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dc.contributor.authorDukhovskoy, DS
dc.contributor.authorMorey, SL
dc.contributor.authorChassignet, EP
dc.contributor.authorChen, X
dc.contributor.authorColes, VJ
dc.contributor.authorCui, L
dc.contributor.authorHarris, CK
dc.contributor.authorHetland, R
dc.contributor.authorHsu, T-J
dc.contributor.authorManning, AJ
dc.contributor.authorStukel, M
dc.contributor.authorThyng, K
dc.contributor.authorWang, J
dc.date.accessioned2023-05-05T00:27:09Z
dc.date.available2023-05-05T00:27:09Z
dc.date.issued2021-03-10
dc.identifier.issn2296-7745
dc.identifier.issn2296-7745
dc.identifier.urihttps://pearl.plymouth.ac.uk/handle/10026.1/20811
dc.description.abstract

The fate and dispersal of oil in the ocean is dependent upon ocean dynamics, as well as transformations resulting from the interaction with the microbial community and suspended particles. These interaction processes are parameterized in many models limiting their ability to accurately simulate the fate and dispersal of oil for subsurface oil spill events. This paper presents a coupled ocean-oil-biology-sediment modeling system developed by the Consortium for Simulation of Oil-Microbial Interactions in the Ocean (CSOMIO) project. A key objective of the CSOMIO project was to develop and evaluate a modeling framework for simulating oil in the marine environment, including its interaction with microbial food webs and sediments. The modeling system developed is based on the Coupled Ocean-Atmosphere-Wave-Sediment Transport model (COAWST). Central to CSOMIO’s coupled modeling system is an oil plume model coupled to the hydrodynamic model (Regional Ocean Modeling System, ROMS). The oil plume model is based on a Lagrangian approach that describes the oil plume dynamics including advection and diffusion of individual Lagrangian elements, each representing a cluster of oil droplets. The chemical composition of oil is described in terms of three classes of compounds: saturates, aromatics, and heavy oil (resins and asphaltenes). The oil plume model simulates the rise of oil droplets based on ambient ocean flow and density fields, as well as the density and size of the oil droplets. The oil model also includes surface evaporation and surface wind drift. A novel component of the CSOMIO model is two-way Lagrangian-Eulerian mapping of the oil characteristics. This mapping is necessary for implementing interactions between the ocean-oil module and the Eulerian sediment and biogeochemical modules. The sediment module is a modification of the Community Sediment Transport Modeling System. The module simulates formation of oil-particle aggregates in the water column. The biogeochemical module simulates microbial communities adapted to the local environment and to elevated concentrations of oil components in the water column. The sediment and biogeochemical modules both reduce water column oil components. This paper provides an overview of the CSOMIO coupled modeling system components and demonstrates the capabilities of the modeling system in the test experiments.

dc.format.extent629299-
dc.publisherFrontiers Media SA
dc.subject37 Earth Sciences
dc.subject3708 Oceanography
dc.subject14 Life Below Water
dc.titleDevelopment of the CSOMIO Coupled Ocean-Oil-Sediment- Biology Model
dc.typejournal-article
dc.typeJournal Article
plymouth.volume8
plymouth.publication-statusPublished online
plymouth.journalFrontiers in Marine Science
dc.identifier.doi10.3389/fmars.2021.629299
plymouth.organisational-group|Plymouth
plymouth.organisational-group|Plymouth|Research Groups
plymouth.organisational-group|Plymouth|Faculty of Science and Engineering
plymouth.organisational-group|Plymouth|Faculty of Science and Engineering|School of Biological and Marine Sciences
plymouth.organisational-group|Plymouth|Research Groups|Marine Institute
plymouth.organisational-group|Plymouth|REF 2021 Researchers by UoA
plymouth.organisational-group|Plymouth|Users by role
plymouth.organisational-group|Plymouth|Users by role|Academics
plymouth.organisational-group|Plymouth|REF 2021 Researchers by UoA|UoA07 Earth Systems and Environmental Sciences
dcterms.dateAccepted2021-02-15
dc.date.updated2023-05-05T00:27:09Z
dc.rights.embargodate2023-8-16
dc.identifier.eissn2296-7745
dc.rights.embargoperiodforever
rioxxterms.versionofrecord10.3389/fmars.2021.629299


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