Atmospheric Rivers (ARs) play a pivotal role in precipitation dynamics, often leading to hazardous flood events. While much research has investigated the relationship between ARs and precipitation in the northern hemisphere, the role of ARs in modulating Australia’s precipitation has received little attention. The ambiguity surrounding AR definition and identification criteria has resulted in the emergence of various algorithms, differing in prerequisite thresholds. This study focuses on refining AR detection algorithm choice with a specific emphasis on the precipitation-AR relationship for Australia. Using data from 1980 to 2019, we examine seven AR selection algorithms, investigating the impact of Integrated Vapor Transport (IVT), a key indicator of AR activity, as well as ARs, on precipitation activity across Australia. We find a robust positive relationship, with a correlation of 0.5 to 1, between annual IVT and precipitation anomalies across Australia. Our findings also reveal a positive correlation between ARs and precipitation on an annual scale. While ARs consistently align with the top 25 % of precipitation, indicative of their association with heavy precipitation events, our study highlights a substantial difference between detection algorithms in the likelihood of AR occurrence on days with and without precipitation – varying from approximately 10 % to almost 40 %. Our results demonstrate that, although ARs are typically associated with heavy precipitation, this association varies greatly between detection algorithms. We anticipate these findings will have implications for our understanding of the role of ARs in hydrologic assessments, particularly related to heavy precipitation events leading to flooding.

中文翻译：

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大气河流和澳大利亚降水：检测算法选择的影响


大气河流 （ARs） 在降水动力学中起着关键作用，通常会导致危险的洪水事件。虽然许多研究调查了北半球 AR 与降水之间的关系，但 AR 在调节澳大利亚降水方面的作用却很少受到关注。围绕 AR 定义和识别标准的模糊性导致了各种算法的出现，这些算法在先决条件阈值上有所不同。本研究侧重于改进 AR 检测算法的选择，特别强调澳大利亚的降水-AR 关系。使用 1980 年至 2019 年的数据，我们研究了七种 AR 选择算法，研究了 AR 活动的关键指标综合蒸汽传输 （IVT） 以及 AR 对澳大利亚降水活动的影响。我们发现澳大利亚的年度 IVT 与降水异常之间存在强大的正相关关系，相关性为 0.5 比 1。我们的研究结果还揭示了 AR 与年降水之间的正相关关系。虽然 AR 始终与前 25% 的降水保持一致，表明它们与强降水事件有关，但我们的研究强调了检测算法在有降水和无降水的日子里 AR 发生的可能性存在很大差异——从大约 10% 到近 40% 不等。我们的结果表明，尽管 ARs 通常与强降水有关，但这种关联在检测算法之间差异很大。我们预计这些发现将对我们理解 AR 在水文评估中的作用产生影响，特别是与导致洪水的强降水事件有关。