Lagrangian measurements from passive ocean instruments provide a useful source of data
for estimating and forecasting the ocean's state (velocity field, salinity field, etc.). However …

In the summer and fall of 2012, during the GLAD experiment in the Gulf of Mexico, the
Consortium for Advanced Research on Transport of Hydrocarbon in the Environment …

Lagrangian data arise from instruments that are carried by the flow in a fluid field.
Assimilation of such data into ocean models presents a challenge due to the potential …

The assimilation of position data from Lagrangian observing platforms is underdeveloped in
operational applications because of two main challenges: 1) nonlinear growth of model and …

Lagrangian measurements provide a significant portion of the data collected in the ocean.
Difficulties arise in their assimilation, however, since Lagrangian data are described in a …

A potential problem with Ensemble Kalman Filter is the implicit Gaussian assumption at
analysis times. Here we explore the performance of a recently proposed fully nonlinear …

The effectiveness of an ensemble Kalman filter (EnKF) is assessed in the Selat Pauh of
Singapore using observing system simulation experiment. Perfect model experiments are …

The most widely used methods of data assimilation in large-scale oceanography, such as
the Simple Ocean Data Assimilation (SODA) algorithm, specify the background error …

I TRODUCTIO We describe a discrete solution of the optimal nonlinear filter that generalizes
the optimality of the correction step of the ensemble Kalman filters to nonlinear systems. This …

Twin experiments were made to compare the reduced rank Kalman filter (RRKF), ensemble
Kalman filter (EnKF), and ensemble square‐root Kalman filter (EnSKF) for coastal ocean …