Efficient tools for marine operational forecast and oil spill tracking

Mar Pollut Bull. 2013 Jun 15;71(1-2):139-51. doi: 10.1016/j.marpolbul.2013.03.022. Epub 2013 Apr 30.

Abstract

Ocean forecasting and oil spill modelling and tracking are complex activities requiring specialised institutions. In this work we present a lighter solution based on the Operational Ocean Forecast Python Engine (OOFε) and the oil spill model General NOAA Operational Modelling Environment (GNOME). These two are robust relocatable and simple to implement and maintain. Implementations of the operational engine in three different regions with distinct oceanic systems, using the ocean model Regional Ocean Modelling System (ROMS), are described, namely the Galician region, the southeastern Brazilian waters and the Texas-Louisiana shelf. GNOME was able to simulate the fate of the Prestige oil spill (Galicia) and compared well with observations of the Krimsk accident (Texas). Scenarios of hypothetical spills in Campos Basin (Brazil) are illustrated, evidencing the sensitiveness to the dynamical system. OOFε and GNOME are proved to be valuable, efficient and low cost tools and can be seen as an intermediate stage towards more complex operational implementations of ocean forecasting and oil spill modelling strategies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Environmental Monitoring / methods*
  • Models, Chemical*
  • Petroleum / analysis*
  • Petroleum Pollution / statistics & numerical data*
  • Seawater / chemistry
  • Water Movements
  • Water Pollutants, Chemical / analysis*

Substances

  • Petroleum
  • Water Pollutants, Chemical