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A 4D-variational ocean data assimilation application for Santos Basin, Brazil.

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Title: A 4D-variational ocean data assimilation application for Santos Basin, Brazil.
Authors: Fragoso, Mauricio1 mauricio@prooceano.com.br, Carvalho, Gabriel1, Soares, Felipe1, Faller, Daiane2, Assad, Luiz3, Toste, Raquel2, Sancho, Lívia2, Passos, Elisa2, Böck, Carina2, Reis, Bruna2, Landau, Luiz2, Arango, Hernan4, Moore, Andrew5
Source: Ocean Dynamics. Mar2016, Vol. 66 Issue 3, p419-434. 16p.
Subjects: Coasts, Mathematical models of oceanography, Weather forecasting, Hydrography, Comparative studies
Geographic Terms: Brazil
Abstract: Aiming to achieve systematic ocean forecasting for the southeastern Brazilian coast, an incremental 4D-Var data assimilation system is applied to a regional ocean model focused mainly in the Santos Basin region. This implementation is performed within the scope of The Santos Basin Ocean Observing System (or Project Azul), a pilot project designed to collect oceanographic data with enough frequency and spatial coverage so to improve regional forecasts through data assimilation. The ocean modeling and data assimilation system of Project Azul is performed with the Regional Ocean Modeling System (ROMS). The observations used in the assimilation cycles include the following: 1-day gridded, 0.1° resolution SST from POES AVHRR; 1-day gridded, 0.3° composite of the MDT SSH from AVISO; and surface and subsurface hydrographic measurements of temperature and salinity collected with gliders and ARGO floats from Project Azul and from UK Met-Office EN3 project dataset. The assimilative model results are compared to forward model results and independent observations, both from remote sensing and in situ sources. The results clearly show that 4D-Var data assimilation leads to an improvement in the skill of ocean hindcast in the studied region. [ABSTRACT FROM AUTHOR]
Copyright of Ocean Dynamics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Aiming to achieve systematic ocean forecasting for the southeastern Brazilian coast, an incremental 4D-Var data assimilation system is applied to a regional ocean model focused mainly in the Santos Basin region. This implementation is performed within the scope of The Santos Basin Ocean Observing System (or Project Azul), a pilot project designed to collect oceanographic data with enough frequency and spatial coverage so to improve regional forecasts through data assimilation. The ocean modeling and data assimilation system of Project Azul is performed with the Regional Ocean Modeling System (ROMS). The observations used in the assimilation cycles include the following: 1-day gridded, 0.1° resolution SST from POES AVHRR; 1-day gridded, 0.3° composite of the MDT SSH from AVISO; and surface and subsurface hydrographic measurements of temperature and salinity collected with gliders and ARGO floats from Project Azul and from UK Met-Office EN3 project dataset. The assimilative model results are compared to forward model results and independent observations, both from remote sensing and in situ sources. The results clearly show that 4D-Var data assimilation leads to an improvement in the skill of ocean hindcast in the studied region. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Ocean Dynamics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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