift 21(1):61–77.  https://doi.org/10.1127/0941-2948/2012/0271 CrossRefGoogle Scholar
  49. Hughes L, Chaudhry N (2011) The challenge of meeting Canadas greenhouse gas reduction targets. Energy Policy 39(3):1352–1362.  https://doi.org/10.1016/j.enpol.2010.12.007 CrossRefGoogle Scholar
  50. Hurrell JW (1995) Decadal trends in the North Atlantic oscillation: regional temperatures and precipitation. Science (New York, NY) 269(5224):676–9.  https://doi.org/10.1126/science.269.5224.676 CrossRefGoogle Scholar
  51. Huth R (2002) Statistical downscaling of daily temperature in central Europe. J Clim 15(13):1731–1742.  https://doi.org/10.1175/1520-0442(2002)015<1731:SDODTI>2.0.CO;2 CrossRefGoogle Scholar
  52. Isard S, Angel JR, VanDyke GT (2000) Zones of origin for Great Lakes Cyclones in North America, 1899–1996. Mon Weather Rev 28(2):474.  https://doi.org/10.1175/1520-0493(2000)128<0474:ZOOFGL>2.0.CO;2 CrossRefGoogle Scholar
  53. Jakob Themeßl M, Gobiet A, Leuprecht A (2011) Empirical-statistical downscaling and error correction of daily precipitation from regional climate models. Int J Climatol 31(10):1530–1544.  https://doi.org/10.1002/joc.2168 CrossRefGoogle Scholar
  54. Jiménez P, González-Rouco J, García-Bustamante E, Navarro J, Montávez J, de Arellano J, Dudhia J, Muñoz-Roldan A (2010) Surface wind regionalization over complex terrain: evaluation and analysis of a high-resolution wrf simulation. J Appl Meteorol Climatol 49(2):268–287.  https://doi.org/10.1175/2009JAMC2175.1 CrossRefGoogle Scholar
  55. Jiménez PA, González-Rouco JF, Montávez JP, García-Bustamante E (2008) Climatology of wind patterns in the northeast of the Iberian Peninsula. Int J Climatol 29:501–525.  https://doi.org/10.1002/joc CrossRefGoogle Scholar
  56. Kaas E, Li TS, Schmith T (1996) Statistical hindcast of wind climatology in the north atlantic and northwestern european region. Clim Res 7(2):97–110CrossRefGoogle Scholar
  57. Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77(3):437–471.  https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2 CrossRefGoogle Scholar
  58. van der Kamp D, Curry CL, Monahan AH (2012) Statistical downscaling of historical monthly mean winds over a coastal region of complex terrain. II. Predicting wind components. Clim Dyn 38:1301–1311.  https://doi.org/10.1007/s00382-011-1175-1 CrossRefGoogle Scholar
  59. Kanamitsu M, Ebisuzaki W, Woollen J, Yang SK, Hnilo JJ, Fiorino M, Potter GL (2002) NCEP-DOE AMIP-II reanalysis (R-2). Bull Am Meteorol Soc 83(11):1631–1643+1559.  https://doi.org/10.1175/BAMS-83-11-1631 CrossRefGoogle Scholar
  60. Khanduri A, Morrow G (2003) Vulnerability of buildings to windstorms and insurance loss estimation. J Wind Eng Ind Aerodyn 91(4):455–467CrossRefGoogle Scholar
  61. Klink K (1999a) Climatological mean and interannual variance of United States surface wind speed, direction and velocity. Int J Climatol 19(5):471–488.  https://doi.org/10.1002/(SICI)1097-0088(199904)19:5<471::AID-JOC367>3.0.CO;2-X CrossRefGoogle Scholar
  62. Klink K (1999b) Trends in mean monthly maximum and minimum surface wind speeds in the coterminous United States, 1961 to 1990. Clim Res 13(3):193–205.  https://doi.org/10.3354/cr013193 CrossRefGoogle Scholar
  63. Kobayashi C, Endo H, Ota Y, Kobayashi S, Onoda H, Harada Y, Onogi K, Kamahori H (2014) Preliminary results of the jra-55c, an atmospheric reanalysis assimilating conventional observations only. Sola 10:78–82.  https://doi.org/10.2151/sola.2014-016 CrossRefGoogle Scholar
  64. Laloyaux P, Balmaseda M, Dee D, Mogensen K, Janssen P (2016) A coupled data assimilation system for climate reanalysis. Q J R Meteorol Soc 142(694):65–78.  https://doi.org/10.1002/qj.2629 CrossRefGoogle Scholar
  65. Lindsay R, Wensnahan M, Schweiger A, Zhang J (2014) Evaluation of seven different atmospheric reanalysis products in the Arctic. J Clim 27(7):2588–2606.  https://doi.org/10.1175/JCLI-D-13-00014.1 CrossRefGoogle Scholar
  66. Lucio-Eceiza EE, González-Rouco JF, Navarro J, Beltrami H (2018a) Quality Control of surface wind observations in North Eastern North America. Part I: Data management issues. J Atmos Ocean Technol 35:163–182.  https://doi.org/10.1175/JTECH-D-16-0204.1 CrossRefGoogle Scholar
  67. Lucio-Eceiza EE, González-Rouco JF, Navarro J, Beltrami H, Conte J (2018b) Quality Control of surface wind observations in North Eastern North America. Part II: Measurement errors. J Atmos Ocean Technol 35:183–205.  https://doi.org/10.1175/JTECH-D-16-0205.1 CrossRefGoogle Scholar
  68. Mailier PJ, Stephenson DB, CaT F, Hodges KI (2006) Serial clustering of extratropical cyclones. Mon Weather Rev 134(8):2224–2240.  https://doi.org/10.1175/MWR3160.1 CrossRefGoogle Scholar
  69. Mantua NJ, Hare SR, Zhang Y, Wallace JM, Francis RC (1997) A Pacific interdecadal climate oscillation with impacts on salmon production. Bull Am Meteorol Soc 78(January):1069–1079.  https://doi.org/10.1175/1520-0477(1997)078h1069:APICOWi2.0.CO;2 CrossRefGoogle Scholar
  70. Martinez Y, Yu W, Lin H (2013) A new statistical-dynamical downscaling procedure based on eof analysis for regional time series generation. J Appl Meteorol Climatol 52(4):935–952.  https://doi.org/10.1175/JAMC-D-11-065.1 CrossRefGoogle Scholar
  71. McVicar TR, Roderick ML, Donohue RJ, Li LT, Van Niel TG, Thomas A, Grieser J, Jhajharia D, Himri Y, Mahowald NM, Mescherskaya AV, Kruger AC, Rehman S, Dinpashoh Y (2012) Global review and synthesis of trends in observed terrestrial near-surface wind speeds: implications for evaporation. J Hydrol 416–417:182–205.  https://doi.org/10.1016/j.jhydrol.2011.10.024 CrossRefGoogle Scholar
  72. Mesinger F, DiMego G, Kalnay E, Mitchell K, Shafran PC, Ebisuzaki W, Jović D, Woollen J, Rogers E, Berbery EH, Ek MB, Fan Y, Grumbine R, Higgins W, Li H, Lin Y, Manikin G, Parrish D, Shi W (2006) North American regional reanalysis. Bull Am Meteorol Soc 87(3):343–360.  https://doi.org/10.1175/BAMS-87-3-343 CrossRefGoogle Scholar
  73. Najac J, Boé J, Terray L (2009) A multi-model ensemble approach for assessment of climate change impact on surface winds in France. Clim Dyn 32(5):615–634.  https://doi.org/10.1007/s00382-008-0440-4 CrossRefGoogle Scholar
  74. National Center for Atmospheric Research (2016) The Climate Data Guide: Hurrell North Atlantic Oscillation (NAO) Index (PC-based)Google Scholar
  75. North GR, Moeng FJ, Bell TL, Cahalan RF, Moeng FJ, Bell TL, Cahalan RF (1982) The latitude dependence of the variance of zonally averaged quantities. Mon Weather Rev 110(5):319–326.  https://doi.org/10.1175/1520-0493(1982)110<0319:TLDOTV>2.0.CO;2 CrossRefGoogle Scholar
  76. Ogi M, Tachibana Y, Yamazaki K (2003) Impact of the wintertime north atlantic oscillation (nao) on the summertime atmospheric circulation. Geophys Res Lett 22:22.  https://doi.org/10.1029/2003GL017280 CrossRefGoogle Scholar
  77. Onogi K, Tsutsi J, Koide H, Sakamoto M, Kobayashi S, Hatsushika H, Matsumoto T, Yamazaki N, Kamahori H, Takahashi K, Kadokura S, Wada K, Kato K, Oyama R, Ose T, Mannoji N, Taira R (2007) The JRA-25 reanalysis. J Meteorol Soc Jpn 85(3):369–432.  https://doi.org/10.2151/jmsj.85.369 CrossRefGoogle Scholar
  78. Plante M, Son SW, Atallah E, Gyakum J, Grise K (2014) Extratropical cyclone climatology across eastern Canada. Int J Climatol 35(10):2759–2776.  https://doi.org/10.1002/joc.4170 CrossRefGoogle Scholar
  79. Poli P, Hersbach H, Dee DP, Berrisford P, Simmons AJ, Vitart F, Laloyaux P, Tan DGH, Peubey C, Thépaut JN, Trémolet Y, Hólm EV, Bonavita M, Isaksen L, Fisher M (2016) ERA-20C: An atmospheric reanalysis of the twentieth century. J Clim 29(11):4083–4097.  https://doi.org/10.1175/JCLI-D-15-0556.1 CrossRefGoogle Scholar
  80. Pryor SC, Barthelmie RJ (2014) Hybrid downscaling of wind climates over the eastern USA. Environ Res Lett 9(2):024013.  https://doi.org/10.1088/1748-9326/9/2/024013 CrossRefGoogle Scholar
  81. Pryor SC, Schoof JT, Barthelmie RJ (2005) Climate change impacts on wind speeds and wind energy density in Northern Europe: empirical downscaling of multiple AOGCMs. Clim Res 29(3):183–198.  https://doi.org/10.3354/cr029183 CrossRefGoogle Scholar
  82. Pryor SC, Schoof JT, Barthelmie RJ (2006) Winds of change?: Projections of near-surface winds under climate change scenarios. Geophys Res Lett 33(11):1–5.  https://doi.org/10.1029/2006GL026000 CrossRefGoogle Scholar
  83. Pryor SC, Barthelmie RJ, Young DT, Takle ES, Arritt RW, Flory D, Jr WJG, Nunes A, Roads J (2009) Wind speed trends over the contiguous United States. J Geophys Res 114:18.  https://doi.org/10.1029/2008JD011416 CrossRefGoogle Scholar
  84. Pryor SC, Barthelmie RJ, Schoof JT (2012) Past and future wind climates over the contiguous USA based on the North American Regional Climate Change Assessment Program model suite. J Geophys Res 117:1–17.  https://doi.org/10.1029/2012JD017449 CrossRefGoogle Scholar
  85. Rasmusson EM, Wallace JM (1983) Meterogical aspects of the El Niño. Science 222:1195–1202.  https://doi.org/10.1126/science.222.4629.1195 CrossRefGoogle Scholar
  86. REN21 (2017) Renewables 2017 global status report. (Paris: REN21 Secretariat). ISBN: 978-3-9818107-0-7.  https://doi.org/10.1016/j.rser.2016.09.082
  87. Richards W, Abuamer Y (2007) Atmospheric hazards: extreme wind gust climatology in Atlantic Canada 1955–2000. Tech. rep, Meteorological Service of Canada, AtlanticGoogle Scholar
  88. Richman MB (1986) Rotation of principal components. J Climatol 6(3):293–335.  https://doi.org/10.1002/joc.3370060305 CrossRefGoogle Scholar
  89. Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Bosilovich MG, Schubert SD, Takacs L, Kim GK, Bloom S, Chen J, Collins D, Conaty A, Da Silva A, Gu W, Joiner J, Koster RD, Lucchesi R, Molod A, Owens T, Pawson S, Pegion P, Redder CR, Reichle R, Robertson FR, Ruddick AG, Sienkiewicz M, Woollen J (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24(14):3624–3648.  https://doi.org/10.1175/JCLI-D-11-00015.1 CrossRefGoogle Scholar
  90. Ropelewski CF, Jones PD (1987) An extension of the Tahiti Darwin Southern Oscillation Index. Mon Weather Rev 115:2161–2165.  https://doi.org/10.1175/1520-0493(1987)115h2161:AEOTTSi2.0.CO;2 CrossRefGoogle Scholar
  91. Saha S, Moorthi S, Pan HL, Wu X, Wang J, Nadiga S, Tripp P, Kistler R, Woollen J, Behringer D, Liu H, Stokes D, Grumbine R, Gayno G, Wang J, Hou YT, Chuang HY, Juang HMH, Sela J, Iredell M, Treadon R, Kleist D, Van Delst P, Keyser D, Derber J, Ek M, Meng J, Wei H, Yang R, Lord S, Van Den Dool H, Kumar A, Wang W, Long C, Chelliah M, Xue Y, Huang B, Schemm JK, Ebisuzaki W, Lin R, Xie P, Chen M, Zhou S, Higgins W, Zou CZ, Liu Q, Chen Y, Han Y, Cucurull L, Reynolds RW, Rutledge G, Goldberg M (2010) The NCEP climate forecast system reanalysis. Bull Am Meteorol Soc 91(8):1015–1057.  https://doi.org/10.1175/2010BAMS3001.1 CrossRefGoogle Scholar
  92. Siegismund F, Schrum C (2001) Decadal changes in the wind forcing over the north sea. Clim Res 18:39–45.  https://doi.org/10.3354/cr018039 CrossRefGoogle Scholar
  93. Stewart R, Bachand D, Dunkley R, Giles A, Lawson B, Legal L, Miller S, Murphy B, Parker M, Paruk B (1995) Winter storms over canada. Atmos Ocean 33(2):223–247.  https://doi.org/10.1080/07055900.1995.9649533 CrossRefGoogle Scholar
  94. von Storch H, Zwiers FW (2003) Statistical analysis in climate research. Cambridge University Press, CambridgeGoogle Scholar
  95. Storch H, Zorita E, Cubasch U (1993) Downscaling of global climate change estimates to regional scales: an application to Iberian rainfall in wintertime. J Clim 6:1161–1171.  https://doi.org/10.1175/1520-0442(1993)006<1161:DOGCCE>2.0.CO;2 CrossRefGoogle Scholar
  96. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106(D7):7183–7192.  https://doi.org/10.1029/2000JD900719 CrossRefGoogle Scholar
  97. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of cmip5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498.  https://doi.org/10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  98. Thomas BC, Martin JE (2007) A synoptic climatology and composite analysis of the alberta clipper. Weather Forecast 22(2):315–333.  https://doi.org/10.1175/WAF982.1 CrossRefGoogle Scholar
  99. Thompson DWJ, Wallace JM (1998) The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys Res Lett 25(9):1297.  https://doi.org/10.1029/98GL00950 CrossRefGoogle Scholar
  100. Thompson DWJ, Wallace JM (2000a) Annular mode in the extratropical circulation. Part I : month-to-month variability. J Clim 13(1999):1000–1016.  https://doi.org/10.1175/1520-0442(2000)013<1000:AMITEC>2.0.CO;2 CrossRefGoogle Scholar
  101. Thompson DWJ, Wallace JM (2000b) Annular modes in the extratropical circulation. Part II: trends. J Clim 13(5):1018–1036.  https://doi.org/10.1175/1520-0442(2000)013<1018:AMITEC>2.0.CO;2 CrossRefGoogle Scholar
  102. Torralba V, Doblas-Reyes FJ, González-Reviriego N (2017) Uncertainty in recent near-surface wind speed trends: a global reanalysis intercomparisonparison. Environ Res Lett 12:10CrossRefGoogle Scholar
  103. Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteorol Anal 79(1):61–78.  https://doi.org/10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2 CrossRefGoogle Scholar
  104. Trenberth KE (1984) Signal versus noise in the southern oscillation. Mon Weather Rev 112:326–332.  https://doi.org/10.1175/1520-0493(1984)112<0326:SVNITS>2.0.CO;2 CrossRefGoogle Scholar
  105. Trenberth KE, Hurrell JW (1994) Decadal atmosphere-ocean variations in the Pacific. Clim Dyn 9(6):303–319.  https://doi.org/10.1007/BF00204745 CrossRefGoogle Scholar
  106. Tuller SE (2004) Measured wind speed trends on the west coast of Canada. Int J Climatol 24(11):1359–1374.  https://doi.org/10.1002/joc.1073 CrossRefGoogle Scholar
  107. Ulbrich U, Leckebusch GC, Pinto JG (2009) Extra-tropical cyclones in the present and future climate: a review. Theor Appl Climatol 96(1–2):117–131.  https://doi.org/10.1007/s00704-008-0083-8 CrossRefGoogle Scholar
  108. Uppala SM, Kallberg PW, Simmons AJ, Andrae U, Bechtold VDC, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, Berg LVD, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Hólm E, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, Mcnally AP, Mahfouf JF, Morcrette JJ, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131(612):2961–3012.  https://doi.org/10.1256/qj.04.176 CrossRefGoogle Scholar
  109. Wallbrink H, Koek F, Brandsma T (2009) The US Maury collection metadata 1796–1861. Koninklijk Nederlands Meteorologisch InstituutGoogle Scholar
  110. Wan H, Wang XL, Swail VR (2010) Homogenization and trend analysis of Canadian near-surface wind speeds. J Clim 23(5):1209.  https://doi.org/10.1175/2009JCLI3200.1 CrossRefGoogle Scholar
  111. Wang XL, Wan H, Swail VR (2006) Observed changes in cyclone activity in Canada and their relationships to major circulation regimes. J Clim 19:896–915.  https://doi.org/10.1175/JCLI3664.1 CrossRefGoogle Scholar
  112. Wang XL, Feng Y, Compo GP, Swail VR, Zwiers FW, Allan RJ, Sardeshmukh PD (2013) Trends and low frequency variability of extra-tropical cyclone activity in the ensemble of twentieth century reanalysis. Clim Dyn 40(11–12):2775–2800.  https://doi.org/10.1007/s00382-012-1450-9 CrossRefGoogle Scholar
  113. Wang YH, Magnusdottir G, Stern H, Tian X, Yu Y (2012) Decadal variability of the NAO: introducing an augmented NAO index. Geophys Res Lett 39(21):1–5.  https://doi.org/10.1029/2012GL053413 CrossRefGoogle Scholar
  114. Wilby RL, Charles SP, Zorita E, Timbal B, Whetton P, Mearns LO (2004) Guidelines for use of climate scenarios developed from statistical downscaling methods. Tech. Rep. August, http://www.narccap.ucar.edu/doc/tgica-guidance-2004.pdf. Accessed 28 Dec 2016
  115. Wiser R, Bolinger M (2016) 2015 Wind technologies market report. Tech. Rep. August, U.S. Department of EnergyGoogle Scholar
  116. WMO (2011) Guide to climatological practices WMO-No. 100, 2011th edn. 100, World Meteorological Organization (WMO), Geneva, Switzerland, WMO-No. 100Google Scholar
  117. 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(5):714–732.  https://doi.org/10.1002/joc.4015 CrossRefGoogle Scholar
  118. Woodruff SD, Diaz HF, Worley SJ, Reynolds RW, Lubker SJ (2005) Early ship observational data and icoads. Clim Change 73(1):169–194.  https://doi.org/10.1007/s10584-005-3456-3 CrossRefGoogle Scholar
  119. Wu J, Zha J, Zhao D (2016) Evaluating the effects of land use and cover change on the decrease of surface wind speed over China in recent 30 years using a statistical downscaling method. Clim Dyn 48:1–19.  https://doi.org/10.1007/s00382-015-2616-z CrossRefGoogle Scholar
  120. Xoplaki E, González-Rouco JF, Luterbacher J, Wanner H (2003) Mediterranean summer air temperature variability and its connection to the large-scale atmospheric circulation and SSTs. Clim Dyn 20(7–8):723–739.  https://doi.org/10.1007/s00382-003-0304-x CrossRefGoogle Scholar
  121. Xoplaki E, González-Rouco JF, Luterbacher J, Wanner H (2004) Wet season Mediterranean precipitation variability: influence of large-scale dynamics and trends. Clim Dyn 23(1):63–78.  https://doi.org/10.1007/s00382-004-0422-0 CrossRefGoogle Scholar
  122. Zhang Y, Wallace JM, Battisti DS (1997) ENSO-like interdecadal variability: 1900–93. J Clim 10(5):1004–1020.  https://doi.org/10.1175/1520-0442(1997)010<1004:ELIV>2.0.CO;2 CrossRefGoogle Scholar
  123. Zha J, Wu J, Zhao D, Yang Q (2017) Changes of the probabilities in different ranges of near-surface wind speed in China during the period for 1970–2011. J Wind Eng Ind Aerodyn 169:156–167.  https://doi.org/10.1016/j.jweia.2017.07.019 CrossRefGoogle Scholar
  124. Zielinski G (2002) A classification scheme for winter storms in the Eastern and Central United States with an emphasis on Nor’easters. Bull Am Meteorol Soc 83(1):37–51.  https://doi.org/10.1175/1520-0477(2002)083<0037:ACSFWS>2.3.CO;2 CrossRefGoogle Scholar
  125. Zorita E, von Storch H (1999) The analog method as a simple statistical downscaling technique: comparison with more complicated methods. J Clim 12(8 PART 2):2474–2489.  https://doi.org/10.1175/1520-0442(1999)012<2474:TAMAAS>2.0.CO;2 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Facultad de CC. FísicasUniversidad Complutense MadridMadridSpain
  2. 2.Instituto de Geociencias (UCM-CSIC)MadridSpain
  3. 3.Dpto. Física de la Tierra y Astrofísica, Fac. CC. FísicasUniversidad Complutense MadridMadridSpain
  4. 4.División de Energías RenovablesCIEMATMadridSpain
  5. 5.Climate and Atmospheric Sciences InstituteSt. Francis Xavier UniversityAntigonishCanada

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