European coasts are regularly exposed to severe storms that trigger extreme water-level conditions, leading to coastal flooding and erosion. Early Warning Systems (EWS) are important tools for the increased preparedness and response against coastal flood events, hence greatly reducing associated risks. With this objective, a proof-of-concept for a European Coastal Flood Awareness System (ECFAS) was developed in the framework of the H2020 ECFAS project, which capitalizes on the Copernicus products. In this context, this manuscript evaluates for the first time the capability of the current Copernicus Marine operational ocean models to forecast extreme coastal water levels and hence to feed coastal flood awareness applications at European scale. A methodology is developed to focus the assessment on storm-driven extreme sea level events (EEs) from tide-gauge records. For the detected EEs, the event peak representation is validated, and the impact of forecast lead time is evaluated. Results show satisfactory performance but a general underprediction of peak magnitudes of 10% for water levels and 18% for surges across the detected EEs. In average, the models are capable of independently flagging 76% of the observed EEs. Forecasts show limited lead time impact up to a 4-day lead time, demonstrating the suitability of the systems for early warning applications. Finally, by separating the surge and tidal contributions to the extremes, the potential sources of the prediction misfits are discussed and consequent recommendations for the evolution of the Copernicus Marine Service forecasting models towards coastal flooding applications are provided.

Towards a pan-European coastal flood awareness system: Skill of extreme sea-level forecasts from the Copernicus Marine Service / Irazoqui Apecechea, Maialen; Melet, Angélique; Armaroli, Clara. - In: FRONTIERS IN MARINE SCIENCE. - ISSN 2296-7745. - ELETTRONICO. - 9:(2022), pp. 1091844.1-1091844.21. [10.3389/fmars.2022.1091844]

Towards a pan-European coastal flood awareness system: Skill of extreme sea-level forecasts from the Copernicus Marine Service

Armaroli, Clara
Ultimo
2022

Abstract

European coasts are regularly exposed to severe storms that trigger extreme water-level conditions, leading to coastal flooding and erosion. Early Warning Systems (EWS) are important tools for the increased preparedness and response against coastal flood events, hence greatly reducing associated risks. With this objective, a proof-of-concept for a European Coastal Flood Awareness System (ECFAS) was developed in the framework of the H2020 ECFAS project, which capitalizes on the Copernicus products. In this context, this manuscript evaluates for the first time the capability of the current Copernicus Marine operational ocean models to forecast extreme coastal water levels and hence to feed coastal flood awareness applications at European scale. A methodology is developed to focus the assessment on storm-driven extreme sea level events (EEs) from tide-gauge records. For the detected EEs, the event peak representation is validated, and the impact of forecast lead time is evaluated. Results show satisfactory performance but a general underprediction of peak magnitudes of 10% for water levels and 18% for surges across the detected EEs. In average, the models are capable of independently flagging 76% of the observed EEs. Forecasts show limited lead time impact up to a 4-day lead time, demonstrating the suitability of the systems for early warning applications. Finally, by separating the surge and tidal contributions to the extremes, the potential sources of the prediction misfits are discussed and consequent recommendations for the evolution of the Copernicus Marine Service forecasting models towards coastal flooding applications are provided.
2022
Towards a pan-European coastal flood awareness system: Skill of extreme sea-level forecasts from the Copernicus Marine Service / Irazoqui Apecechea, Maialen; Melet, Angélique; Armaroli, Clara. - In: FRONTIERS IN MARINE SCIENCE. - ISSN 2296-7745. - ELETTRONICO. - 9:(2022), pp. 1091844.1-1091844.21. [10.3389/fmars.2022.1091844]
Irazoqui Apecechea, Maialen; Melet, Angélique; Armaroli, Clara
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/917338
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