Sensitivity of seasonal Snowfall Attribution to Atmospheric Rivers and Their Reanalysis-Based Detetcion
Sensitivity of seasonal Snowfall Attribution to Atmospheric Rivers and Their Reanalysis-Based Detetcion
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DOI：
10.1029/2018gl080783
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发表时间：
2019-01-28
影响因子：
5.2
通讯作者：
Lettenmaier, Dennis P.
中科院分区：
文献类型：
--
作者：
Huning, Laurie S.;Guan, Bin;Lettenmaier, Dennis P.
我们的特点的敏感性，大气河流（AR）派生的季节性降雪量估计，他们的大气再分析为基础的检测在塞拉利昂内华达州，美国。我们使用一个独立的雪数据集和AR识别与一个单一的检测方法应用到多个大气再分析不同的水平分辨率，评估地形的关系和贡献的个别AR的季节性累积降雪（CS）。空间分辨率差异对诊断的AR数量的影响相对较小，在1985-2015年冬季，平均每年有4个更高分辨率的数据集识别AR。然而，这可能导致类似的10%的差异AR归因于平均域范围的季节性CS和差异高达47%的降雪归因于季节尺度。我们发现，识别积雪AR提供了更多的信息比简单地知道有多少AR发生的季节性CS。总的来说，我们发现，更高分辨率的大气再分析意味着更大的归因于季节性CS的ARs.Plain语言摘要虽然众所周知，细长的富含水分的大气特征，称为大气河流（AR），在美国西部山区的水资源中发挥着重要作用，关于用于诊断AR存在的大气数据集如何影响每年冬天估计的AR归因的降雪量，人们知之甚少。尽管如此，这些缺失的信息对于管理水资源和改善依赖AR衍生降雪的地区的季节性降雪预测非常重要。我们表明，使用一个单一的AR检测算法，应用到多个大气再分析，以确定AR，高分辨率的大气再分析诊断高达4个以上的AR每个冬天意味着10%以上的AR归因于整个美国内华达州山脉的平均季节性降雪。了解不同的大气再分析如何发挥作用，在我们的解释AR对水文研究和水资源管理的影响，因为我们在这里调查，是很重要的，特别是因为更多的AR预计会发生在一个温暖的未来大气。
We characterize the sensitivity of atmospheric river (AR)-derived seasonal snowfall estimates to their atmospheric reanalysis-based detection over Sierra Nevada, USA. We use an independent snow data set and the ARs identified with a single detection method applied to multiple atmospheric reanalyses of varying horizontal resolutions, to evaluate orographic relationships and contributions of individual ARs to the seasonal cumulative snowfall (CS). Spatial resolution differences have relatively minor effects on the number of ARs diagnosed, with higher-resolution data sets identifying four more AR days per year, on average, during the 1985-2015 winters. However, this can lead to similar to 10% difference in AR attribution to the mean domain-wide seasonal CS and differences up to 47% snowfall attribution at the seasonal scale. We show that identifying snow-bearing ARs provides more information about the seasonal CS than simply knowing how many ARs occurred. Overall, we find that higher-resolution atmospheric reanalyses imply greater attribution of seasonal CS to ARs.Plain Language Summary While it is known that elongated moisture-rich atmospheric features, known as atmospheric rivers (ARs), play an important role in the water resources of the mountainous western United States, less is known about how the atmospheric data sets used to diagnose the presence of ARs influence the amount of AR-attributed snowfall estimated each winter. Nonetheless, this missing information can be important for managing water resources and improving seasonal snowfall forecasts for areas depending on AR-derived snowfall. We show that using a single AR detection algorithm, applied to multiple atmospheric reanalyses to identify ARs, higher-resolution atmospheric reanalyses diagnose up to four more ARs per winter implying 10% greater AR attribution to the mean seasonal snowfall across Sierra Nevada, USA. Understanding how different atmospheric reanalyses play a role in our interpretation of AR impacts for hydrologic studies and water resources management, as we investigate here, is important especially as more ARs are projected to occur in a warmer future atmosphere.