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Quality Assessment Techniques Applied to Surface Radial Velocity Maps Obtained from High-Frequency Radars

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  • 1 Department of Mechanical Engineering, School of Mechanical and Aerospace Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
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Abstract

This paper presents examples of the data quality assessment of surface radial velocity maps obtained from shore-based single and multiple high-frequency radars (HFRs) using statistical and dynamical approaches in a hindcast mode. Since a single radial velocity map contains partial information regarding a true current field, archived radial velocity data embed geophysical signals, such as tides, wind stress, and near-inertial and low-frequency variance. The spatial consistency of the geophysical signals and their dynamic relationships with driving forces are used to conduct the quality assurance and quality control of radial velocity data. For instance, spatial coherence, tidal amplitudes and phases, and wind-radial transfer functions are used to identify a spurious range and azimuthal bin. The uncertainty and signal-to-noise ratio of radial data are estimated with the standard deviation and cross correlation of paired radials sampled at nearby grid points that belong to two different radars. This review paper can benefit HFR users and operators and those who are interested in analyzing HFR-derived surface radial velocity data.

Corresponding author address: Sung Yong Kim, Department of Mechanical Engineering, School of Mechanical and Aerospace Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea. E-mail: syongkim@kaist.ac.kr

Abstract

This paper presents examples of the data quality assessment of surface radial velocity maps obtained from shore-based single and multiple high-frequency radars (HFRs) using statistical and dynamical approaches in a hindcast mode. Since a single radial velocity map contains partial information regarding a true current field, archived radial velocity data embed geophysical signals, such as tides, wind stress, and near-inertial and low-frequency variance. The spatial consistency of the geophysical signals and their dynamic relationships with driving forces are used to conduct the quality assurance and quality control of radial velocity data. For instance, spatial coherence, tidal amplitudes and phases, and wind-radial transfer functions are used to identify a spurious range and azimuthal bin. The uncertainty and signal-to-noise ratio of radial data are estimated with the standard deviation and cross correlation of paired radials sampled at nearby grid points that belong to two different radars. This review paper can benefit HFR users and operators and those who are interested in analyzing HFR-derived surface radial velocity data.

Corresponding author address: Sung Yong Kim, Department of Mechanical Engineering, School of Mechanical and Aerospace Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea. E-mail: syongkim@kaist.ac.kr
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