Construction of synthetic ocean wave series along the Colombian Caribbean Coast: A wave climate analysis

In this paper a methodology is applied to generate synthetic wave series during mean and extreme conditions. An analysis is carried out that describes mean and extreme wave behavior for several climatic conditions along the Colombian Caribbean Coast. During mean conditions, the most energetic ocean...

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Autores:
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad de Medellín
Repositorio:
Repositorio UDEM
Idioma:
eng
OAI Identifier:
oai:repository.udem.edu.co:11407/2303
Acceso en línea:
http://hdl.handle.net/11407/2303
Palabra clave:
Caribbean Sea
Colombia
Hurricane waves
Synthetic series
Waves
Rights
restrictedAccess
License
http://purl.org/coar/access_right/c_16ec
Description
Summary:In this paper a methodology is applied to generate synthetic wave series during mean and extreme conditions. An analysis is carried out that describes mean and extreme wave behavior for several climatic conditions along the Colombian Caribbean Coast. During mean conditions, the most energetic ocean waves are observed during the DJF season for both ENSO phases (El Niño and La Niña) for most of the Caribbean Sea. During the Niño years, there is a reduction in the speed of the north-east trade winds and their associated waves, but only in the DJF and MAM seasons. However, during the JJA season, this situation is reversed with the highest values occurring during El Niño and low values appearing during La Niña. Toward the east around the Guajira region, this general pattern is shown to change significantly. For extreme conditions, the results show a significant influence of extreme events toward the northwest, around La Guajira and the insular zones of San Andres and Providence when compared with other regions along the coast. All of these results (including the synthetic wave series) provide a design and management tool for the successful implementation of any coastal project (scientific or consulting) in Colombia. © 2016 Elsevier Ltd.