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Development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia.

Authors :
Lee, S.
Song, C. H.
Park, R. S.
Park, M. E.
Han, K. M.
Kim, J.
Choi, M. J.
Ghim, Y. S.
Woo, J.-H.
Source :
Geoscientific Model Development Discussions; 2015, Vol. 8 Issue 7, p5315-5366, 52p
Publication Year :
2015

Abstract

To improve short-term particulate matter (PM) forecasts in South Korea, the initial distribution of PM composition, particularly over the upwind regions, is primarily important. To prepare the initial PM composition, the aerosol optical depth (AOD) data retrieved from a geostationary equatorial orbit (GEO) satellite sensor, GOCI (Geostationary Ocean Color Imager) which covers Northeast Asia (113-146° E; 25-47° N), were used. Although GOCI can provide a higher number of AOD data in a semi-continuous manner than low Earth orbit (LEO) satellite sensors, it still has a serious limitation in that the AOD data are not available at cloud pixels and over high-reflectance areas, such as desert and snow-covered regions. To overcome this limitation, a spatio-temporal (ST) kriging method was used to better prepare the initial AOD distributions that were converted into the PM composition over Northeast Asia. One of the largest advantages to using the ST-kriging method in this study is that more observed AOD data can be used to prepare the best initial AOD fields. It is demonstrated in this study that the short-term PM forecast system developed with the application of the ST-kriging method can greatly improve PM<subscript>10</subscript> predictions in Seoul Metropolitan Area (SMA), when evaluated with ground-based observations. For example, errors and biases of PM<subscript>10</subscript> predictions decreased by ∼ 60 and ∼ 70 %, respectively, during the first 6 h of short-term PM forecasting, compared with those without the initial PM composition. In addition, the influences of several factors (such as choices of observation operators and control variables) on the performances of the short-term PM forecast were explored in this study. The influences of the choices of the control variables on the PM chemical composition were also investigated with the composition data measured via PILS-IC and low air-volume sample instruments at a site near Seoul. To improve the overall performances of the short-term PM forecast system, several future research directions were also discussed and suggested. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19919611
Volume :
8
Issue :
7
Database :
Complementary Index
Journal :
Geoscientific Model Development Discussions
Publication Type :
Academic Journal
Accession number :
108770034
Full Text :
https://doi.org/10.5194/gmdd-8-5315-2015