In recent years, the Office of Naval Research has funded field experiments to help establish a relocatable coastal ocean observing system, in which observations are assimilated daily into numerical models, and adaptive sampling guidance based on these models is then used to plan future trajectories of the ocean instruments (primarily underwater gliders). At previous IOAS-AOLS meetings, the methodology for an ensemble prediction system and adaptive sampling guidance used during the 2003 and 2006 field experiments in Monterey Bay has been presented.

In this talk, we will first provide initial results on the evaluation of ability of the ensemble of the Regional Ocean Modeling System (ROMS) to predict forecast error variance in the Monterey Bay region. Using ROMS data-denial experiments, we will also present the impact of assimilating glider data in sensitive areas selected by the ensemble transform Kalman filter (ETKF) adaptive sampling methodology, and we will draw preliminary conclusions about whether ensemble-based methods demonstrate the potential to be effective on a routine basis.