Arid
DOI10.5194/gmd-9-17-2016
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
Lee, S.1; Song, C. H.1; Park, R. S.1,5; Park, M. E.1,6; Han, K. M.1; Kim, J.2; Choi, M.2; Ghim, Y. S.3; Woo, J. -H.4
通讯作者Song, C. H.
来源期刊GEOSCIENTIFIC MODEL DEVELOPMENT
ISSN1991-959X
EISSN1991-9603
出版年2016
卷号9期号:1页码:17-39
英文摘要

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 a part of Northeast Asia (113-146 degrees E; 25-47 degrees N), were used. Although GOCI can provide a higher number of AOD data in a semicontinuous 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 spatiotemporal-kriging (STK) 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 in using the STK method in this study is that more observed AOD data can be used to prepare the best initial AOD fields compared with other methods that use single frame of observation data around the time of initialization. It is demonstrated in this study that the short-term PM forecast system developed with the application of the STK method can greatly improve PM10 predictions in the Seoul metropolitan area (SMA) when evaluated with ground-based observations. For example, errors and biases of PM10 predictions decreased by similar to 60 and similar to 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 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 (particle-into-liquid sampler coupled with ion chromatography) 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.


类型Article
语种英语
国家South Korea
收录类别SCI-E
WOS记录号WOS:000376932900002
WOS关键词SECONDARY ORGANIC AEROSOL ; SULFUR-DIOXIDE EMISSIONS ; ABSOLUTE ERROR MAE ; BASIS-SET APPROACH ; EAST-ASIA ; AIR-POLLUTION ; CHEMICAL-CHARACTERIZATION ; ISOPRENE EMISSIONS ; MODEL PERFORMANCE ; SHIP PLUMES
WOS类目Geosciences, Multidisciplinary
WOS研究方向Geology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/193286
作者单位1.Gwangju Inst Sci & Technol, Sch Environm Sci & Engn, Gwangju 500712, South Korea;
2.Yonsei Univ, Dept Atmospher Sci, Seoul 120749, South Korea;
3.Hankuk Univ Foreign Studies, Dept Environm Sci, Yongin 449791, South Korea;
4.Konkuk Univ, Dept Adv Technol Fus, Seoul 143701, South Korea;
5.Korea Inst Atmospher Predict Syst, Numer Model Team, Seoul 156849, South Korea;
6.Natl Inst Meteorol Res, Asian Dust Res Div, Jeju Do 697845, South Korea
推荐引用方式
GB/T 7714
Lee, S.,Song, C. H.,Park, R. S.,et al. 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[J],2016,9(1):17-39.
APA Lee, S..,Song, C. H..,Park, R. S..,Park, M. E..,Han, K. M..,...&Woo, J. -H..(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.GEOSCIENTIFIC MODEL DEVELOPMENT,9(1),17-39.
MLA Lee, S.,et al."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".GEOSCIENTIFIC MODEL DEVELOPMENT 9.1(2016):17-39.
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