A framework to quantify uncertainty in simulations of oil transport in the ocean

Handle URI:
http://hdl.handle.net/10754/621372
Title:
A framework to quantify uncertainty in simulations of oil transport in the ocean
Authors:
Gonçalves, Rafael C.; Iskandarani, Mohamed; Srinivasan, Ashwanth; Thacker, W. Carlisle; Chassignet, Eric; Knio, Omar
Abstract:
An uncertainty quantification framework is developed for the DeepC Oil Model based on a nonintrusive polynomial chaos method. This allows the model's output to be presented in a probabilistic framework so that the model's predictions reflect the uncertainty in the model's input data. The new capability is illustrated by simulating the far-field dispersal of oil in a Deepwater Horizon blowout scenario. The uncertain input consisted of ocean current and oil droplet size data and the main model output analyzed is the ensuing oil concentration in the Gulf of Mexico. A 1331 member ensemble was used to construct a surrogate for the model which was then mined for statistical information. The mean and standard deviations in the oil concentration were calculated for up to 30 days, and the total contribution of each input parameter to the model's uncertainty was quantified at different depths. Also, probability density functions of oil concentration were constructed by sampling the surrogate and used to elaborate probabilistic hazard maps of oil impact. The performance of the surrogate was constantly monitored in order to demarcate the space-time zones where its estimates are reliable. © 2016. American Geophysical Union.
KAUST Department:
King Abdullah University of Science and Technology; Thuwal Kingdom of Saudi Arabia
Citation:
Gonçalves RC, Iskandarani M, Srinivasan A, Thacker WC, Chassignet E, et al. (2016) A framework to quantify uncertainty in simulations of oil transport in the ocean. Journal of Geophysical Research: Oceans 121: 2058–2077. Available: http://dx.doi.org/10.1002/2015JC011311.
Publisher:
Wiley-Blackwell
Journal:
Journal of Geophysical Research: Oceans
Issue Date:
2-Mar-2016
DOI:
10.1002/2015JC011311
Type:
Article
ISSN:
2169-9275
Sponsors:
This research was made possible in part by a grant from BP/The Gulf of Mexico Research Initiative to the Deep-C and CARTHE Consortia, by the Office of Naval Research, award N00014-101-0498, and by the US Department of the Interior, Bureau of Ocean Energy Management under the cooperative agreement MC12AC00019. R. Goncalves acknowledges support by the Brazilian Ministry of Science, Technology and Innovation (CNPq-Council for Scientific and Technological Development) through a PHD scholarship from the Science Without Borders program, grant 202263/2012-6. O. Knio acknowledges partial support from the US Department of Energy, Office of Advanced Scientific Computing Research, under award DE-SC0008789. This research was conducted in collaboration with and using the resources of the University of Miami Center for Computational Science. The outputs of the DeepC Oil Model used here are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC). [Available at https://data.gulfresearchinitiative.org/data/R1.x138.077:0026.]
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Full metadata record

DC FieldValue Language
dc.contributor.authorGonçalves, Rafael C.en
dc.contributor.authorIskandarani, Mohameden
dc.contributor.authorSrinivasan, Ashwanthen
dc.contributor.authorThacker, W. Carlisleen
dc.contributor.authorChassignet, Ericen
dc.contributor.authorKnio, Omaren
dc.date.accessioned2016-11-03T08:27:46Z-
dc.date.available2016-11-03T08:27:46Z-
dc.date.issued2016-03-02en
dc.identifier.citationGonçalves RC, Iskandarani M, Srinivasan A, Thacker WC, Chassignet E, et al. (2016) A framework to quantify uncertainty in simulations of oil transport in the ocean. Journal of Geophysical Research: Oceans 121: 2058–2077. Available: http://dx.doi.org/10.1002/2015JC011311.en
dc.identifier.issn2169-9275en
dc.identifier.doi10.1002/2015JC011311en
dc.identifier.urihttp://hdl.handle.net/10754/621372-
dc.description.abstractAn uncertainty quantification framework is developed for the DeepC Oil Model based on a nonintrusive polynomial chaos method. This allows the model's output to be presented in a probabilistic framework so that the model's predictions reflect the uncertainty in the model's input data. The new capability is illustrated by simulating the far-field dispersal of oil in a Deepwater Horizon blowout scenario. The uncertain input consisted of ocean current and oil droplet size data and the main model output analyzed is the ensuing oil concentration in the Gulf of Mexico. A 1331 member ensemble was used to construct a surrogate for the model which was then mined for statistical information. The mean and standard deviations in the oil concentration were calculated for up to 30 days, and the total contribution of each input parameter to the model's uncertainty was quantified at different depths. Also, probability density functions of oil concentration were constructed by sampling the surrogate and used to elaborate probabilistic hazard maps of oil impact. The performance of the surrogate was constantly monitored in order to demarcate the space-time zones where its estimates are reliable. © 2016. American Geophysical Union.en
dc.description.sponsorshipThis research was made possible in part by a grant from BP/The Gulf of Mexico Research Initiative to the Deep-C and CARTHE Consortia, by the Office of Naval Research, award N00014-101-0498, and by the US Department of the Interior, Bureau of Ocean Energy Management under the cooperative agreement MC12AC00019. R. Goncalves acknowledges support by the Brazilian Ministry of Science, Technology and Innovation (CNPq-Council for Scientific and Technological Development) through a PHD scholarship from the Science Without Borders program, grant 202263/2012-6. O. Knio acknowledges partial support from the US Department of Energy, Office of Advanced Scientific Computing Research, under award DE-SC0008789. This research was conducted in collaboration with and using the resources of the University of Miami Center for Computational Science. The outputs of the DeepC Oil Model used here are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC). [Available at https://data.gulfresearchinitiative.org/data/R1.x138.077:0026.]en
dc.publisherWiley-Blackwellen
dc.subjectDeep water blowouten
dc.subjectDeepwater horizonen
dc.subjectFar fielden
dc.subjectOil transporten
dc.subjectPolynomial chaosen
dc.subjectUncertainty quantificationen
dc.titleA framework to quantify uncertainty in simulations of oil transport in the oceanen
dc.typeArticleen
dc.contributor.departmentKing Abdullah University of Science and Technology; Thuwal Kingdom of Saudi Arabiaen
dc.identifier.journalJournal of Geophysical Research: Oceansen
dc.contributor.institutionRosenstiel School of Marine and Atmospheric Science; University of Miami; Miami Florida USAen
dc.contributor.institutionTendral LLC; Miami Florida USAen
dc.contributor.institutionindependent scholaren
dc.contributor.institutionCenter for Ocean-Atmospheric Prediction Studies, Florida State University; Tallahassee Florida USAen
dc.contributor.institutionDepartment of Mechanical Engineering and Materials Science; Duke University; Durham North Carolina USAen
kaust.authorKnio, Omaren
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