CMAQ模拟的美国背景和人为臭氧的源特异性偏差校正。

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
T Nash Skipper, Christian Hogrefe, Barron H Henderson, Rohit Mathur, Kristen M Foley, Armistead G Russell
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引用次数: 0

摘要

美国(US)背景臭氧(O3)是在美国人为零排放的情况下存在的反事实臭氧。对美国背景臭氧的估计通常来自化学输运模式(CTMs),但不同模式对背景臭氧和总臭氧的估计各不相同。本文采用测量模型数据融合方法估算了美国人为臭氧和多个美国背景臭氧源(包括自然排放、远距离国际排放、来自加拿大和墨西哥的短程国际排放以及平流层臭氧)的CTM偏差。空间和时间变化的偏差校正因子调整每个模拟的O3分量,以便与未调整的估计值相比,调整后分量的总和对观测值的评估更好。估计的校正因子表明,在美国东部,美国人为O3存在季节性一致的正偏差,随着模式分辨率的提高和模拟总O3的增加,偏差变得越来越大,尽管随着观测到的O3的增加,偏差不会增加太多。在12、36和108公里分辨率的一组模拟中,美国东部夏季平均人为臭氧估计偏高了2、7和11 ppb(11%、32%和49%),而在另一组12和108公里分辨率的模拟中,估计偏高了1和6 ppb(10%和37%)。不同美国背景O3组分之间的相关性会增加源特异性调整因子估计的不确定性。尽管如此,结果表明,对平流层臭氧对地表影响的模拟估计存在负偏差,基于平流层臭氧示踪剂估计的美国西部春季平均偏差为-3.5 ppb(-25%)。这种类型的数据融合方法可以扩展到包括来自多个模型的数据,以利用不同数据源的优势,同时减少美国背景臭氧估计的不确定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ.

United States (US) background ozone (O3) is the counterfactual O3 that would exist with zero US anthropogenic emissions. Estimates of US background O3 typically come from chemical transport models (CTMs), but different models vary in their estimates of both background and total O3. Here, a measurement-model data fusion approach is used to estimate CTM biases in US anthropogenic O3 and multiple US background O3 sources, including natural emissions, long-range international emissions, short-range international emissions from Canada and Mexico, and stratospheric O3. Spatially and temporally varying bias correction factors adjust each simulated O3 component so that the sum of the adjusted components evaluates better against observations compared to unadjusted estimates. The estimated correction factors suggest a seasonally consistent positive bias in US anthropogenic O3 in the eastern US, with the bias becoming higher with coarser model resolution and with higher simulated total O3, though the bias does not increase much with higher observed O3. Summer average US anthropogenic O3 in the eastern US was estimated to be biased high by 2, 7, and 11 ppb (11%, 32%, and 49%) for one set of simulations at 12, 36, and 108 km resolutions and 1 and 6 ppb (10% and 37%) for another set of simulations at 12 and 108 km resolutions. Correlation among different US background O3 components can increase the uncertainty in the estimation of the source-specific adjustment factors. Despite this, results indicate a negative bias in modeled estimates of the impact of stratospheric O3 at the surface, with a western US spring average bias of -3.5 ppb (-25%) estimated based on a stratospheric O3 tracer. This type of data fusion approach can be extended to include data from multiple models to leverage the strengths of different data sources while reducing uncertainty in the US background ozone estimates.

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来源期刊
Geoscientific Model Development
Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
8.60
自引率
9.80%
发文量
352
审稿时长
6-12 weeks
期刊介绍: Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.
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