Towards robust pan-European storm surge forecasting

Operational forecasting systems are important for disaster risk reduction. In this work we implement a coupled storm surge and tidal model on an unstructured grid over Europe towards the development of a pan-European Storm Surge Forecasting System (EU-SSF). The skill to predict tidal, surge and total water levels was evaluated based on measurements from 208 tidal gauge stations. Results show satisfactory performance for the two atmospheric forcing datasets tested, a High Resolution Forecast and ERA-INTERIM reanalysis, both provided by the European Center for Medium range Weather Forecast. For tidal predictions, the total RSS is equal to 0.197 m, lower than the values estimated by the global tidal model FES2004, and outperformed only by FES2012 (RSS = 0.05 m), which however is a product of data assimilation. Storm surge validation results show good predictive skill, with 0.04 m < RMSE < 0.21 m and %RMSE within 4%–22%. Coupling with tides results in improved storm surge level predictions, with RMSE reducing by up to 0.033 m. The areas benefiting most from the coupling are the North Sea and the English Channel, resulting in up to 2% reduction of the %RMSE. Increasing the resolution of atmospheric forcing also improves the predictive skill, leading to a reduction of RMSE up to 0.06 m in terms of the extremes, especially in shallow areas where wind is the main driver for surge production. We propose a setup for operational pan-European storm surge forecasting combining tidal levels from the FES2012 model and storm surge residuals from the EU-SSF setup which couples meteorological and astronomic tides.

FERÁNDEZ-MONTBLANC Tomás;  VOUSDOUKAS Michail;  CIAVOLA Paolo;  VOUKOUVALAS Evangelos;  MENTASCHI Lorenzo;  BREYIANNIS George;  FEYEN Luc;  SALAMON Peter; 

2019-04-03

ELSEVIER SCI LTD

JRC110403

1463-5003 (online),   

https://www.sciencedirect.com/science/article/pii/S1463500318301823,    https://publications.jrc.ec.europa.eu/repository/handle/JRC110403,   

10.1016/j.ocemod.2018.12.001 (online),