Research Overview of the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE)

Tamay M. Özgökmen, Francisco J. Beron-Vera, Darek Bogucki, Shuyi S. Chen, Clint Dawson, William Dewar, Annalisa Griffa, Brian K. Haus, Angelique C. Haza, Helga Huntley, Mohamed Iskandarani, Gregg Jacobs, Bert Jagers, A.D. Kirwan, Nathan Laxague, Bruce Lipphardt, Jamie MacMahan, Arthur J. Mariano, Josefina Olascoaga, Guillaume NovelliAndrew C. Poje, A.J.H.M. Reniers, Juan M. Restrepo, Brad Rosenheim, Edward H. Ryan, Conor Smith, Alexander Soloviev, Shankar Venkataramani, Ge-Cheng Zha, Ping Zhu

Research output: Contribution to journalArticlepeer-review

Abstract

CARTHE (http://carthe.org/) is a Gulf of Mexico Research Initiative (GoMRI) consortium established through a competitive peer-reviewed selection process. CARTHE comprises 26 principal investigators from 14 universities and research institutions distributed across four Gulf of Mexico states and other four states. It fuses into one group investigators with unique scientific and technical knowledge and extensive publications related to oil fate/transport processes, oceanic and atmospheric turbulence, air-sea interactions, tropical cyclones and winter storms, and coastal and nearshore modeling and observations.

Our primary goal is to accurately predict the fate of hydrocarbons released into the environment. Achieving this goal is particularly challenging since petroleum releases into the environment interact with natural processes across six orders of magnitude of time and space scales. We are developing a multi-scale modeling tool by incorporating state-of-the-art hydrophysical models, each applicable for a restricted range of scales, into a single, interconnected modeling system to predict the physical dispersal of hydrocarbons across scales ranging from the microscale at the wellhead to oceanic and atmospheric mesoscales. CARTHE is also conducting novel in-situ observations and laboratory experiments specifically designed for quantifying submesoscale dispersion as well as for both model validation and parameterization. Finally, we are providing a robust set of uncertainty metrics and analysis tools to assess model performance and quantify predictive uncertainty.

Original languageAmerican English
JournalInternational Oil Spill Conference Proceedings
Volume2014
DOIs
StatePublished - Jan 1 2014

Disciplines

  • Life Sciences

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