Superstatistical analysis of HF Radar sea surface currents in the Gulf of Trieste, their idealized wind-driven stochastic modeling and extreme power-input events

Abstract

The increasing amount of data in earth-observing systems allows us to move from considering low-order moments (means and variances) of fluctuating observations to their PDFs (Probability Density Functions). For two years of HFR (High Frequency Radar) sea surface current increments in the Gulf of Trieste (Northern Adriatic Sea) we found the analytical fat-tailed PDF form (a combination of a gaussian and a convolution of two exponentials) using superstatistics and the maximum entropy principle twice: on a short and on a longer time scale. The data observed under different wind regimes (Bora, Sirocco and low wind, from the WRF model local forecasts) follow the same analytical PDF, pointing towards a universal behaviour. We developed an idealised deterministic-stochastic model of the wind-driven sea surface currents in the Gulf of Trieste. The deterministic model consists of a time-dependent Ekman layer system, including the tidal signal, with a quadratic drag. It describes 57% of the variability, missing the fast fluctuations. The stochastic part accounts for the fast fluctuations, reproducing the superstatistical PDFs from the observations. The model, providing a huge amount of data, allows for studying the PDF of the mechanical power-input into the ocean and the associated extreme events.