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Title: The underestimated magnitude and decline trend in near-surface wind over China

Journal Article · · Atmospheric Science Letters
DOI: https://doi.org/10.1002/asl.791 · OSTI ID:1493249
 [1];  [2];  [3];  [4];  [3];  [5]
  1. China Meteorological Administration, Beijing (China). Specialized Meteorological Office. Public Weather Service Center
  2. Chinese Academy of Sciences (CAS), Beijing (China). CAS Key Lab. of Regional Climate-Environment for Temperate East Asia. Inst. of Atmospheric Physics; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Climate and Ecosystem Sciences Division
  3. Meteorological Bureau of Chaohu Lake Basin, Chaohu (China)
  4. Shandong Meteorological Bureau, Jinan (China). Shandong Climate Center
  5. Chinese Academy of Sciences (CAS), Beijing (China). CAS Key Lab. of Regional Climate-Environment for Temperate East Asia. Inst. of Atmospheric Physics

This study reports the magnitude, spatial pattern and temporal trend of near-surface wind speed (NWS) by comparing 20th century simulations in Coupled Model Intercomparison Project phase 5 (CMIP5) and 3 (CMIP3) and the climate reanalyses with measurements at 563 weather stations in China over 1961–2005. Both CMIP5 and CMIP3 agree quite well with observations in reproducing the spatial pattern of annual mean NWS. CMIP5 models are superior to CMIP3 models in hindcasting the magnitude and spatial pattern of seasonal mean NWS, the temporal trend in annual and seasonal mean NWS. Although both CMIP3 and CMIP5 reproduced the decline trend in the annual and seasonal mean NWS, the hindcasted decline rate is smaller than observed decline trend by the magnitude of one order. The ensemble of optimal models that are better correlated to observations in both NWS and temporal trend possesses advantages over individual model hindcast and reanalyses. The reanalyzed data are not able to represent the observed either the spatial pattern or the decline trend of NWS. The analyses presented here reveal the uncertainties in the current wind field products including reanalyses and model outputs and highlight the benefits of parameterization development and increased horizontal resolution in the new-generation CMIP models.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE; National Natural Science Foundation of China (NSFC); CAS Pioneer Hundred Talents Program (China)
Grant/Contract Number:
AC02-05CH11231; 41205114
OSTI ID:
1493249
Journal Information:
Atmospheric Science Letters, Vol. 18, Issue 12; ISSN 1530-261X
Publisher:
Royal Meteorological SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 12 works
Citation information provided by
Web of Science

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Cited By (1)

Future projections of the near-surface wind speed over eastern China based on CMIP5 datasets journal January 2020

Figures / Tables (5)