Superstatistical analysis of sealevel fluctuations

TL;DR

This paper analyzes UK sea level time series, demonstrating that superstatistical models, especially $$-superstatistics, effectively describe the stochastic fluctuations after removing deterministic tides, with consistent results across multiple locations.

Contribution

It introduces a superstatistical approach to model sea level fluctuations, highlighting the suitability of $$-superstatistics for short-term sea level differences.

Findings

$$-superstatistics best fits the data

Model effectively captures short-term sea level differences

Consistent results across five UK locations

Abstract

We perform a statistical analysis of measured time series of sea levels at various coastal locations in the UK, measured at time differences of 15 minutes over the past 20 years. When the astronomical tide and other deterministic components are subtracted, a stochastic signal remains which is well-described by a superstatistical model. We do various tests on the measured time series, and compare the data of 5 different UK locations. Overall it appears that $\chi^2$-superstatistics is best suitable to describe the data, in particular when one looks at the dynamics of sealevel {\em differences} on short time scales.