Tuning the Model Winds in Perspective of Operational Storm Surge Prediction in the Adriatic Sea

In the Adriatic Sea, the sea surface wind forecasts are often underestimated, with detrimental effects on the accuracy of sea level and storm surge predictions. Among the various causes, this mainly depends on the meteorological forcing of the wind. In this paper, we try to improve an existing numerical method, called wind bias mitigation, which relies on scatterometer wind observations to determine a multiplicative factor Delta w, whose application to the model wind reduces its inaccuracy with respect to the scatterometer wind. Following four different mathematical approaches, we formulate and discuss seven new expressions of the multiplicative factor. The eight different expressions of the bias mitigation factor, the original one and the seven formulated in this study, are assessed with the aid of four datasets of real sea surface wind events in a variety of sea level conditions in the northern Adriatic Sea, several of which gave rise to high water events in the Venice Lagoon. The statistical analysis shows that some of the seven new formulations of the wind bias mitigation factor are able to lower the model-scatterometer bias with respect to the original formulation. For some other of the seven new formulations, the absolute bias, with respect to scatterometer, of the mitigated model wind field, results lower than that supplied by the unmodified model wind field in 81% of the considered storm surge events in the area of interest, against the 73% of the original formulation of the wind bias mitigation. This represents an 11% improvement in the bias mitigation process, with respect to the original formulation. The best performing of the seven new wind bias mitigation factors, that based on the linear least square regression of the squared wind speed (LLSRE), has been implemented in the operational sea level forecast chain of the Tide Forecast and Early Warning Centre of the Venice Municipality (CPSM), to provide support to the operation of the MO.SE. barriers in Venice.

Automated summary

In this paper, the authors aim to improve the accuracy of sea level and storm surge predictions in the Adriatic Sea by mitigating the wind bias in the sea surface wind forecasts. They propose seven new expressions of the wind bias mitigation factor based on scatterometer wind observations. Statistical analysis shows that some of these new formulations are able to reduce the bias between the model wind and scatterometer wind, resulting in an 11% improvement compared to the original formulation. The best performing formulation, based on linear least square regression of the squared wind speed, has been implemented in the operational sea level forecast chain to support the operation of the MO.SE. barriers in Venice.