Saving lives at sea: Integration of Oceanographic Models and Observations to Improve Coastguard Search and Rescue Operations

Search and rescue planning tools and programs use surface currents and wind data to perform drift simulations to determine the approximate location of persons lost at sea. Access to accurate ocean and atmospheric modeling forecast data and real-time observations is critical for drift modeling simulations to enable targeted SAR operations and planning, and narrowing of search areas in the marine environment, thus saving lives at sea. The United States Coast Guard (USCG) employs the Search and Rescue Optimal Planning System (SAROPS) for search and rescue (SAR) and planning. SAROPS accesses more than 100 environmental global and local ocean and meteorological surface currents and wind products through the Environmental Data Server (EDS) to perform thousands of Monte Carlo drift simulations and generate time-evolving probability maps which depict the envelope of the search area. The accuracy of ocean and atmospheric models combined with observations is essential to save lives. Real-time measurements are critical in: 1) areas covered by two or more models which render current speeds/directions that do not match, 2) areas where one model is not accurate at that particular time and location, 3) remote areas (e.g. small islands in the Pacific Ocean) where ocean dynamics are not adequately represented by the global models available. Inaccuracy in model data becomes very challenging for SAR of mariners lost at sea because searches will be conducted in wrong locations, thus delaying the rescue and expending resources. Observations from drifters and observational networks are essential for additional SAR guidance. 95% of SAR cases are within 20 NM from the coast.  The U.S.C.G. deploys self-locating datum marker buoys (SLDMB), Davis-style oceanographic surface drifters, from aircrafts and vessels to provide real-time currents and assist in determining the best model that matches the observations to use for drift modeling and planning. Other oceanographic measurements useful for SAR are near real-time surface currents from High Frequency Radar (HFR) networks which provide continuous maps of ocean surface currents within 200 km of the coast at high spatial (1–6 km) and temporal resolution (hourly or higher).  HFR surface currents are used for model validations, for assimilation into models, and for input to the Short-Term Predictive System (STPS), a forecast model based on HFR - all products used in SAROPS. Collaboration between the US Coast Guard and CoastPredict’s Predict-on-Time Core Project is intended to have particular impact in remote areas, e.g. remote islands where low-resolution models restrict the efficacy of drift modeling simulations for SAR. Small islands and atolls of the Pacific rely on ocean resources for their subsistence with limited technology so the likelihood of having a distress incident is higher. Getting search and rescue units (SRUs) to those remote areas requires additional time, so the uncertainty in the location of the lost craft or persons becomes larger. Access to more accurate, high-resolution models is critical and the international network for collaboration established by CoastPredict offers an opportunity to leverage existing knowledge and a shared digital infrastructure to improve capacity in areas currently under-resourced.