Using ensemble reforecasts to generate flood thresholds for improved global flood forecasting
Using ensemble reforecasts to generate flood thresholds for improved global flood forecasting
复制标题
使用集合重新预测生成洪水阈值以改进全球洪水预报
DOI：
10.1111/jfr3.12658
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发表时间：
2020
影响因子：
4.1
通讯作者：
H. Cloke
中科院分区：
文献类型：
--
作者：
E. Zsótér;C. Prudhomme;E. Stephens;H. Cloke
全球洪水预报系统依靠预先定义的洪水阈值来突出潜在的即将到来的洪水事件。现有的洪水阈值定义方法通常基于重新分析数据集，使用所有预测前置时间的单一阈值，例如在全球洪水预警系统中。这导致极端洪水事件在洪水阈值中的表现与集合预报之间的不一致。本文探讨了利用河流流量集合再预测来产生洪水阈值的潜在好处，这些阈值可以提高可靠性和技能，增加人道主义和民防合作伙伴对预测的信心。在再分析和再预测的阈值计算中，数据集的选择和采样年最大值的方法，从阈值大小、预测可靠性和不同洪水严重程度和前置时间的技能等方面进行了分析。当从不同的年度最大值样本估计时，阈值幅度的变异性可能非常大，对预测技能的后续影响也是如此。基于再分析的阈值应仅用于前几天，之后，基于集合再预测的阈值随着预测提前期的变化而变化，可以解释预测偏差趋势，提供更可靠和更熟练的洪水预报。
Global flood forecasting systems rely on predefining flood thresholds to highlight potential upcoming flood events. Existing methods for flood threshold definition are often based on reanalysis datasets using a single threshold across all forecast lead times, such as in the Global Flood Awareness System. This leads to inconsistencies between how the extreme flood events are represented in the flood thresholds and the ensemble forecasts. This paper explores the potential benefits of using river flow ensemble reforecasts to generate flood thresholds that can deliver improved reliability and skill, increasing the confidence in the forecasts for humanitarian and civil protection partners. The choice of dataset and methods used to sample annual maxima in the threshold computation, both for reanalysis and reforecast, is analysed in terms of threshold magnitude, forecast reliability, and skill for different flood severity levels and lead times. The variability of threshold magnitudes, when estimated from the different annual maxima samples, can be extremely large, as can the subsequent impact on forecast skill. Reanalysis‐based thresholds should only be used for the first few days, after which ensemble‐reforecast‐based thresholds, that vary with forecast lead time and can account for the forecast bias trends, provide more reliable and skilful flood forecasts.
影响因子：
8.2
作者：
Wu, Wenyan;Emerton, Rebecca;Robertson, David E.
通讯作者：
Robertson, David E.