Quality Assessment of HF Radar–Derived Surface Currents Using Optimal Interpolation

Abstract

his study investigates the applicability of the optimal interpolation (OI) method proposed by Kim et al. for estimating ocean surface currents from high-frequency radar (HFR) in the northeastern Chukchi Sea, where HFR siting is dictated by power availability rather than optimal locations. Although the OI technique improves data coverage when compared to the conventional unweighted least squares fit (UWLS) method, biased solutions can emerge. The quality of the HFR velocity estimates derived by OI is controlled by three factors: 1) the number of available incorporating radials (AR), 2) the ratio of the incorporating radials from multiple contributing site locations [ratio of overlapping radial velocities (ROR) or radar geometry], and 3) the positive definiteness [condition number (CN)] of the correlation matrix. Operationally, ROR does not require knowledge of the angle covariance matrix used to compute the geometric dilution of precision (GDOP) in the UWLS method and can be computed before site selection to optimize coverage or after data processing to assess data quality when applying the OI method. The Kim et al. method is extended to examine sensitivities to data gaps in the radial distribution and the effects on OI estimates.