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		<doi>10.1016/j.ocecoaman.2021.105552</doi>
		<issn>0964-5691</issn>
		<issn>1873-524X</issn>
		<citationkey>BarretoDTSKIWM:2021:CoCoMo</citationkey>
		<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</title>
		<year>2021</year>
		<month>Apr.</month>
		<typeofwork>journal article</typeofwork>
		<secondarytype>PRE PI</secondarytype>
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		<author>Barreto, Fernando Túlio Camilo,</author>
		<author>Dammann, Dyre O.,</author>
		<author>Tessarolo, Luciana de Freitas,</author>
		<author>Skancke, Jorgen,</author>
		<author>Keghouche, Intissar,</author>
		<author>Innocentini, Valdir,</author>
		<author>Winther-Kaland, Nina,</author>
		<author>Marton, Luís,</author>
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		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>StormGeo</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>SINTEF</affiliation>
		<affiliation>StormGeo</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>StormGeo</affiliation>
		<affiliation>Climatempo</affiliation>
		<electronicmailaddress>fernandotcbarreto@gmail.com</electronicmailaddress>
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		<electronicmailaddress>luciana.tessarolo@inpe.br</electronicmailaddress>
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		<electronicmailaddress>valdir.innocentini@inpe.br</electronicmailaddress>
		<journal>Ocean and Coastal Management</journal>
		<volume>204</volume>
		<pages>e105552</pages>
		<secondarymark>A1_PLANEJAMENTO_URBANO_E_REGIONAL_/_DEMOGRAFIA A1_GEOGRAFIA A1_ENGENHARIAS_I A1_ADMINISTRAÇÃO,_CIÊNCIAS_CONTÁBEIS_E_TURISMO A2_INTERDISCIPLINAR A2_CIÊNCIAS_AMBIENTAIS B1_GEOCIÊNCIAS B1_ENGENHARIAS_IV B1_ENGENHARIAS_III B1_EDUCAÇÃO B1_BIODIVERSIDADE B2_CIÊNCIA_DA_COMPUTAÇÃO B3_CIÊNCIAS_BIOLÓGICAS_I B3_BIOTECNOLOGIA</secondarymark>
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		<contenttype>External Contribution</contenttype>
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		<keywords>Oil spill, Computational modeling, Model comparison, CMOP, OSCAR.</keywords>
		<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.</abstract>
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		<language>en</language>
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