An Operational Technology for Assimilating Lagrangian Data Based on Dynamical Systems Techniques

Much data in the ocean is Lagrangian in nature. Its full use in ocean prediction could advance significantly the Navy's ability both to predict ocean conditions and to assess the optimal strategies for deploying Lagrangian instruments and their associated sensors. The long-term objective of this project is the building of comprehensive and reliable DA platform for incorporating Lagrangian data into ocean state analysis and forecasting. By Lagrangian data, we mean both positions of moving instruments and also measurements taken by them. Autonomous vehicles (AUVs) that glide or maneuver in the ocean are new types of moving instruments, and they will be incorporated into the Lagrangian DA (LaDA) platform. This platform will be ideal for designing and performing the autonomous ocean sampling network, adaptive observations, and optimal deployment plans of such moving instruments. The new LaDA platform will form the basis of an integrated prediction scheme for the ocean that can feed on both purely Lagrangian and mixed source data. By utilizing the Lagrangian data that have been underused in the past, the new platform is expected to enhance a naval predicted capacity.