Preprints
https://doi.org/10.5194/egusphere-2024-3391
https://doi.org/10.5194/egusphere-2024-3391
16 Jan 2025
 | 16 Jan 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Comparing an idealized deterministic-stochastic model (SUP model, version 1) of the tide-and-wind driven sea surface currents in the Gulf of Trieste to HF Radar observations

Sofia Flora, Laura Ursella, and Achim Wirth

Abstract. In the Gulf of Trieste the sea surface currents are observed by High Frequency Radar for almost two years (2021–2022) at a temporal resolution of 30 min. We developed a hierarchy of idealized models to simulate the observed sea surface currents, combining a deterministic and a stochastic approach, in order to reproduce the externally forced motion and the internal variability, which is characterized by a fat-tailed statistics. The deterministic signal includes tidal and Ekman forcing and resolves the slowly varying part of the flow, while the stochastic signal represents the fast-varying small-scale dynamics, characterized by Gaussian or fat-tailed statistics, depending on the statistical used. This is done using Langevin equations and modified Langevin equations with a Gamma distributed variance parameter. The models were adapted to resolve the dynamics under nine tidal and wind Forcing Protocols in order to best fit the observed forced motion and internal variability Probability Density Function (PDF). The stochastic signal requires 2 stochastic degrees of freedom when the averaged tidal forcing is adopted, while it needs 1/2 stochastic degree of freedom when the complete tidal forcing is used. Despite its idealization, the deterministic-stochastic model with stochastic fat-tailed statistics captures the essential dynamics and permits to mimic the observed PDF. Moreover, a Fluctuation Response Relation is valid when the stochastic signal is perturbed, showing that the response to an external perturbation can be obtained by considering the fluctuations of the unperturbed system.

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We developed a hierarchy of idealized deterministic-stochastic models to simulate the sea...
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