Error assessment of HF radar-based ocean current measurements: An error model based on sub-period measurement variance

Abstract

Data from CODAR-type ocean current sensing radar systems are used here to evaluate the performance of an error indicator provided as part of the available radar data. Investigations are based on data from pairs of radar systems with over-water baselines. Approximately year-long time series are used. The radar data are the typical hourly radial measurements provided by CODAR systems. These measurements are actually the median (or mean) of anywhere between 2 and 7 sub-hourly measurements collected by the radar system. The error indicator under examination is based on the standard deviation (std) of the sub-hourly radials, divided by the square root of the number of sub-hourly radials. These values are recorded in the hourly data files produced by recent versions of the CODAR data processing software. Examination of the model demonstrates a positive correlation between the model and the measured baseline difference std for all baseline pairs examined. The predictive capability of the error model is demonstrated by presenting its use as a data discriminator and by examination of time series of sliding boxcar samples of radar data. Baseline difference std for data rejected by a threshold based on the error model is shown to be significantly higher than for the data retained. The results presented here demonstrate potential to improve assessment of the HF radar current measurement uncertainty. Such improvement has potential to benefit all applications of HF radar data, including for example, Lagrangian particle tracking and surface current assimilation into numerical models.