Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies.

There is a greater probability of more frequent and/or larger oil spills in the Arctic region due to increased maritime shipping and natural resource development. Accordingly, there is an increasing need for effective spilled-oil computer modeling to help emergency oil spill response decision makers, especially in waters where sea ice is present. The National Oceanic & Atmospheric Administration (NOAA) Office of Response & Restoration (OR&R) provides scientific support to the U.S. Coast Guard Federal On-Scene Coordinator (FOSC) during oil spill response. OR&R’s modeling products must provide adequate spill trajectory predictions so that response efforts minimize economic, cultural, and ecologic impacts, including those to species, habitats, and food supplies. The Coastal Response Research Center is conducting a project entitled Oil Spill Modeling for Improved Response to Arctic Maritime Spills: The Path Forward, in conjunction with modelers, responders, and researchers. A goal of the project is to prioritize new investments in model and tool development to improve response effectiveness in the Arctic. The project delineated FOSC needs during Arctic maritime spill response and provided a solution communicating sources of uncertainty in model outputs using a Confidence Estimates of Oil Model Inputs and Outputs (CEOMIO) table. The table shows the level of confidence (high, medium, low) in a model’s trajectory prediction over scenario-specific time intervals and the contribution of different component inputs (e.g., temperature, wind, ice) to that result.

Lab experiments were conducted to investigate the time development of oil droplet size distribution and volume-based median diameter, d₅₀^v, under a spilling breaking wave. Results show that the size distribution varies continuously during the experiment. To aid the discussion, we introduce a conceptual framework describing the phases of the entrainment process, comprising injection, breakup, turbulent transport, and buoyant rise and resurfacing. A one-dimensional model was implemented, describing the turbulent transport and buoyant rise phases based on a stochastic transport equation and vertical diffusivity profile: These are the same vertical transport mechanisms found in operational oil spill models. It was found to reproduce the time development of the d₅₀^v after the breakup phase well, when initialized with a suitably fitted log-normal droplet size distribution. The measurements showed a decrease in d₅₀^v with time, after the breakup phase, as t^-0.537 and t^-0.443 at two different sampling locations. The model can reproduce these results, but is sensitive to the initial size distribution, both initial median diameter and standard deviation. Our results highlight the inherent challenges in measuring oil droplet size distributions that change with both time and spatial location, and never truly reach an equilibrium. We believe that a way forward is to use models actively in the interpretation of experimental results, acting as "digital twins" of the system studied in the lab.

The National Contingency Plan (NCP) requires that Area Contingency Plans (ACPs) be adequate to address the removal of a worst case discharge from a vessel or facility operating in or near the area. The U.S. Coast Guard took this requirement further by issuing guidance in 1992 that ACPs address response to worst case, maximum most probable, and most probable discharges. As a result, many ACPs include area-specific scenarios applying these discharge quantities. However, there remains very little guidance about including trajectories in the ACPs. For example, only three of California's six ACPs include trajectories from computer models; the remaining three contain only oil spill scenarios that incorporate committee-selected environmental conditions to help estimate where oil might go. The 2000 revision of the San Francisco Bay and Delta ACP includes a new type of trajectory using the National Oceanic and Atmospheric Administration's (NOAA's) Trajectory Analysis Planner (TAP II). TAP II is a statistical model rather than a single scenario-based deterministic model. It generates statistics that describe oil spill behavior using an ensemble modeling approach. These statistics are generated from an ensemble of thousands of possible trajectories resulting from hundreds of oil spill scenarios computed within a given location. This approach is designed specifically for planning purposes, and not response. A statistics-based approach facilitates the planning process by providing key information, including which shorelines have the highest probability of being impacted, the size of the area that might be affected, how quickly a response should be mounted, what quantity of oil could impact a shoreline location, which resources will be oiled, which assets will be affected, and the most threatening origin of possible oil discharge. The authors describe how the TAP II model employs ensemble modeling, detail its application in the 2000 version of the San Francisco Bay and Delta ACP, and discuss possibilities for future applications.

Over the last decade, there have been more and more oil spill responses effected by subsurface waves in the coastal zone. These have ranged from oil leaking from sunken ships to heavy oils that have sunk to the bottom. A primary example is the DBL 152 incident on the Gulf of Mexico coast in November, 2006. The incident resulted in approximately 70,000 barrels of Slurry Oil (API 4) being released and sinking to the bottom. Waves played a significant role in the mobilization of the oil on the bottom, in addition to effecting sediment loading in the subsurface, often restricting visibility and making ROV operations difficult. Waves can also play a major role disturbing sunken ships, and evidenced by the SS Jacob Luckenbach, sunken off San Francisco during WWII. The ship was a source of occasional incidents of oiled birds washing ashore after certain winter storms. The oil on the ship was removed as part of a major remediation effort in the summer of 2002.The oil spill response community will be more effective, particularly with subsurface oils, with a better understanding of the role of waves on the mobilization of sediment and other deposited substances (such as subsurface oil). This paper provides an overview of wave mechanics and the implications for subsurface oil movement and spill response activities, using examples from the DBL 152, SS Jacob Luckenbach, and other recent incidents. Shortcomings of current understanding will be highlighted, with suggestions for future research offered.