Gulf of Maine Operational Forecast System

Although recent technology advances in seafloor mapping systems greatly improved the quality and the efficiency of data acquisition, the resulting products (e.g., bathymetric grids, acoustic backscatter mosaics) and the overall operational efficiency are often affected by a poor awareness of the oceanographic environment in which the survey is conducted. Given the current level of predictability of the oceanographic environment, such an outcome is quite disappointing. Increasingly reliable ocean nowcast and forecast model predictions – from local to global scales – are publicly available for key environmental variables (e.g., water temperature and salinity), but they are commonly ignored by ocean mappers. This is mainly because of the lack of tools that support them in transposing such model predictions into the estimated effects on the survey data, as well as studies showing the potential benefits of such practices.

With the intent to contribute to reduce such a gap, this work evaluates some of the possible ocean mapping applications for commonly available oceanographic predictions by focusing on one of the available regional models: the NOAA’s Gulf of Maine Operational Forecast System (GoMOFS). The GoMOFS was selected because the Gulf of Maine – a semi-enclosed coastal basin along the U.S. east coast – entails a rich variety of physical oceanography phenomena (from a complex circulation system to strong tidal currents) with relative significance varying both spatially and seasonally. Thus, a good part of the study outcomes should be extensible to other models of similar (or minor) complexity. The study explores two main use cases: the uncertainty estimation of the oceanographic variability as a meaningful input during the survey planning phase; and the use of the predicted oceanographic variability along the water column to enhance and extend (or even substitute) the data collected on site by sound speed profilers, during the survey data acquisition.

After having described the techniques adopted for each use case as well as their implementation as an extension of publicly-available ocean mapping tools, this work provides some evidence that the adoption of these techniques has great potential to improve efficiency in survey operation and quality in the resulting ocean mapping products. Finally, several possible future improvements are discussed, and more extended tests to validate such techniques are proposed.

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