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Radiative forcing and climate metrics for ozone precursor emissions: the impact of multi-model averaging

机译:臭氧前体排放的辐射强制和气候指标:多模型平均的影响

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Multi-model ensembles are frequently used to assess understanding of the response of ozone and methane lifetime to changes in emissions of ozone precursors such as NOx, VOCs (volatile organic compounds) and CO. When these ozone changes are used to calculate radiative forcing (RF) (and climate metrics such as the global warming potential (GWP) and global temperature-change potential (GTP)) there is a methodological choice, determined partly by the available computing resources, as to whether the mean ozone (and methane) concentration changes are input to the radiation code, or whether each model's ozone and methane changes are used as input, with the average RF computed from the individual model RFs. We use data from the Task Force on Hemispheric Transport of Air Pollution source–receptor global chemical transport model ensemble to assess the impact of this choice for emission changes in four regions (East Asia, Europe, North America and South Asia). We conclude that using the multi-model mean ozone and methane responses is accurate for calculating the mean RF, with differences up to 0.6% for CO, 0.7% for VOCs and 2% for NOx. Differences of up to 60% for NOx 7% for VOCs and 3% for CO are introduced into the 20 year GWP. The differences for the 20 year GTP are smaller than for the GWP for NOx, and similar for the other species. However, estimates of the standard deviation calculated from the ensemble-mean input fields (where the standard deviation at each point on the model grid is added to or subtracted from the mean field) are almost always substantially larger in RF, GWP and GTP metrics than the true standard deviation, and can be larger than the model range for short-lived ozone RF, and for the 20 and 100 year GWP and 100 year GTP. The order of averaging has most impact on the metrics for NOx, as the net values for these quantities is the residual of the sum of terms of opposing signs. For example, the standard deviation for the 20 year GWP is 2–3 times larger using the ensemble-mean fields than using the individual models to calculate the RF. The source of this effect is largely due to the construction of the input ozone fields, which overestimate the true ensemble spread. Hence, while the average of multi-model fields are normally appropriate for calculating mean RF, GWP and GTP, they are not a reliable method for calculating the uncertainty in these fields, and in general overestimate the uncertainty.
机译:多模型集合经常用于评估臭氧和甲烷寿命的响应,以对NOx,VOC(挥发性有机化合物)和CO的臭氧前体的排放变化的理解。当这些臭氧的变化用于计算辐射强制时(RF )(以及全球变暖潜力(GWP)和全球温度变化潜力(GTP)等气候指标)有一种方法学选择,部分地由可用的计算资源确定,以及是否平均臭氧(和甲烷)浓度变化输入到辐射码,或者每个模型的臭氧和甲烷变化是否用作输入,从各个模型RF计算的平均RF。我们使用来自空气污染源 - 受体全球化学传输模型集合的半球传输的特遣部队数据来评估这一选择对四个地区的排放变化的影响(东亚,欧洲,北美和南亚)。我们得出结论,使用多模型平均臭氧和甲烷反应是计算平均射频的准确性,CO的差异高达0.6%,对于VOC的0.7%,对于NOx为2%。对于20年GWP,将VOC的NOx 7%的低至60%的差异为7%和3%。 20年GTP的差异小于NOx的GWP,以及其他物种的差异。然而,从集合式输入字段计算的标准偏差的估计(在模型网格上的每个点处的标准偏差被添加到或减去平均场),在RF,GWP和GTP度量中几乎始终始终大于真正的标准偏差,并且可以大于短期臭氧RF的模型范围,以及20岁和100年GWP和100年GTP。平均的顺序对NOx的度量产生最大影响,因为这些数量的净值是相反标志的剩余之和。例如,20年GWP的标准偏差使用集合的字段比使用单个模型来计算RF的2-3倍。这种效果的来源在很大程度上是由于输入臭氧场的构造,这估计了真正的集合传播。因此,虽然多模型字段的平均值通常适合计算平均RF,GWP和GTP,但它们不是计算这些字段中的不确定性的可靠方法,并且通常高估不确定性。

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