Wave Anomaly Detection in Wave Measurements

Joey J. Voermans Department of Infrastructure Engineering, University of Melbourne, Melbourne, Victoria, Australia

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Alexander V. Babanin Department of Infrastructure Engineering, University of Melbourne, Melbourne, Victoria, Australia
Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Cagil Kirezci Department of Infrastructure Engineering, University of Melbourne, Melbourne, Victoria, Australia

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Jonas T. Carvalho Laboratory of Ocean and Atmosphere Studies, Earth Observation and Geoinformatics Division, National Institute for Space Research (OBT/INPE), São José dos Campos, Brazil

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Marcelo F. Santini Laboratory of Ocean and Atmosphere Studies, Earth Observation and Geoinformatics Division, National Institute for Space Research (OBT/INPE), São José dos Campos, Brazil

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Bruna F. Pavani Institute of Energy and Environment, University of São Paulo, São Paulo, Brazil

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Luciano P. Pezzi Laboratory of Ocean and Atmosphere Studies, Earth Observation and Geoinformatics Division, National Institute for Space Research (OBT/INPE), São José dos Campos, Brazil

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Abstract

Quality control measures for ocean waves observations are necessary to give confidence of their accuracy. It is common practice to detect anomalies or outliers in surface displacement observations by applying a standard deviation threshold. Besides being a purely statistical method, this quality control procedure is likely to flag extreme wave events erroneously, thereby impacting higher-order descriptions of the wave field. In this paper we extend the use of the statistical phase-space threshold, an established outlier detection method in the field of turbulence, to detect anomalies in a wave record. We show that a wave record in phase space (here defined as a diagram of displacement against acceleration) can be enclosed by a predictable ellipse where the major and minor axes are defined by the spectral properties of the wave field. By using the parameterized ellipse in phase space as a threshold to identify wave anomalies, this is a semiphysical filtering method. Wave buoy data obtained from a mooring deployed near King George Island, Antarctica [as part of the Antarctic Modeling Observation System (ATMOS)], and laser altimeter data obtained at the Northwest Shelf of Australia were used to demonstrate the functioning of the filtering methodology in identifying wave anomalies. Synthetic data obtained using a high-order spectral model are used to identify how extreme waves are positioned in phase space.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Joey Voermans, jvoermans@unimelb.edu.au

Abstract

Quality control measures for ocean waves observations are necessary to give confidence of their accuracy. It is common practice to detect anomalies or outliers in surface displacement observations by applying a standard deviation threshold. Besides being a purely statistical method, this quality control procedure is likely to flag extreme wave events erroneously, thereby impacting higher-order descriptions of the wave field. In this paper we extend the use of the statistical phase-space threshold, an established outlier detection method in the field of turbulence, to detect anomalies in a wave record. We show that a wave record in phase space (here defined as a diagram of displacement against acceleration) can be enclosed by a predictable ellipse where the major and minor axes are defined by the spectral properties of the wave field. By using the parameterized ellipse in phase space as a threshold to identify wave anomalies, this is a semiphysical filtering method. Wave buoy data obtained from a mooring deployed near King George Island, Antarctica [as part of the Antarctic Modeling Observation System (ATMOS)], and laser altimeter data obtained at the Northwest Shelf of Australia were used to demonstrate the functioning of the filtering methodology in identifying wave anomalies. Synthetic data obtained using a high-order spectral model are used to identify how extreme waves are positioned in phase space.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Joey Voermans, jvoermans@unimelb.edu.au
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