Model type II regression for lagrangian validation of HF radar velocities in the NW Iberian Peninsula

Two designs of lagrangian low-cost drifting buoys have been developed in order to monitor the ocean surface dynamics in the North-west Iberian Peninsula and provide ground-truth observations that can be used to assess the performance of High Frequency (HF) Radars of RAIA observatory from 2020 to 202...

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Detalles Bibliográficos
Autores: Martínez Fernández, Adrián, Redondo Caride, Waldo, Alonso Pérez, Fernando, Piedracoba Varela, Silvia, Lorente, Pablo, Allen-Perkins Cáceres, Silvia, Montero Vilar, Pedro, Ayensa Aguirre, Garbiñe, Torres López, Silvia, Fernández Baladrón, Adrián, Varela Benvenuto, Ramiro Alberto, Velo Lanchas, Antón, Gil Coto, Miguel
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/391982
Acceso en línea:https://hdl.handle.net/2117/391982
Access Level:acceso abierto
Palabra clave:Buoys
Radar
Drifting buoy
HF radar
Observing system
Lagrangian validations
Boies
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Radar
Àrees temàtiques de la UPC::Enginyeria electrònica::Instrumentació i mesura
Descripción
Sumario:Two designs of lagrangian low-cost drifting buoys have been developed in order to monitor the ocean surface dynamics in the North-west Iberian Peninsula and provide ground-truth observations that can be used to assess the performance of High Frequency (HF) Radars of RAIA observatory from 2020 to 2022. Since regression model type I, which is typically used in buoy-HF radar antennas validations, does not consider the presence of errors in the observations from both instruments, regression model type II was proposed to instrument intercomparison. Furthermore, a new metric was developed to better assess both model types regressions in lagrangian validations.