How do I know if I've improved my continental scale flood early warning system?

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 f...

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Bibliographic Details
Published in:Environmental research letters 2017-04, Vol.12 (4), p.44006
Main Authors: Cloke, Hannah L, Pappenberger, Florian, Smith, Paul J, Wetterhall, Fredrik
Format: Article
Language:English
Subjects:
copernicus
Early warning systems
Emergency communications systems
european flood awareness system
flood early warning systems
Flood forecasting
flood resilience
Floods
forecast skill
Mathematical models
monetary value
multi-forcing ensemble
Numerical prediction
Optimization
Spatial variations
Warning systems
Weather forecasting
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Summary: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.
ISSN:1748-9326
1748-9326
DOI:10.1088/1748-9326/aa625a