<div>In this study, two years (2021-2022) of High Frequency Radar (HFR) sea surface current data (30 min time resolution) and modelled near-bottom wind data (1 h time resolution) in the Gulf of Trieste (Northern Adriatic Sea) are analysed through a superstatistical (a superposition of different statistics) approach.</div> <div> </div> <div>Three distinct main wind forcing regimes are present in the Gulf of Trieste: Bora, Sirocco and low wind. Bora and Sirocco are strong winds whose characteristics are different: the Bora is a cold wind that blows in gusts from the East-North-East with a short fetch, the Sirocco is a warm wind that blows from the South with a fetch along the entire Adriatic.</div> <div> </div> <div>The currents in the Gulf of Trieste are forced and highly dependent on such variable wind conditions. It results in a succession of different sea current dynamics on different time scales, asking for a superstatistical analysis of the sea surface current data. From the oceanic signal it is possible to extract two different time scales: a relaxation time <em>τ</em>, the time the system spends to reach the local equilibrium and a larger timescale <em>T</em>, the time for which the signal is locally gaussian. This permits extracting a slowly varying <em>β(t)</em> strictly connected to the original time series’ local variance <em>σ<sup>2</sup>=β<sup>-1</sup></em>. Neither <em>β</em> nor <em>σ<sup>2</sup></em> show well known PDFs and have algebraic tails. Contrary to what one might expect, they show a universal behaviour with respect to the different wind regimes blowing over the Gulf of Trieste.</div>

Abstract. Two years (2021–2022) of High Frequency Radar (HFR) sea surface current data in the Gulf of Trieste (Northern Adriatic Sea) are analysed. Two different time scales are extracted using superstatistical formalism: a relaxation time and a larger timescale over which the system is gaussian. A new analytical universality class of Probability Density Functions (PDFs) is proposed for ocean current data combining a gaussian PDF for the fast fluctuations and a convolution of exponential PDFs for the slowly evolving variance of the gaussian. The Gaussian PDF has maximum entropy for real-valued variables with a given variance. If a positive variable, as is a variance, has a specified mean, the maximum entropy solution is an exponential PDF. Here it is the sum of two exponentials, reflecting the two spatial degrees of freedom. In the Gulf of Trieste there are three distinct main wind forcing regimes: Bora, Sirocco and low wind, leading to a succession of different sea current dynamics on different time scales. The universality class PDF successfully fits the observed data over the two observation years and also for each wind regime separately with a different variance of the variance PDF, which is the only free parameter in all the fits.