Improving Wind Forcing with Scatterometer Observations for Operational Storm Surge Forecasting in the Adriatic Sea

Abstract

Reliable storm surge predictions rely on accurate atmospheric model simulations, especially of the sea surface pressure and wind vector. The Adriatic Sea is among the regional seas of the Mediterranean basin experiencing the highest tidal excursions, particularly in its northern side, the Gulf of Venice, where storm surge predictions are therefore of great importance. Unfortunately, sea surface wind forecasts in the Adriatic Sea are known to be underestimated. A numerical method aiming at reducing the bias between scatterometer wind observations and atmospheric model winds, has been developed. The method is called “wind bias mitigation” and uses the scatterometer observations to reduce the bias between scatterometer observations and the modeled sea surface wind, in this case that supplied by the European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric model. We have compared four mathematical approaches to this method, for a total of eight different formulations of the multiplicative factor $\Delta ws$ which compensates the model wind underestimation, thus decreasing the bias between scatterometer and model. Four datasets are used for the assessment of the eight different bias mitigation methods: a collection of 29 storm surge events (SEVs) cases in the years 2004–2014, a collection of 48 SEVs in the years 2013–2016, a collection of 364 cases of random sea level conditions in the same period, and a collection of the seven SEVs in 2012–2016 that were worst predicted. The statistical analysis shows that the bias mitigation procedures supplies a mean wind speed more accurate than the standard forecast, when compared with scatterometer observations, in more than 70% of the analyzed cases.