Advances in Climate Change Research (Apr 2022)

Near-surface wind speed changes in eastern China during 1970–2019 winter and its possible causes

  • Xiao Li,
  • Qiao-Ping Li,
  • Yi-Hui Ding,
  • Mei Wang

Journal volume & issue
Vol. 13, no. 2
pp. 228 – 239

Abstract

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The changes in near-surface wind speed (NWS) have a crucial influence on the wind power industry, and previous studies have indicated that NWS on global and China has declined continuously for decades under global warming. However, recently, the decreasing trend of global NWS has slowed down and even showed a recovery trend. Using the observation data of 831 weather stations of the China Meteorological Administration and the Japanese 55-year reanalysis data from 1970 to 2019, NWS changes in eastern China were analyzed and the possible influencing factors were discussed. Results show that winter NWS presented a decreasing trend from −0.29 m s−1 per decade (p < 0.001) in 1970–1989 to −0.05 m s−1 per decade (p < 0.01) in 1990–2019. Moreover, NWS exhibited a significant upward trend of 0.18 m s−1 per decade (p < 0.1) in 2011–2019, resulting in a 19.6% per decade recovery of the wind power generation. A possible cause is asymmetric changes of the sea level pressure and near-surface air temperature differences between the mid-high latitudes (40°–60°N, 80°–120°E) and low latitudes (20°–40°N, 110°–140°E) altered the horizontal air pressure gradient. Furthermore, NWS changes were closely associated with the large-scale ocean-atmosphere circulations (LOACs). NWS at 77.4% of the stations in eastern China shows significant correlation (p < 0.05) with the East Asian winter monsoon index, besides, the inter/multidecadal variability of NWS was considerably correlated to four LOACs, including Arctic oscillation (AO), North Atlantic oscillation (NAO), Pacific decadal oscillation (PDO), and El Niño–Southern Oscillation (ENSO). The time-series reconstructed by a multiple linear regression model based on above five LOACs matches well with the NWS. Interannual variability of NWS were significantly correlated to AO (−0.45, p < 0.01) and NAO (−0.28, p < 0.05), while the correlation between NWS and ENSO was weak.

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