Volume 37 Issue 3
May  2017
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Article Navigation >  Chinese Journal of Space Science  > 2017  >  37(3): 284-290
YANG Junfeng, XIAO Cunying, HU Xiong, XU Qingchen. Observations and Simulations of the Mean Winds in Mesosphere and Lower Thermosphere over Langfang of China[J]. Chinese Journal of Space Science, 2017, 37(3): 284-290. doi: 10.11728/cjss2017.03.284
Citation: YANG Junfeng, XIAO Cunying, HU Xiong, XU Qingchen. Observations and Simulations of the Mean Winds in Mesosphere and Lower Thermosphere over Langfang of China[J]. Chinese Journal of Space Science, 2017, 37(3): 284-290. doi: 10.11728/cjss2017.03.284
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Observations and Simulations of the Mean Winds in Mesosphere and Lower Thermosphere over Langfang of China

doi: 10.11728/cjss2017.03.284 cstr: 32142.14.cjss2017.03.284

  • 1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190;

  • 2. University of Chinese Academy of Sciences, Beijing 100049

  • Received Date: 2016-01-25
  • Rev Recd Date: 2016-12-05
  • Publish Date: 2017-05-15
    Abstract
  • By use of the observations of the meteor radar located at Langfang, China (39.4°N, 116.7°E), the seasonal variation of mean winds in the Mesospheric and Lower Thermospheric (MLT) layer at 80~100km altitude over Langfang are studied. The time range of the observations is from 1 April 2012 to 31 March 2013. The results show that both the mean zonal winds and the mean meridional winds have obvious seasonal variations. In winter, westward winds prevail in the MLT, which are strongest in mesopause and decrease with increasing altitude. In summer, eastward winds dominate in mesosphere and decrease with increasing altitude, then turn to the strong westward winds at 82km altitude in lower thermosphere. Usually, the mean meridional winds are southward in summer and northward in winter. The wind evolutions have the transition features in spring and autumn. The above main seasonal variations of mean winds are captured largely by the simulation of WACCM4 model and HWM93 model. However, WACCM overestimates the wind velocities, and HWM93 underestimates the winds velocities.

     

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