气候变化领域集成服务门户(CCPortal): On the limit to the accuracy of regional-scale air quality models

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DOI	10.5194/acp-20-1627-2020
	On the limit to the accuracy of regional-scale air quality models
	Trivikrama Rao S.; Luo H.; Astitha M.; Hogrefe C.; Garcia V.; Mathur R.
发表日期	2020
ISSN	1680-7316
起始页码	1627
结束页码	1639
卷号	20 期号:3
英文摘要	Regional-scale air pollution models are routinely being used worldwide for research, forecasting air quality, and regulatory purposes. It is well recognized that there are both reducible (systematic) and irreducible (unsystematic) errors in the meteorology-atmospheric-chemistry modeling systems. The inherent (random) uncertainty stems from our inability to properly characterize stochastic variations in atmospheric dynamics and chemistry and from the incommensurability associated with comparisons of the volumeaveraged model estimates with point measurements. Because stochastic variations are not being explicitly simulated in the current generation of regional-scale meteorology-air quality models, one should expect to find differences between the model estimates and corresponding observations. This paper presents an observation-based methodology to determine the expected errors from current-generation regional air quality models even when the model design, physics, chemistry, and numerical analysis, as well as its input data, were "perfect". To this end, the short-term synoptic-scale fluctuations embedded in the daily maximum 8 h ozone time series are separated from the longer-term forcing using a simple recursive moving average filter. The inherent uncertainty attributable to the stochastic nature of the atmosphere is determined based on 30C years of historical ozone time series data measured at various monitoring sites in the contiguous United States (CONUS). The results reveal that the expected root mean square error (RMSE) at the median and 95th percentile is about 2 and 5 ppb, respectively, even for perfect air quality models driven with perfect input data. Quantitative estimation of the limit to the model's accuracy will help in objectively assessing the current state of the science in regional air pollution models, measuring progress in their evolution, and providing meaningful and firm targets for improvements in their accuracy relative to ambient measurements. © 2020 Author(s).
语种	英语
scopus关键词	accuracy assessment; air quality; atmospheric modeling; atmospheric pollution; ozone; quantitative analysis; stochasticity; uncertainty analysis; United States
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/141554
作者单位	Department of Marine Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC, United States; Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT, United States; Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC, United States
推荐引用方式 GB/T 7714	Trivikrama Rao S.,Luo H.,Astitha M.,et al. On the limit to the accuracy of regional-scale air quality models[J],2020,20(3).
APA	Trivikrama Rao S.,Luo H.,Astitha M.,Hogrefe C.,Garcia V.,&Mathur R..(2020).On the limit to the accuracy of regional-scale air quality models.Atmospheric Chemistry and Physics,20(3).
MLA	Trivikrama Rao S.,et al."On the limit to the accuracy of regional-scale air quality models".Atmospheric Chemistry and Physics 20.3(2020).