气候变化领域集成服务门户(CCPortal): A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS)

CCPortal

DOI	10.1029/2020JD032554
	A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS)
	Kumar R.; Alessandrini S.; Hodzic A.; Lee J.A.
发表日期	2020
ISSN	2169897X
卷号	125 期号:16
英文摘要	This study examines the benefit of using a dynamical ensemble for 48 hr deterministic and probabilistic predictions of near-surface fine particulate matter (PM2.5) over the contiguous United States (CONUS). Our ensemble design captures three key sources of uncertainties in PM2.5 modeling including meteorology, emissions, and secondary organic aerosol (SOA) formation. Twenty-four ensemble members were simulated using the Community Multiscale Air Quality (CMAQ) model during January, April, July, and October 2016. The raw ensemble mean performed better than most of the ensemble members but underestimated the observed PM2.5 over the CONUS with the largest underestimation over the western CONUS owing to negative PM2.5 bias in nearly all the members. To improve the ensemble performance, we calibrated the raw ensemble using model output statistics (MOS) and variance deficit methods. The calibrated ensemble captured the diurnal and day-to-day variability in observed PM2.5 very well and exhibited almost zero mean bias. The mean bias in the calibrated ensemble was reduced by 90–100% in the western CONUS and by 40–100% in other parts of the CONUS, compared to the raw ensemble in all months. The corresponding reduction in root-mean-square error (RMSE) was 13–40%. The calibrated ensemble also showed 30% improvement in the RMSE and spread matching compared to the raw ensemble. We have also shown that a nine-member ensemble based on combinations of three meteorological and three anthropogenic emission scenarios can be used as a smaller subset of the full ensemble when sufficient computational resources are not available in the operational setting. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	air quality; CMAQ; ensemble calibration; ensemble modeling; PM2.5
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/185814
作者单位	National Center for Atmospheric Research, Boulder, CO, United States
推荐引用方式 GB/T 7714	Kumar R.,Alessandrini S.,Hodzic A.,et al. A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS)[J],2020,125(16).
APA	Kumar R.,Alessandrini S.,Hodzic A.,&Lee J.A..(2020).A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS).Journal of Geophysical Research: Atmospheres,125(16).
MLA	Kumar R.,et al."A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS)".Journal of Geophysical Research: Atmospheres 125.16(2020).