Assessment of Metocean Forecast Data and Consensus Forecasting for Maritime Search and Rescue and Pollutant Response Applications

Abstract

Effective prediction of objects drifting on the water surface is essential to successful maritime search and rescue (SAR) services, since a more accurate prediction of the object’s likely location results in a greater probability for the success of a SAR operation. SAR drift models, based on Lagrangian stochastic particle trajectory models, are frequently utilised for this task. More recently, metocean (meteorological and oceanographic) forecast data has been used as input to these models to provide the environmental forcing (due to winds and ocean currents) that the object may be subject to. Further, the slip of a drifting object across the water surface due to the ambient wind and waves (irrespective of currents) is described by its leeway drift coefficients, which are also required by the SAR drift model to calculate the potential drift of the object. This study examined several ways to improve the prediction of an objects drift on the water surface, with the primary focus being the improvement of SAR forecasting. To achieve this, many simulations were undertaken, comparing the trajectories of actual drifters deployed in the ocean, and the corresponding model simulations of drift, using the commercially available SARMAP (Search and Rescue Mapping and Analysis Program) SAR drift model. Each drifter trajectory was simulated independently using a different ocean model to provide ocean current forcing. The ocean models tested included BLUElink, FOAM (Forecasting Ocean Assimilation Model), HYCOM (Hybrid Coordinate Ocean Model) and NCOM (Navy Coastal Ocean Model).