@Article{BarretoDTSKIWM:2021:CoCoMo,
author = "Barreto, Fernando T{\'u}lio Camilo and Dammann, Dyre O. and
Tessarolo, Luciana de Freitas and Skancke, Jorgen and Keghouche,
Intissar and Innocentini, Valdir and Winther-Kaland, Nina and
Marton, Lu{\'{\i}}s",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and StormGeo
and {Instituto Nacional de Pesquisas Espaciais (INPE)} and SINTEF
and StormGeo and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and StormGeo and Climatempo",
title = "Comparison of the Coupled Model for Oil spill Prediction (CMOP)
and the Oil Spill Contingency and Response model (OSCAR) during
the DeepSpill field experiment",
journal = "Ocean and Coastal Management",
year = "2021",
volume = "204",
pages = "e105552",
month = "Apr.",
keywords = "Oil spill, Computational modeling, Model comparison, CMOP,
OSCAR.",
abstract = "An oil spill model is an important tool for environmental risk
assessment, strategic planning, and tactical decision making in
the event of an oil spill. However, limited data exist to evaluate
such models and their performance. During the DeepSpill field
campaign, a unique dataset was acquired by monitoring a deliberate
deep-water oil blowout. In this work, we evaluate and compare two
oil spill models the Coupled Model for Oil spill Prediction (CMOP)
and the Oil Spill Contingency and Response model (OSCAR) against
the DeepSpill experiment. We find that the general plume
trajectory is captured well with a default model setup for both
models. However, to accurately model the surface slick
development, it was necessary to alter modeling parameters and
incorporate model changes to increase scenario flexibility.
Through this work, we build further confidence in the two models
and provide suggestions for improvements.",
doi = "10.1016/j.ocecoaman.2021.105552",
url = "http://dx.doi.org/10.1016/j.ocecoaman.2021.105552",
issn = "0964-5691 and 1873-524X",
language = "en",
targetfile = "barreto_comparison.pdf",
urlaccessdate = "20 set. 2024"
}