Dynamical systems for remote validation of very high-resolution ocean models

TL;DR

This paper introduces a new method for validating high-resolution ocean models using satellite imagery and dynamical systems, enabling better assessment of model accuracy in coastal areas without extensive in situ data.

Contribution

It proposes a novel remote validation approach linking satellite data with model outputs through dynamical systems, improving validation in data-scarce coastal regions.

Findings

Effective correlation between satellite observations and model experiments.

Quantitative performance index for model validation.

Enhanced validation accuracy in coastal zones.

Abstract

This paper presents and investigates a novel methodology for validating high-resolution ocean models using satellite imagery. High-resolution ocean models provide detailed information in coastal areas where other available data products are too coarse. Models are usually fitted by comparing them with observations; However, accessing in situ data in all small coastal areas is not feasible, as in situ observations are scarce and obtained through dedicated ships or instruments in limited and selected regions. Our work aims to use alternative remote sensing information to overcome this challenge. The approach involves establishing connections between the satellite observations and the outcomes of various computational experiments carried out using the Regional Ocean Modeling System (ROMS), which allows the selection of different parameters to run the ocean model. These choices are not fully determined a priori and each one produces distinct outputs, which are then linked to the images through dynamical systems objects. By defining a performance index, we are able to quantify which experiment provides a better representation of the local ocean state.