Journal of Meteorological Research

, Volume 33, Issue 1, pp 149–158 | Cite as

Simulation and Projection of Near-Surface Wind Speeds in China by BCC-CSM Models

  • Yajun Xiong
  • Xiaoge XinEmail author
  • Xingxia Kou
Regular Articles


We evaluated the ability of the Beijing Climate Center models on different horizontal resolutions (BCC-CSM1.1 on approximately 280-km resolution and BCC-CSM1.1m on approximately 110-km resolution) in simulating the nearsurface wind speeds (NWS) in China during 1961–2005. The spatial distribution of the annual mean NWS over China is better captured by BCC-CSM1.1m than by BCC-CSM1.1 due to the finer resolution. The weakened NWS over China during 1961–2005 cannot be reproduced by BCC-CSM1.1, whereas BCC-CSM1.1m is able to simulate the decreasing trend of the autumn NWS in North China, although the magnitude is about 1/3 of the observed value. This is attributed to the better performance of this finer-resolution model in reproducing the increase in sea level pressure over Mongolia and North China over the past 45 years. The results suggest that increasing the horizontal resolution of the BCC-CSM model has improved its ability in reproducing the spatial distribution and long-term changes of NWS over China. Future projections by BCC-CSM1.1m under different Representative Concentration Pathway (RCP) scenarios demonstrate that the autumn NWS in North China will decrease during the 21st century under both the middle (RCP4.5) and high (RCP8.5) emission scenarios, with a higher decreasing rate under RCP8.5.

Key words

wind speed simulation projection BCC-CSM Representative Concentration Pathway (RCP) 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bucchignani, E., A. L. Zollo, L. Cattaneo, et al., 2016: Extreme weather events over China: Assessment of COSMO-CLM simulations and future scenarios. Int. J. Climatol., 37: 1578–1594, doi: 10.1002/joc.4798.CrossRefGoogle Scholar
  2. Chen, H. P., and H. J. Wang, 2015: Haze days in North China and the associated atmospheric circulations based on daily visibility data from 1960 to 2012. J. Geophys. Res. Atmos., 120: 5895–5909, doi: 10.1002/2015JD023225.CrossRefGoogle Scholar
  3. Griffies, S. M., A. Gnanadesikan, K. W. Dixon, et al., 2005: Formulation of an ocean model for global climate simulations. Ocean Sci., 1: 45–79, doi: 10.5194/os-1-45-2005.CrossRefGoogle Scholar
  4. Guo, L. J., X. L. Guo, C. G. Fang, et al., 2015: Observation analysis on characteristics of formation, evolution and transition of a long-lasting severe fog and haze episode in North China. Sci. China Earth Sci., 58: 329–344, doi: 10.1007/s11430-014-4924-2.CrossRefGoogle Scholar
  5. Ji, J. J., M. Huang, and K. R. Li, 2008: Prediction of carbon exchanges between China terrestrial ecosystem and atmosphere in 21st century. Sci. China Ser. D Earth Sci., 51: 885–898, doi: 10.1007/s11430-008-0039-y.CrossRefGoogle Scholar
  6. Jiang, Y., Y. Luo, and Z. C. Zhao, 2009: Evaluation of wind speeds in China as simulated by global climate models. Acta Meteor. Sinica, 67: 923–934, doi: 10.11676/qxxb2009.090. (in Chinese)Google Scholar
  7. Jiang, Y., Y. Luo, and Z. C. Zhao, 2010: Projection of wind speed changes in China in the 21st century by climate models. Chinese J. Atmos. Sci., 2: 323–336, doi: 10.3878/j.issn.1006-9895.2010.02.07. (in Chinese)Google Scholar
  8. Jiang, Y., X. Y. Xu, H. W. Liu, et al., 2017: The underestimated magnitude and decline trend in near-surface wind over China. Atmos. Sci. Lett., 18: 475–483, doi: 10.1002/asl.791.CrossRefGoogle Scholar
  9. Kalnay, E., M. Kanamitsu, R. Kistler, et al., 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77: 437–472, doi: 10.1175/1520-0477(1996)077<0437:TNY RP>2.0.CO;2.CrossRefGoogle Scholar
  10. Kumar, D., V. Mishra, and A. R. Ganguly, 2015: Evaluating wind extremes in CMIP5 climate models. Climate Dyn., 45: 441–453, doi: 10.1007/s00382-014-2306-2.CrossRefGoogle Scholar
  11. Niu, F., Z. Q. Li, C. Li, et al., 2010: Increase of wintertime fog in China: Potential impacts of weakening of the eastern Asian monsoon circulation and increasing aerosol loading. J. Geophys. Res. Atmos., 115, D00K20, doi: 10.1029/2009JD013484.CrossRefGoogle Scholar
  12. Pei, L., Z. W. Yan, Z. B. Sun, et al., 2018: Increasing persistent haze in Beijing: Potential impacts of weakening East Asian winter monsoons associated with northwestern Pacific sea surface temperature trends. Atmos. Chem. Phys., 18: 3173–3183, doi: 10.5194/acp-18-3173-2018.CrossRefGoogle Scholar
  13. Sun, B., and H. J. Wang, 2015: Interdecadal transition of the leading mode of interannual variability of summer rainfall in East China and its associated atmospheric water vapor transport. Climate Dyn., 44: 2703–2722, doi: 10.1007/s00382-014-2251-0.CrossRefGoogle Scholar
  14. Trenberth, K. E., 1984: Some effects of finite sample size and persistence on meteorological statistics. Part II: Potential predictability. Mon. Wea. Rev., 112: 2369–2379, doi: 10.1175/1520-0493(1984)112<2369:SEOFSS>2.0.CO;2. Van Vuuren, D. P., J. Edmonds, M. Kainuma, et al., 2011: The representative concentration pathways: An overview. Climatic Change, 109: 5–31, doi: 10.1007/s10584-011-0148-z.Google Scholar
  15. Wang, Z. Y., Y. H. Ding, J. H. He, et al., 2004: An updated analysis of the climate change in China in recent 50 years. Acta Meteor. Sinica, 62: 228–236, doi: 10.11676/qxxb2004.023. (in Chinese)Google Scholar
  16. Wu, J., and X. J. Gao, 2013: A gridded daily observation dataset over China region and comparison with the other datasets. Chinese J. Geophys., 56: 1102–1111, doi: 10.6038/cjg2013 0406. (in Chinese)Google Scholar
  17. Wu, J., X. J. Gao, F. Giorgi, et al., 2017: Changes of effective temperature and cold/hot days in late decades over China based on a high resolution gridded observation dataset. Int. J. Climatol., 37: 788–800, doi: 10.1002/joc.5038.CrossRefGoogle Scholar
  18. Wu, P., Y. H. Ding, and Y. J. Liu, 2017: Atmospheric circulation and dynamic mechanism for persistent haze events in the Beijing–Tianjin–Hebei region. Adv. Atmos. Sci., 34: 429–440, doi: 10.1007/s00376-016-6158-z.CrossRefGoogle Scholar
  19. Wu, T. W., R. C. Yu, F. Zhang, et al., 2010: The Beijing Climate Center atmospheric general circulation model: Description and its performance for the present-day climate. Climate Dyn., 34: 123–147, doi: 10.1007/s00382-008-0487-2.CrossRefGoogle Scholar
  20. Wu, T. W., W. P. Li, J. J. Ji, et al., 2013: Global carbon budgets simulated by the Beijing Climate Center Climate System Model for the last century. J. Geophys. Res. Atmos., 118: 4326–4347, doi: 10.1002/jgrd.50320.CrossRefGoogle Scholar
  21. Xin, X. G., T. W. Wu, and J. Zhang, 2013: Introduction of CMIP5 experiments carried out with the climate system models of Beijing Climate Center. Adv. Climate Change Res., 4: 41–49, doi: 10.3724/SP.J.1248.2013.041.CrossRefGoogle Scholar
  22. Xu, M., C.-P. Chang, C. B. Fu, et al., 2006: Steady decline of East Asian monsoon winds, 1969–2000: Evidence from direct ground measurements of wind speed. J. Geophy. Res. Atmos., 111, D24111, doi: 10.1029/2006JD007337.CrossRefGoogle Scholar
  23. Zhong, J. T., X. Y. Zhang, Y. S. Dong, et al., 2018: Feedback effects of boundary-layer meteorological factors on cumulative explosive growth of PM2.5 during winter heavy pollution episodes in Beijing from 2013 to 2016. Atmos. Chem. Phys., 18: 247–258, doi: 10.5194/acp-18-247-2018.CrossRefGoogle Scholar
  24. Zhou, T. J., and R. C. Yu, 2006: Twentieth-century surface air temperature over China and the globe simulated by coupled climate models. J. Climate, 19: 5843–5858, doi: 10.1175/JCL I3952.1.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Urban MeteorologyChina Meteorological AdministrationBeijingChina
  2. 2.Environmental Meteorology Forecast Center of Beijing–Tianjin–Hebei RegionBeijingChina
  3. 3.National Climate CenterChina Meteorological AdministrationBeijingChina

Personalised recommendations