Volume 40 Issue 2
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Article Navigation >  Chinese Journal of Space Science  > 2020  >  40(2): 227-241
JING Wenqi, CUI Yuanyuan, WANG Yegui, JIANG Huiming, CAI Qifa, LAN Weiren. Assimilation of Near Space Temperature Data from SABER and MLS Observations into the Whole Atmosphere Community Climate Model and Data Assimilation Research Test-bed[J]. Chinese Journal of Space Science, 2020, 40(2): 227-241. doi: 10.11728/cjss2020.02.227
Citation: JING Wenqi, CUI Yuanyuan, WANG Yegui, JIANG Huiming, CAI Qifa, LAN Weiren. Assimilation of Near Space Temperature Data from SABER and MLS Observations into the Whole Atmosphere Community Climate Model and Data Assimilation Research Test-bed[J]. Chinese Journal of Space Science, 2020, 40(2): 227-241. doi: 10.11728/cjss2020.02.227
shu

Assimilation of Near Space Temperature Data from SABER and MLS Observations into the Whole Atmosphere Community Climate Model and Data Assimilation Research Test-bed

doi: 10.11728/cjss2020.02.227 cstr: 32142.14.cjss2020.02.227

  • 1 Meteorological Observatory of 94758 Troops, Ningde 355103;

  • 2 Hebei Meteorological Observatory, Shijiazhuang 050021;

  • 3 Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

  • Received Date: 2018-12-17
  • Rev Recd Date: 2019-12-21
  • Publish Date: 2020-03-15
    Abstract
  • This study performs SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) and MLS (Microwave Limb Sounder) temperature data assimilation experiments to simulate a SSW (Stratospheric Sudden Warming) process occurred in February 2016, based on WACCM+DART (Whole Atmosphere Community Climate Model, Data Assimilation Research Test-bed). The following main conclusions are obtained. First, assimilating SABER and MLS temperature observations significantly reduces WACCM's forecast error of temperature fields in mesosphere and middle-upper stratosphere (0.001～10hPa), and effectively improves control experiment's several discrepancies with observations and reanalysis, such as colder mesosphere during SSW, lower layer height that zonal wind direction firstly changes when SSW occurs, east zonal wind layers in 0.1～10hPa prematurely vanishing, stronger zonal wind and higher stratopause height during SSW recovery phase. The verification based on ERA5 reanalysis suggests that assimilating SABER and MLS temperature observations is in favor of reducing analysis error of zonal wind in low mesosphere and middle-upper stratosphere (0.1～14hPa) and temperature in stratosphere and middle-lower mesosphere (0.01～100hPa) above high-latitude areas (60°-90°N)in the northern hemisphere. In addition, assimilating low atmospheric observations is also beneficial for reducing analysis error of zonal wind in 0.1～14hPa and temperature in 0.01～100hPa, but this reduction effect is not as significant as that of assimilating SABER and MLS temperature observations.

     

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