Articles | Volume 9, issue 1
Geosci. Model Dev., 9, 17–39, 2016
https://doi.org/10.5194/gmd-9-17-2016
Geosci. Model Dev., 9, 17–39, 2016
https://doi.org/10.5194/gmd-9-17-2016

Development and technical paper 15 Jan 2016

Development and technical paper | 15 Jan 2016

GIST-PM-Asia v1: development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia

S. Lee et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Sojin Lee on behalf of the Authors (01 Oct 2015)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (09 Oct 2015) by Olivier Boucher
RR by Anonymous Referee #1 (28 Oct 2015)
ED: Publish subject to technical corrections (05 Nov 2015) by Olivier Boucher
AR by Sojin Lee on behalf of the Authors (11 Nov 2015)  Author's response    Manuscript
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Short summary
We developed an integrated air quality modeling system using AOD data retrieved from a geostationary satellite sensor, GOCI (Geostationary Ocean Color Imager), over Northeast Asia with an application of the spatiotemporal-kriging (STK) method and conducted short-term hindcast runs using the developed system. It appears that the STK approach can greatly reduce not only the errors and biases of AOD and PM10 predictions but also the computational burden of a chemical weather forecast (CWF).