How do I know if I’ve improved my continental scale flood early warning system?
How do I know if I’ve improved my continental scale flood early warning system?
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我如何知道我是否改进了大陆范围的洪水预警系统？
DOI：
10.1088/1748-9326/aa625a
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发表时间：
2017
影响因子：
6.7
通讯作者：
F. Wetterhall
中科院分区：
文献类型：
--
作者：
H. Cloke;F. Pappenberger;Paul Smith;F. Wetterhall
洪水预警系统可减轻损害和生命损失，是提高抗灾能力的一种经济有效的方式。大陆范围的洪水预警系统的使用正在迅速增加。欧洲洪水预警系统（European Flood Awareness System，简称EFAS）是一个由多模式数值天气预报集成而成的泛欧洲洪水预警系统。在这些计算成本高昂的大陆尺度系统中，对科学和技术变化的反应可能是复杂的，需要通过评估整个系统的运行来测试改进。结果表明，预报技巧与预警值无关。为了判断系统是否得到了改进，需要一种既考虑预测技巧又考虑预警值的评估策略。EFAS洪水预报的多强迫集合的组合进行评估与一个新的技能价值的战略。在业务预报中，推荐使用完整的多强迫集合，但最佳预报组合存在空间差异。结果表明，优化预测的基础上的价值，而不是技能改变的最佳强迫组合和预测性能。还表明，模型多样性和集成规模都是重要的，在实现最佳的整体性能。在考虑改进预警系统时，强烈建议采用既考虑技能又考虑价值的若干评价措施。
Flood early warning systems mitigate damages and loss of life and are an economically efficient way of enhancing disaster resilience. The use of continental scale flood early warning systems is rapidly growing. The European Flood Awareness System (EFAS) is a pan-European flood early warning system forced by a multi-model ensemble of numerical weather predictions. Responses to scientific and technical changes can be complex in these computationally expensive continental scale systems, and improvements need to be tested by evaluating runs of the whole system. It is demonstrated here that forecast skill is not correlated with the value of warnings. In order to tell if the system has been improved an evaluation strategy is required that considers both forecast skill and warning value. The combination of a multi-forcing ensemble of EFAS flood forecasts is evaluated with a new skill-value strategy. The full multi-forcing ensemble is recommended for operational forecasting, but, there are spatial variations in the optimal forecast combination. Results indicate that optimizing forecasts based on value rather than skill alters the optimal forcing combination and the forecast performance. Also indicated is that model diversity and ensemble size are both important in achieving best overall performance. The use of several evaluation measures that consider both skill and value is strongly recommended when considering improvements to early warning systems.
影响因子：
6.3
作者：
F. Wetterhall;F. Pappenberger;L. Alfieri;H. Cloke;J. T. Pozo;S. Balabanova;J. Daňhelka;A. Vogelbacher-A.
通讯作者：
F. Wetterhall;F. Pappenberger;L. Alfieri;H. Cloke;J. T. Pozo;S. Balabanova;J. Daňhelka;A. Vogelbacher-A.
影响因子：
3.8
作者：
Chwala, Christian;Keis, Felix;Kunstmann, Harald
通讯作者：
Kunstmann, Harald
影响因子：
2.7
作者：
Cloke, Hannah L.;Pappenberger, Florian
通讯作者：
Pappenberger, Florian