Experimental Validation of Intelligent Ad Hoc System for Sea Surface Velocity Approximation

This paper presents the validation of a smart ad hoc system designed to approximate the sea surface velocity field using measurements obtained from multiple floating sensors. Recognizing that point data alone cannot fully capture the domain's circulation, we propose a method that uses a simplified two-dimensional flow model as a surrogate for submesoscale flow, reconstructing the entire velocity field from the scattered data. To ensure reliable flow dynamics, the approach addresses the problem as a model-fitting process, adjusting the boundary conditions of numerical simulations to align the flow with measured data. Experimental validation was performed with the collected measurements, which involved the deployment of Global Positioning System (GPS) drifters in the Kvarner Bay area. The results highlight the system's adaptability to various domains, measurement types, and conditions, demonstrating its effectiveness for real-world submesoscale applications where an approximate velocity field is acceptable.