Improving marine drift and dispersion forecasts
Canada's coastline is by far the longest in the world and covers three oceans, two of which are at least seasonally ice-covered. Being able to respond to emergencies all along this coast requires appropriate equipment, reliable and efficient communication systems and trained personnel stationed at strategic locations. It also requires accurate hindcasts and forecasts of winds and surface currents that are necessary to estimate where a person at sea or an oil patch should be found. Time is key and this is particularly true in harsh ice-infested coastal environments: survival time is shorter, conditions can be extremely difficult, and equipment is highly pressured. In the case of an oil spill, the presence of sea ice can simply make the recovery impossible, which requires knowing where it will be when it melts and trapped oil is released. This is a paramount challenge, which adds up to the bigger challenge of tracking how the oil patch disperses and evolves in a cold multi-phase environment and quantifying the short- and long-term impacts on the ecosystem. In this one-year project, we propose to improve surface drift forecasts in seasonally ice-infested seas by combining multi-scale operational modeling and monitoring systems. We will carry this project in the Lower St. Lawrence Estuary (LSLE), a particularly dynamic marine environment where a suite of research and operational modeling and monitoring systems is maintained. This suite includes a 5-km resolution operational coupled ice-atmosphere-ocean numerical model, a 400-m resolution tidal ocean model, four high-frequency radars (HFR) measuring surface currents in real-time, and one automatic buoy providing real-time surface measurements during Summer. The HFR array that was recently deployed in the area allows for a truly innovative and ground-breaking study of marine dispersion. In this project, we plan to supplement models and real-time observations with drifting buoy data against which they will be tested for the first time, and with a spectral wave model that will estimate the wave-induced contribution to the surface drift, a phenomenon that has been so far ignored. A special focus will be placed on surface drift in the presence of sea ice so that the entire spectrum of environmental conditions affecting surface drift is covered. This project directly involves Canadian marine operational service providers and benefits from the support of the Canadian Operation Network of Coupled Environmental Prediction Systems and the Canadian Coast Guard Environmental Response Team.