Effective model coupling for oil spills
The project aimed at developing an advanced alert and tracking system for chemical effluents and oil pollution using an integrated set of data and tools. Special areas of interest are those that are vulnerable to pollution, such as the Mediterranean sea. By employing modern space technologies, and recent meteorological and ocean scientific research, the system may support prevention, mitigation and assessment of oil or chemical marine pollution. Normally, variable geographical meteo-ocean conditions cause movement of oil spills that can be better predicted by using gridded meteo-ocean data. Yet, model performance heavily relies on the reliability and quality of such data, particularly under stormy conditions. To answer these need, researchers completed a detailed review on model coupling issues and took into consideration physical studies, algorithmic tools and scientific/operational systems with well-defined model coupling strategies. This key project result allows coupling the atmosphere, ocean and wave part of model chains at a higher resolution level for improving pollutant drift modelling. Model communication is conducted through a 'standard' forcing chain. For instance, atmosphere forcing (winds) drive sea waves, while winds, surface heating and salinity fluxes cause ocean dynamics. Winds, waves and ocean currents provide information on pollution spills, while feedback information is derived by studying the influences of waves to atmosphere and ocean, and, of ocean to waves. This coupling would improve the description of the dynamics of the atmosphere-sea surface boundary layer and provide a better assessment of the key constituents of surface pollution, such as oil slicks. Additionally, in-situ and/or earth observation data can be linked to models as initial conditions to run the models and play a key role in model's calibration/validation. This result is expected to significantly contribute to the improvement of coastal disaster emergency management activities of national/regional authorities and organisations.
