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The influence of the North Atlantic Oscillation and El Ni?o–Southern Oscillation on mean and extreme values of column ozone over the United States

机译:北大西洋涛动和厄尔尼诺-南方涛动对全美国柱状臭氧平均值和极值的影响

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Continuous measurements of total ozone (by Dobson spectrophotometers) acrossthe contiguous United States began in the early 1960s. Here, we analyzetemporal and spatial variability and trends in total ozone from the five USsites with long-term records. While similar long-term ozone changes aredetected at all five sites, we find differences in the patterns of ozonevariability on shorter timescales. In addition to standard evaluationtechniques, STL-decomposition methods (Seasonal Trend decomposition of timeseries based on LOESS (LOcally wEighted Scatterplot Smoothing)) are used toaddress temporal variability and "fingerprints" of dynamical features in theDobson data. Methods from statistical extreme value theory (EVT) are used tocharacterize days with high and low total ozone (termed EHOs and ELOs,respectively) at each station and to analyze temporal changes in thefrequency of ozone extremes and their relationship to dynamical featuressuch as the North Atlantic Oscillation (NAO) and El Ni?o–Southern Oscillation.A comparison of the fingerprints detected in the frequency distribution ofthe extremes with those for standard metrics (i.e., the mean) shows thatmore fingerprints are found for the extremes, particularly for thepositive phase of the NAO, at all five US monitoring sites. Results from theSTL decomposition support the findings of the EVT analysis. Finally, weanalyze the relative influence of low- and high-ozone events on seasonal meancolumn ozone at each station. The results show that the influence of ELOsand EHOs on seasonal mean column ozone can be as much as ±5 %,about as large as the overall long-term decadal ozone trends.
机译:1960年代初开始对整个美国的臭氧总量进行连续测量(通过Dobson分光光度计)。在这里,我们分析了具有长期记录的美国五个站点的总臭氧的时空变化和趋势。尽管在所有五个地点都检测到了相似的长期臭氧变化,但我们发现在较短的时间尺度上,臭氧变化的模式存在差异。除标准评估技术外,还使用STL分解方法(基于LOESS(局部加权散点图平滑)的时间序列的季节趋势分解)来解决Dobson数据中的时间变化和动态特征的“指纹”。统计极值理论(EVT)的方法用于表征每个站点总臭氧水平高低的日子(分别称为EHO和ELO),并分析臭氧极端频率的时间变化及其与动态特征(如北大西洋)的关系振动(NAO)和厄尔尼诺现象-南方涛动。在极端频率分布中检测到的指纹与标准度量(即平均值)的指纹比较表明,在极端情况下,尤其是在正相位时,发现了更多的指纹。 NAO,位于美国所有五个监视站点。 STL分解的结果支持EVT分析的结果。最后,我们分析了低臭氧和高臭氧事件对每个站点季节性平均柱臭氧的相对影响。结果表明,ELOs和EHOs对季节性平均柱臭氧的影响可能高达±5%,大约相当于整个长期十年臭氧趋势的总和。

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