PASSENGERS-2022-Fall

Our modeling and experimental research program aims to improve the capability of data-assimilative ocean models to predict acoustic propagation in dynamic oceanographic environments, while forming a better understanding of the true uncertainty attached to these forecasts. Our study includes real-time testing and comparison of several novel and diverse data assimilation and adaptive sampling techniques that minimize acoustic uncertainty. We will contrast starkly different ocean data-assimilation approaches – the use of coordinated teams of gliders and the most advanced algorithms on land vs. onboard algorithms paired with fresh data from sensors on the vehicle. Simultaneously we will collect a paired acoustic and oceanographic data set that will be ideally suited to evaluate and compare novel state estimation and machine learning approaches both on land and at sea for many years of future research.