This project, under lead PI Eric Chassignet (FSU), aims to achieve measurable and significant improvements in short- to medium-range (1- to 10-day), subseasonal, and long-range (3- to 6-month) prediction skill of sustained continuous operational forecasts of Gulf of Mexico (GoM) ocean dynamics. The specific objectives are to i) Improve the prediction skill for Gulf of Mexico operational forecast models run within NOAA, U.S. Navy, and industry environments by increasing and enhancing model and DA capabilities and by maximizing the use of existing and new near-real-time observations, including those adaptively deployed; ii) Develop new derived products and tools from observations and numerical models to provide skillful operational forecasts and knowledge of full-water-column currents (including upper ocean circulation and near-bottom currents); and iii) Apply improvements in hydrodynamic forecasting capabilities to hurricane forecasting and fisheries management.