Abstract
Despite recent technological advances in seafloor mapping systems, the resulting products and the overall operational efficiency of surveys are often affected by poor awareness of the oceanographic environment in which the surveys are conducted. Increasingly reliable ocean nowcast and forecast model predictions of key environmental variables – from local to global scales – are publicly available, but they are often not used by ocean mappers. With the intention of rectifying this situation, this work evaluates some possible ocean mapping applications for commonly available oceanographic predictions by focusing on one of the available regional models: NOAA’s Gulf of Maine Operational Forecast System. The study explores two main use cases: the use of predicted oceanographic variability in the water column to enhance and extend (or even substitute) the data collected on-site by sound speed profilers during survey data acquisition; and, the uncertainty estimation of oceanographic variability as a meaningful input to estimate the optimal time between sound speed casts. After having described the techniques adopted for each use case and their implementation as an extension of publicly-available ocean mapping tools, this work provides evidence that the adoption of these techniques has the potential to improve efficiency in survey operations as well as the quality of the resulting ocean mapping products.
Highlights
Recent technological advances in seafloor mapping systems have greatly improved the quality and the efficiency of data acquisition (Mayer, 2014; Hughes Clarke, 2018; Lamarche and Lurton, 2018)
By leveraging predictions from Gulf of Maine Operational Forecast System (GoMOFS), this study explores two main use cases: the use of predicted oceanographic variability in the water column to enhance and extend the data collected on-site by sound speed profilers during the survey data acquisition; and, the use of uncertainty estimation of oceanographic variability as a meaningful input to estimate the optimal time between sound speed casts
The use of the GoMOFS-predicted oceanographic variability in the water column in place of the observed profiles was evaluated in Figure 10 for each of the three input subsets
Summary
Recent technological advances in seafloor mapping systems have greatly improved the quality and the efficiency of data acquisition (Mayer, 2014; Hughes Clarke, 2018; Lamarche and Lurton, 2018). Reliable nowcast and forecast guidance from operational oceanographic forecast modeling systems – from local to global scales – are publicly available for key environmental variables (e.g., water temperature and salinity), but they are often not used by ocean mappers (Dudhia, 2014; Bauer et al, 2015; Tonani et al, 2015; Powers et al, 2017; Masetti et al, 2018) This is likely due to the limited awareness of these predictions and the lack of tools that allow surveyors to transform model predictions into the estimated effects on the survey data as well as the limited number of studies that have shown the potential benefits incorporating modeled data (Beaudoin et al, 2013; Ros, 2018; Sowers et al, 2019). Several possible future improvements are discussed and additional tests to validate such techniques are proposed
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