Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.668 IF 5.668
  • IF 5-year value: 6.201 IF 5-year
    6.201
  • CiteScore value: 6.13 CiteScore
    6.13
  • SNIP value: 1.633 SNIP 1.633
  • IPP value: 5.91 IPP 5.91
  • SJR value: 2.938 SJR 2.938
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 174 Scimago H
    index 174
  • h5-index value: 87 h5-index 87
Discussion papers
https://doi.org/10.5194/acp-2019-648
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-648
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 28 Aug 2019

Submitted as: research article | 28 Aug 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Improving air quality forecasting with the assimilation of GOCI AOD retrievals during the KORUS-AQ period

Soyoung Ha1, Zhiquan Liu1, Wei Sun1, Yonghee Lee2, and Limseok Chang2 Soyoung Ha et al.
  • 1National Center for Atmospheric Research, Boulder, Colorado, USA
  • 2National Institute of Environmental Research, Incheon, South Korea

Abstract. The Korean Geostationary Ocean Color Imager (GOCI) satellite has monitored the East Asian region in high temporal and spatial resolution every day, providing unprecedented information on air pollutants over the upstream region of the Korean peninsula for the last decade. In this study, the GOCI Aerosol optical depth (AOD), retrieved at 550 nm wavelength, is assimilated to ameliorate the analysis quality, thereby making systematic improvements on air quality forecasting in South Korea. For successful data assimilation, GOCI retrievals are carefully investigated and processed based on data characteristics. The preprocessed data are then assimilated in the three-dimensional variational data assimilation (3DVAR) technique for the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). During the Korea-United States Air Quality (KORUS-AQ) period (May 2016), the impact of GOCI AOD on the accuracy of air quality forecasting is examined by comparing with other observations including Moderate Resolution Imaging Spectroradiometer (MODIS) sensors and fine particulate matter (PM2.5) observations at the surface. Consistent with previous studies, the assimilation of surface PM2.5 concentrations alone systematically underestimates surface PM2.5 and its positive impact lasts mainly for about 6 h. When GOCI AOD retrievals are assimilated with surface PM2.5 observations, however, the negative bias is diminished and forecasts are improved up to 24 h, with the most significant contributions to the prediction of heavy pollution events over South Korea.

Soyoung Ha et al.
Interactive discussion
Status: open (until 23 Oct 2019)
Status: open (until 23 Oct 2019)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Soyoung Ha et al.
Soyoung Ha et al.
Viewed  
Total article views: 217 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
163 46 8 217 1 1
  • HTML: 163
  • PDF: 46
  • XML: 8
  • Total: 217
  • BibTeX: 1
  • EndNote: 1
Views and downloads (calculated since 28 Aug 2019)
Cumulative views and downloads (calculated since 28 Aug 2019)
Viewed (geographical distribution)  
Total article views: 183 (including HTML, PDF, and XML) Thereof 179 with geography defined and 4 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 17 Sep 2019
Publications Copernicus
Download
Short summary
The aerosol optical depth (AOD) retrieved from the Korean Geostationary Ocean Color Imager (GOCI) satellite was assimilated in the three-dimensional variational data assimilation (3DVAR) system for the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) during the Korea-United States Air Quality (KORUS-AQ) period (May 2016). The assimilation of GOCI AOD improved the prediction of surface PM2.5 up to 24 h, particularly in the heavy pollution event.
The aerosol optical depth (AOD) retrieved from the Korean Geostationary Ocean Color Imager...
Citation