High resolution downscaled ocean waves (DOW) reanalysis in coastal areas

Camus, Paula; Méndez, Fernando J.; Medina, Raúl; Tomás, Antonio; Izaguirre, Cristina

doi:10.1016/j.coastaleng.2012.09.002

Cited by 106 publications

(70 citation statements)

References 17 publications

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“…Os apontamentos estão sendo elencados e sintetizados em tabelas adaptadas do Manual de Oliveira, 2013;Almeida et al, 2015;Araújo et al, 2015;Ribeiro et al, 2015;Silva et al, 2016 (Camus et al, 2013). O DOW forneceu dados de parâmetros espectrais em termos de sua probabilidade de ocorrência no ponto (IH-CANTABRIA, 2012), a saber: altura signiicativa de onda (Hs), período médio (Tm), período de pico (Tp) e direção média de onda (θm), em termos de regime médio (índice 50 ) e extremo (índice 12 ) das condições de mar.…”

Section: Oicinas Participativasunclassified

Planejamento participativo para a gestão da orla marítima de Galinhos/RN, nordeste brasileiro, com apoio de sensores remotos e modelagem costeira

Marcelino

Pinheiro

Costa

2018

Desenvolv. Meio Ambiente

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Artigo recebido em 1 de setembro de 2017, versão inal aceita em 3 de dezembro de 2017. RESUMO:Este trabalho objetivou trazer à discussão a experiência de planejamento e gestão costeira da orla marítima do município de Galinhos no Litoral Setentrional do Rio Grande do Norte, a partir da aplicação da metodologia proposta para a elaboração do Plano de Gestão Integrada da Orla Marítima (PGI), utilizando-se como ferramentas complementares ao planejamento estratégico e participativo o uso do Sistema de Modelagem Costeira do Brasil (SMC-Brasil), do sensoriamento remoto e do levantamento complementar por Veículo Aéreo Não Tripulado (VANT). Tais ferramentas, aliadas à metodologia de oicinas participativas proposta pelo Projeto Orla, permitiram agregar conhecimento técnico ao tradicional local. Tais metodologias contribuíram para a identiicação das modiicações da linha de costa e a espacialização da expansão do uso do espaço territorial restrito e sujeito aos processos naturais da dinâmica costeira. A modelagem apontou para a intensa energia de ondas sobre a península, luxo médio anual de 366,43 J/m.s, com transporte longitudinal de 185.839 m3/ano de sedimentos da praia, com tendência de abertura de canal isolando o pontal arenoso. O cálculo da planta de equilíbrio das enseadas de Galinhos e Galos indica tendência de avanço da linha de costa em aproximadamente 80 m e 120 m em direção a estes distritos, respectivamente. A revisão do PGI serviu também como registro de informações que serão aportadas como subsídio à elaboração do Plano Diretor Participativo (PDP) do município. Concluiu-se que tais ferramentas e tecnologias são imprescindíveis no processo de planejamento para a gestão integrada da orla marítima. Permitem ampliar a compreensão sobre a dinâmica costeira junto aos moradores das praias, gestores locais e demais atores-chaves para a efetivação do PGI e do PDP, dentre outros instrumentos de gestão territorial e ambiental em áreas próximas à linha de costa.

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Section: Oicinas Participativasunclassified

Planejamento participativo para a gestão da orla marítima de Galinhos/RN, nordeste brasileiro, com apoio de sensores remotos e modelagem costeira

Marcelino

Pinheiro

Costa

2018

Desenvolv. Meio Ambiente

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“…Global winds (Reanalysis 1 -NCEP/NCAR), ice (NCEP/ NCAR) and bathymetry (GEBCO) data were used as input for the WW3 model, which resulted in wave parameters for all oceans around the globe (Reguero et al 2012); ii) second, focusing on the generation of regional data with higher resolution, a downscaling was conducted by propagating GOW parameters to shallow waters in 17 grids along the Brazilian coast using coastal bathymetry and winds (Reanalysis 1 -NCEP/NCAR) on SWAN model (Camus et al 2013). Details of all steps for GOW and DOW generation can be found in Reguero et al (2012) and Camus et al (2013).…”

Section: Reanalysis Data (Dow -Smc Brazil)mentioning

confidence: 99%

“…The most relevant and widely used of those models are WAM (Hasselman et al 1988) and WAVEWATCHIII -WW3 (Tolman 1991) for oceanic modeling, and SWAN (Booij et al 1999) on coastal modeling (Heras et al 1995, Brown 2010, Mostafa Siadatmousavi et al 2011, Reguero et al 2012, Arinaga and Cheung 2012, Camus et al 2013, Chawla et al 2013, Rascle 2013. In recent decades, many studies have been carried out in order to generate wave data from atmospheric reanalysis and validate this time series.…”

Section: Introductionmentioning

confidence: 99%

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Performance assessment of the database downscaled ocean waves (DOW) on Santa Catarina coast, South Brazil

Silva

Klein

González

et al. 2015

An. Acad. Bras. Ciênc.

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This work presents a validation of wave parameters from the new sixty years Downscaled Ocean Waves (DOW) reanalysis database. This study compares quantiles of the Gumbel distribution of Hs (significant wave height) and Tp (peak period) from simulated data with an 11 months' time series obtained from a buoy moored seaward on the Santa Catarina coast. Analysis by means of Gumbel distribution quantiles allows more weight to be given to the highest values of the time series, which are especially important in design projects. The statistical parameters used to verify the fit between the measured and the modeled data included: RMSE, BIAS, Scatter Index and Pearson Correlation Coefficient. Mean direction (θm) validation was conducted qualitatively. The database showed good fit of the mean conditions, especially Hs which was well reproduced by the wave model. Underestimation of Tp, related mainly to the low spatial and temporal resolution of wind data used to generate waves, highlights this general modeling problem. Based on calculated statistical parameters, DOW data were considered comparable to the values obtained by measurements; however, such data must be cautiously used for extreme events analysis and in areas of bimodal sea conditions, where major deficiencies in the database were observed.

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“…In recent years, in fact, wave reanalyses have become popular as a powerful source of information for wave climate research and engineering applications. These wave reanalyses provide continuous time series of offshore wave parameters; nevertheless, in coastal areas or shallow water, waves are poorly described because spatial resolution is not detailed (Camus et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

On the feasibility of the use of wind SAR to downscale waves on shallow water

et al. 2016

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Abstract. In recent years, wave reanalyses have become popular as a powerful source of information for wave climate research and engineering applications. These wave reanalyses provide continuous time series of offshore wave parameters; nevertheless, in coastal areas or shallow water, waves are poorly described because spatial resolution is not detailed. By means of wave downscaling, it is possible to increase spatial resolution in high temporal coverage simulations, using forcing from wind and offshore wave databases. Meanwhile, the reanalysis wave databases are enough to describe the wave climate at the limit of simulations; wind reanalyses at an adequate spatial resolution to describe the wind structure near the coast are not frequently available. Remote sensing synthetic aperture radar (SAR) has the ability to detect sea surface signatures and estimate wind fields at high resolution (up to 300 m) and high frequency.In this work a wave downscaling is done on the northern Adriatic Sea, using a hybrid methodology and global wave and wind reanalysis as forcing. The wave fields produced were compared to wave fields produced with SAR winds that represent the two dominant wind regimes in the area: the bora (ENE direction) and sirocco (SE direction). Results show a good correlation between the waves forced with reanalysis wind and SAR wind. In addition, a validation of reanalysis is shown. This research demonstrates how Earth observation products, such as SAR wind fields, can be successfully uptaken into oceanographic modeling, producing similar downscaled wave fields when compared to waves forced with reanalysis wind.

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High resolution downscaled ocean waves (DOW) reanalysis in coastal areas

Cited by 106 publications

References 17 publications

Planejamento participativo para a gestão da orla marítima de Galinhos/RN, nordeste brasileiro, com apoio de sensores remotos e modelagem costeira

Planejamento participativo para a gestão da orla marítima de Galinhos/RN, nordeste brasileiro, com apoio de sensores remotos e modelagem costeira

Performance assessment of the database downscaled ocean waves (DOW) on Santa Catarina coast, South Brazil

On the feasibility of the use of wind SAR to downscale waves on shallow water

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