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Geosci. Model Dev., 9, 17-39, 2016
https://doi.org/10.5194/gmd-9-17-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
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 discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC C1548: 'Review of "Development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia" by Lee et al.', Anonymous Referee #1, 29 Jul 2015 Printer-friendly Version 
AC C2313: 'Responses to comments of the Anonymous Referee #1', Sojin Lee, 01 Oct 2015 Printer-friendly Version 
 
RC C1630: 'Review of “Development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrived aerosol optical data over Northeast Asia” by Lee et al.', Anonymous Referee #2, 08 Aug 2015 Printer-friendly Version 
AC C2318: 'Responses to comments of the Anonymous Referee #2', Sojin Lee, 01 Oct 2015 Printer-friendly Version 
 
SC C1661: 'Executive Editor Comment on "Development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia"', Astrid Kerkweg, 11 Aug 2015 Printer-friendly Version 
AC C2324: 'Responses to executive editor', Sojin Lee, 01 Oct 2015 Printer-friendly Version 
 
AC C2308: 'Final response', Sojin Lee, 01 Oct 2015 Printer-friendly Version Supplement 
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
CC BY 4.0
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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).
We developed an integrated air quality modeling system using AOD data retrieved from a...
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