The objective of this research is to advance capabilities in ocean data assimilation and probabilistic forecasting developing control and optimization of swarms of unmanned underwater vehicles (UUV) to provide observations informing assimilative forecast models. Such optimization and assimilation encompass underwater, airborne and satellite observing systems supporting global and regional ocean forecasts of temperature, salinity, and mixed-layer depth. Such forecasts include representation of forecast uncertainty in coupled atmosphere-ocean-ice-wave systems, extending from standard deterministic models forecast ensembles enabling probabilistic ocean forecasting. High priority efforts presently include automated targeting for unmanned ocean observing systems, representing probability in ocean/acoustic systems, and energy management for persistent observing swarms. Long term work is developing cutting edge capabilities that transition to operational forecast centers.