Interpretation of Coastal HF Radar–Derived Surface Currents with High-Resolution Drifter Data

Abstract

Dense arrays of surface drifters are used to quantify the flow field on time and space scales over which high-frequency (HF) radar observations are measured. Up to 13 drifters were repetitively deployed off the Santa Barbara and San Diego coasts on 7 days during 18 months. Each day a regularly spaced grid overlaid on a 1-km 2 (San Diego) or 4-km 2 (Santa Barbara) square, located where HF radar radial data are nearly orthogonal, was seeded with drifters. As drifters moved from the square, they were retrieved and replaced to maintain a spatially uniform distribution of observations within the sampling area during the day. This sampling scheme resulted in up to 56 velocity observations distributed over the time (1 h) and space (1 and 4 km 2 ) scales implicit in typical surface current maps from HF radar. Root-mean-square (RMS) differences between HF radar radial velocities obtained using measured antenna patterns, and average drifter velocities, are mostly 3-5 cm s Ϫ1 . Smaller RMS differences compared with past validation studies that employ current meters are due to drifter resolution of subgrid-scale velocity variance included in time and space average HF radar fields. Roughly 5 cm s Ϫ1 can be attributed to sampling on disparate time and space scales. Despite generally good agreement, differences can change dramatically with time. In one instance, the difference increases from near zero to more than 20 cm s Ϫ1 within 2 h. The RMS difference and bias (mean absolute difference) for that day exceed 7 and 12 cm s Ϫ1 , respectively.

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

“…These errors (GDOP and GDOSA) are distributed spatially and can be controlled and estimated in the processing from total to radials Barrick, 2002). Related to the data uncertainties, it is worth mentioning that a number of validation exercises exist, based on comparisons of HFR currents against independent in situ measurements (Kohut and Glenn, 2003;Kaplan et al, 2005;Paduan et al, 2006;Ohlmann et al, 2007;Cosoli et al, 2010;Lorente et al, 2014Lorente et al, , 2015aSolabarrieta et al, 2014;Kalampokis et al, 2016). These validation exercises can be limited by the fact that part of the discrepancies observed through these comparisons are due to the specificities and own inaccuracies of the different measuring systems (Solabarrieta et al, 2014;Kalampokis et al, 2016).…”

“…This can explain the significant scatter found in the literature concerning point to point comparison between HFR and other in situ measurements. When HFR data are compared with surface drifter clusters or ADCPs whose uppermost bins are not deeper than 5 m, RMSDs typical values range between 3 and 12 cm.s −1 (e.g., Ohlmann et al, 2007;Molcard et al, 2009;Liu et al, 2010;Kalampokis et al, 2016). Each row corresponds to one of the ITU frequency bands allocated for oceanographic radar with the lower and upper band limits in frequency.…”

Evaluation of two algorithms for a network of coastal HF radars in the Mid-Atlantic Bight

“…Before any evaluation can be done to assess the quality of HF radar surface current estimates, the expected differences due to environmental variability must be quantified Kohut et al 2006;Ohlmann et al 2007;Paduan et al 2006). The temporal averaging of the drifter and ADCP velocities was consistent with the HF radar processing to remove bias from different temporal sampling and averaging.…”

Brahan Project High Frequency Radar Ocean Measurements: Currents, Winds, Waves and Their Interactions

“…Reports already exist in the literature providing such comparisons for current velocities and wave parameters, see [2][3][4][5][6]. Wind direction mapping is in a preliminary phase and awaits validation with in-situ measurements in the radar coverage area.…”