The validation of estimates of ocean surface current speed and direction from high-frequency (HF) Doppler radars can be obtained through comparisons with measurements from moored near-surface current meters, acoustic Doppler current profilers, or drifters. Expected differences between current meter (CM) and HF radar estimates of ocean surface vector currents depend on numerous sources of errors and differences such as instrument and sensor limitations, sampling characteristics, mooring response, and geophysical variability. We classify these sources of errors and differences as being associated exclusively with the current meter, as being associated exclusively with the HF radar, or as a result of differing methodologies in which current meters and HF radars sample the spatially and temporally varying ocean surface current vector field. In this latter context we consider three geophysical processes, namely, the Stokes drift, Ekman drift, and baroclinicity, which contribute to the differences between surface and near-surface vector current measurements. The performance of the HF radar is evaluated on the basis of these expected differences. Vector currents were collected during the High Resolution Remote Sensing Experiment II off the coast of Cape Hatteras, North Carolina, in June 1993. The results of this analysis suggest that 40%-60% of the observed differences between near-surface CM and HF radar velocity measurements can be explained in terms of contributions from instrument noise, collocation and concurrence differences, and geophysical processes. The rms magnitude difference ranged from 11 to 20 cm s-1 at the four mooring sites. The average angular difference ranged between 15° and 25° of which about 10° is attributed to the directional error of the radar current vector estimates due to the alignment of the radial beams.
ASJC Scopus subject areas
- Geochemistry and Petrology
- Earth and Planetary Sciences (miscellaneous)
- Space and Planetary Science
- Earth and Planetary Sciences(all)
- Environmental Science(all)