Analysis of Sparse and Noisy Ocean Current Data Using Flow Decomposition. Part II: Applications to Eulerian and Lagrangian Data

Abstract

The capability of the reconstruction scheme developed in Part I is demonstrated here through three practical applications. First, the nonlinear regression model is used to reproduce the upper-layer three-dimensional circulation of the eastern Black Sea from model data distorted by white and red noises. Second, the quasigeostrophic approximation is used to reconstruct the shallow water circulation pattern in an open domain with various sampling strategies. Third, the large-scale circulation in the Southern Ocean is reproduced from the First Global Atmospheric Research Program (GARP) Global Experiment (FGGE) drifter data with noncontrollable noise statistics. All three cases confirm that the theoretical approach is robust to various noise-to-signal ratios, number of observations, and station disposition. Using the simplified open boundary condition for analyzing long-term observational data is recommended because the nonlinear regression procedure requires considerable computer resources.