The Center for the Integrated Modeling and Analysis of the Gulf Ecosystem

A tale of two Gulf spills: A research consortium of 19 institutions from 5 countries studying the impacts of oil spills on the Gulf of Mexico.

Task 1 Items

Task 1 Items (4)

Robin Rowland, an Eckerd College art student, has collaborated with Claire Paris and Task 1 members to create a 3D sculpture of the Deepwater Horizon oil dispersion. Using dispersion models from Paris' group, Rowland's work - made entirely from test tube caps - shows the density and location of suspended oil in the northern Gulf. "She wants to be accurate," Paris said, "she's asking how many droplets there are at different depths, she wants our model outputs to represent her work."

Connectivity Modeling System: A probabilistic modeling tool for the multi-scale tracking of biotic and abiotic variability in the ocean

Pelagic organisms' movement and motion of buoyant particles are driven by processes operating across multiple, spatial and temporal scales. We developed a probabilistic, multi-scale model, the Connectivity Modeling System (CMS), to gain a mechanistic understanding of dispersion and migration processes in the ocean. The model couples offline a new nested-grid technique to a stochastic Lagrangian framework where individual variability is introduced by drawing particles' attributes at random from specified probability distributions of traits. This allows 1) to track seamlessly a large number of both actively swimming and inertial particles over multiple, independent ocean model domains and 2) to generate ensemble forecasts or hindcasts of the particles' three dimensional trajectories, dispersal kernels, and transition probability matrices used for connectivity estimates. In addition, CMS provides Lagrangian descriptions of oceanic phenomena (advection, dispersion, retention) and can be used in a broad range of oceanographic applications, from the fate of pollutants to the pathways of water masses in the global ocean. Here we describe the CMS modular system where particle behavior can be augmented with specific features, and a parallel module implementation simplifies data management and CPU intensive computations associated with solving for the tracking of millions of active particles. Some novel features include on-the-fly data access of operational hydrodynamic models, individual particle variability and inertial motion, and multi-nesting capabilities to optimize resolution. We demonstrate the performance of the interpolation algorithm by testing accuracy in tracing the flow stream lines in both time and space and the efficacy of probabilistic modeling in evaluating the bio-physical coupling against empirical data. Finally, following recommended practices for the development of community models, we provide an open source code with a series of coupled standalone, optional modules detailed in a user's guide.

Ref:  Paris CB, Helgers J, Van Sebille E, Srinivasan A (2013) Connectivity Modeling System (CMS): A multi-scale tool for the tracking of biotic and abiotic variability in the ocean, Environmental Modelling & Software, 42: 47-54

Near Field Modeling Listserv hosted by Texas A&M University

This ListServ is private and intended to foster a discussion on near field (within 1 to 5 km radius) modeling of accidental subsea oil leaks and well blowouts. This list serve got its start through discussions by three of the Consortia recently funded by the BP/Gulf of Mexico Research Initiative (GoMRI), though the ListServ is free and participation includes many engineers, scientists and policy makers from a wide range of institutions.

In the wake of the Deepwater Horizon accident, many different teams are running, building, or developing near field models, both to hindcast the Deepwater Horizon accident and to understand risks of and aid in response during potential future accidents. These include simple analytical models and integral plume models to fully three-dimensional computational fluid dynamics models. This list serv was founded so that these developers, users, and policy makers could collaborate closely, share information, and communicate often as each project moves forward. This List Serve is one avenue to host these activities. We also host group conference calls and expect to host several modeling workshops for face-to-face discussions.

The main objective of this list serve is to support individual modeling efforts by pooling understanding in areas needed by all models (i.e., equations of state, dissolution models, hydrocarbon models, etc.). We do not expect or desire to converge on one model, but rather to help each model develop to its maximum potential. This modeling group should also work to inform laboratory and field experiments on near-field plume physics and chemistry.


Comment on "Evolution of the Macondo Well Blowout: Simulating the Effects of the Circulation and Synthetic Dispersants on the Subsea Oil Transport

Paris et al.(1) use regional circulation and transport models to simulate the transport of oil from the Macondo well blowout, and conclude that subsurface dispersants may not have been particularly helpful in keeping oil submerged. They reach this conclusion because, without treatment, their assumed droplet sizes were already sufficiently small that much of the oil would have stayed submerged anyway. However this conclusion is based on a model of initial droplet sizes that we do not believe is appropriate.

Ref: Adams, E. E., S. A. Socolofsky, M. Boufadel, Comment on "Evolution of the Macondo Well Blowout: Simulating the Effects of the Circulation and Synthetic Dispersants on the Subsea Oil Transport, Environmental Science and Technology, 2013, 47(20), 11905-11905.

Podcasts from The Loop

The Loop is a series of podcasts which take an in depth look at C-IMAGE research. Partnering with Mind Open Media reporters Ari Daniel Shapiro and David Levin, our researchers share the importance of their studies and how they help our understanding of oil spills. David and Ari have produced eight podcasts and have more in the queue. The podcasts are linked below. Plug in and learn about our research!

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