A Gaussian Process Model Applied to Prediction of the Water Levels in Venice Lagoon

Forecasting the water level at Venice lagoon has been object of extensive studies in the past. For example, the numerical model (MIKE 21) based on deterministic equations has been setup for the purposes of the operational water level forecast. The model includes all the fundamental modelling components necessary for use in operational mode and model has been tested against a number of historical storms. This paper describes a somewhat alternative approach of combining observations and numerical model results in order to produce a more accurate forecast routine. The paper presents an approach where the errors made by a deterministic model are corrected by a gaussian process model. The paper concludes with the analysis of the forecast skill for resulting, hybrid model which provides rather good forecast skill that can be extended over a forecasting horizon of considerable length.