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Advanced Lagrangian Predictions for Hazards Assessments (NSF-ALPHA)

MSEAS Group Page

P.F.J. Lermusiaux, P.J. Haley, F. Feppon, C. Kulkarni,
S. Jana, C. Mirabito,
T. Peacock

Massachusetts Institute of Technology
Center for Ocean Engineering
Mechanical Engineering
Cambridge, Massachusetts

Project Summary
Ongoing MIT-MSEAS Research
Additional NSF-ALPHA Links
Background Information


This research is sponsored by the National Science Foundation.

Project Summary

Hazards due to the fundamental process of advection of natural and anthropogenic material in environmental flows are ubiquitous and profoundly impact society; preparedness and effective response can save many lives, untold environmental damage and enormous financial cost. Recent catastrophic examples include: oil spill advection during the Deep Water Horizon disaster, the passage of the ash cloud from the Eyjafjallajökull volcano through commercial air space, and the trail of radioactive waste from the Fukushima reactor disaster. On a day-to-day operational level, search-and-rescue operations at sea rely critically on correctly modeling and interpreting flow transport in order to inform life-or-death decisions. Understanding how flow transport is organized and predicting where things go in complex environmental flows remains a formidable scientific challenge, however, due to unsteady nonlinear and multiscale flows, ambiguities in defining material transport, multiple sources of uncertainty, the difficulty of identifying and acquiring pertinent data to assimilate into models, the variability of predictions across different models, and the complexity of analyzing vast data sets and visually representing the results.

The NSF-ALPHA (Advanced Lagrangian Predictions for Hazards Assessments) team (MIT, WHOI, Virginia Tech and UC Berkeley) proposes transformational progress in tackling these science issues by exploiting and advancing recent fundamental breakthroughs in four-dimensional (3D plus time) Lagrangian methods. An integrated theoretical, computational and observational approach will be employed to develop, implement and utilize these cutting-edge Lagrangian methods with data-driven modeling for the purpose of uncovering, quantifying and predicting key transport processes and structures during regional flow-based hazards in the ocean and atmosphere. The challenges are broad in scope, encompassing engineering, geosciences, applied mathematics, and computational and information science and engineering.

The overall goal of the ALPHA project is to employ an integrated theoretical, computational and observational approach to develop, implement and utilize these cutting-edge Lagrangian methods with data-driven modeling for the purpose of uncovering, quantifying and predicting key transport processes and four-dimensional (3D plus time) structures during regional flow-based hazards in the ocean and atmosphere.

Background information is available below.

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Ongoing MIT-MSEAS Research

Long-Term (Collaborative) MIT-MSEAS Goal:

Develop and apply ocean modeling, data assimilation and Lagrangian methods for regional transport process studies during flow-based hazards

Specific MIT-MSEAS Objectives:

Reanalysis of July/August/September 2014

We have completed the initial reanalysis of ocean dynamical fields in the Nantucket and Martha's Vineyard coastal region during the July/August/September 2014 time period. We provide the MSEAS-PE ocean re-analysis simulations as well as the data processed by the MSEAS group for input, initialization, and/or forcing to these simulations.

Reanalysis main page: processed and analyzed data, MSEAS-PE ocean re-analysis simulations, and data sources


MSEAS NSF-ALPHA-supported Publications

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Additional NSF-ALPHA Links

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Background Information

The NSF-ALPHA team approach exploits and advances novel LCS methods to support the integration of observing, modeling and data analysis systems, enabling a transformational advance in current capabilities for forecasting and mitigating environmental flow hazards. To rigorously validate our analytical and computational advances we will perform ocean and atmosphere field tests, followed by a capstone coupled air-sea experiment simulating a hazard scenario. Leveraging existing sea and air observing capabilities, the field studies will be performed in the New England region of the East Coast, in the vicinity of the Martha’s Vineyard Coastal Observatory (MVCO), and at Virginia Tech’s Kentland farm airfield, which is a FAA-designated unmanned aircraft systems (UAS) test site. During these studies, the LCS methodology will be integrated with in situ and remote observations, adaptive autonomous observing platforms, advanced multi-resolution modeling, data-assimilative predictions with uncertainty, and efficient computations and visualizations. Notable features of the MVCO site selected for the coupled air-sea hazard scenario include: (1) Proximity to a nearby airfield to support simultaneous ocean and airborne studies; (2) Several ongoing or planned industrial activities within the region (e.g. nuclear power stations, wind farm construction) that have the potential to initiate hazards; (3) The existence of three-dimensional ocean jet structures, via which pollution could potentially impact regional ecosystems and fisheries; (4) Proximity to our US Coast Guard partner based at Rhode Island. Furthermore, we propose to provide a rapid response capability to a regional oceanic hazard of opportunity during the tenure of the project.

The research of our multi-institution (MIT, WHOI, Virginia Tech, UC Berkeley) ALPHA team encompasses engineering, geosciences, computational and information science and engineering, and applied mathematics. Our research is highly interdisciplinary, in large part because the underlying topic of unsteady flow transport is so fundamental that it transcends traditional disciplinary boundaries. We have extensive connections with international collaborators (ETH Zurich, U. of Western Australia, U. of New South Wales, Bologna U.), regional and government agencies (NERACOOS, US Coast Guard, USGS), local K-to-12 schools and communities (e.g. Gloucester and New Bedford fishermen), and major industrial partners (Shell Oil, SINTEF, IBM), thereby ensuring regional, national and global impact. The project is led by Prof. Thomas Peacock (MIT).

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