During the August–September 2003 Autonomous Ocean Sampling Network-II experiment, the Harvard Ocean Prediction System (HOPS) and Error Subspace Statistical Estimation (ESSE) system were utilized in real-time to forecast physical fields and uncertainties, assimilate various ocean measurements (CTD, AUVs, gliders and SST data), provide suggestions for adaptive sampling, and guide dynamical investigations. The qualitative evaluations of the forecasts showed that many of the surface ocean features were predicted, but that their detailed positions and shapes were less accurate. The root-mean-square errors of the real-time forecasts showed that the forecasts had skill out to two days. Mean one-day forecast temperature RMS error was View the MathML source less than persistence RMS error. Mean two-day forecast temperature RMS error was View the MathML source less than persistence RMS error. Mean one- or two-day salinity RMS error was 0.036 PSU less than persistence RMS error. The real-time skill in the surface was found to be greater than the skill at depth. Pattern correlation coefficient comparisons showed, on average, greater skill than the RMS errors. For simulations lasting 10 or more days, uncertainties in the boundaries could lead to errors in the Monterey Bay region.