This project 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 ocean dynamics.
Project outcomes will support maritime industry safety by reducing risks associated with offshore oil and gas exploration and production, as well as enhancing fisheries management and hurricane/natural hazards forecasting. The GOFFISH Consortium will implement enhancements to established and next-generation GoM forecast systems operated by the U.S. Navy and NOAA, improvements in model utilization of observational data, and development of specific forecast products targeted toward end users in industry.
Building upon prior activities conducted by project team members during UGOS-1, Observing System Simulation Experiments and Observing System Experiments will be applied to quantify the utility of future observing systems and guide optimal and rapid adaptive sampling strategies. Capabilities for assimilating these data will be integrated into enhanced configurations of GoM forecast systems operated by the Navy, NOAA, and industry. The improvements in the forecasts will be assessed during a real-time field campaign using the new sampling strategies.
Integral to GOFFISH are end users of GoM forecasts, including partners from industry and NOAA hurricane and fisheries researchers. These partnerships will guide design, development, and transition of prediction tools and model products. Statistical and machine learning tools will be developed to complement model forecasts to increase predictability of full water column currents, including deep currents associated with Topographic Rossby Waves that impact critical oil and gas infrastructure. Forecast system improvements will be applied to coupled ocean-atmosphere-wave modeling systems to enhance predictability of hurricanes, sea state, and interseasonal climate forecasts, and to fisheries recruitment forecasting and dynamic management, building upon existing collaborations and advances made by project team members.