Aircraft atmospheric profiling is a valuable technique for determining greenhouse gas fluxes at regional scales (10⁴–10⁶ km²). Here, we describe a new, simple method for estimating the surface influence of air samples that uses backward trajectories based on the Lagrangian model Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT). We determined “regions of influence” on a quarterly basis between 2010 and 2018 for four aircraft vertical profile sites: SAN and ALF in the eastern Amazon, and RBA and TAB or TEF in the western Amazon. We evaluated regions of influence in terms of their relative sensitivity to areas inside and outside the Amazon and their total area inside the Amazon. Regions of influence varied by quarter and less so by year. In the first and fourth quarters, the contribution of the region of influence inside the Amazon was 83–93% for all sites, while in the second and third quarters, it was 57–75%. The interquarter differences are more evident in the eastern than in the western Amazon. Our analysis indicates that atmospheric profiles from the western sites are sensitive to 42–52.2% of the Amazon. In contrast, eastern Amazon sites are sensitive to only 10.9–25.3%. These results may help to spatially resolve the response of greenhouse gas emissions to climate variability over Amazon.

中文翻译：

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利用HYSPLIT模型确定的航迹密度确定飞机垂直剖面获得的影响区域。

飞机大气轮廓分析是确定区域尺度（10 ⁴ –10 ⁶ km ²）。在这里，我们描述了一种基于Lagrangian模型混合单粒子Lagrangian综合轨迹模型（HYSPLIT）的使用后向轨迹估算空气样本表面影响的新方法。我们在2010年至2018年之间按季度确定了四个飞机垂直剖面站点的“影响范围”：亚马逊东部地区的SAN和ALF，亚马逊西部地区的RBA和TAB或TEF。我们根据对亚马逊内部和外部区域以及亚马逊内部总区域的相对敏感性来评估影响区域。影响区域按季度变化，而按年份变化则较小。在第一季度和第四季度，亚马逊内部的影响区域对所有站点的贡献为83-93％，而在第二季度和第三季度，为57-75％。亚马逊东部地区的季度间差异比西部亚马逊地区的更为明显。我们的分析表明，西部站点的大气廓线对亚马逊地区的42-52.2％敏感。相反，亚马逊东部地区的站点仅对10.9–25.3％敏感。这些结果可能有助于在空间上解决温室气体排放对亚马逊地区气候变化的响应。