Assimilation of next generation geostationary aerosol optical depth retrievals to improve air quality simulations

被引:88
作者
Saide, Pablo E. [1 ]
Kim, Jhoon [2 ]
Song, Chul H. [3 ]
Choi, Myungje [2 ]
Cheng, Yafang [4 ]
Carmichael, Gregory R. [1 ]
机构
[1] Univ Iowa, Ctr Global & Reg Environm Res, Iowa City, IA 52242 USA
[2] Yonsei Univ, Dept Atmospher Sci, Seoul 120749, South Korea
[3] Gwangju Inst Sci & Technol, Sch Environm Sci & Engn, Gwangju, South Korea
[4] Max Planck Inst Chem, Multiphase Chem Dept, D-55128 Mainz, Germany
基金
美国国家卫生研究院;
关键词
Data assimilation; AOD; GSI; WRF-Chem; Pollution episode; modeling; MODEL; CHEMISTRY; EMISSIONS; POLLUTION; VICINITY; IMPACT; OZONE; DUST; SET;
D O I
10.1002/2014GL062089
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Planned geostationary satellites will provide aerosol optical depth (AOD) retrievals at high temporal and spatial resolution which will be incorporated into current assimilation systems that use low-Earth orbiting (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) AOD. The impacts of such additions are explored in a real case scenario using AOD from the Geostationary Ocean Color Imager (GOCI) on board of the Communication, Ocean, and Meteorology Satellite, a geostationary satellite observing northeast Asia. The addition of GOCI AOD into the assimilation system generated positive impacts, which were found to be substantial in comparison to only assimilating MODIS AOD. We found that GOCI AOD can help significantly to improve surface air quality simulations in Korea for dust, biomass burning smoke, and anthropogenic pollution episodes when the model represents the extent of the pollution episodes and retrievals are not contaminated by clouds. We anticipate future geostationary missions to considerably contribute to air quality forecasting and provide better reanalyses for health assessments and climate studies.
引用
收藏
页码:9188 / 9196
页数:9
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