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

Carter Ohlmann Institute for Computational Earth System Science, University of California, Santa Barbara, Santa Barbara, California
Scripps Institution of Oceanography, La Jolla, California

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Peter White Institute for Computational Earth System Science, University of California, Santa Barbara, Santa Barbara, California

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Libe Washburn Marine Science Institute, University of California, Santa Barbara, Santa Barbara, California

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Brian Emery Marine Science Institute, University of California, Santa Barbara, Santa Barbara, California

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Eric Terrill Scripps Institution of Oceanography, La Jolla, California

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Mark Otero Scripps Institution of Oceanography, La Jolla, California

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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-km2 (San Diego) or 4-km2 (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 km2) 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−1. 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−1 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−1 within 2 h. The RMS difference and bias (mean absolute difference) for that day exceed 7 and 12 cm s−1, respectively.

Corresponding author address: Dr. Carter Ohlmann, Institute for Computational Earth System Science, University of California, Santa Barbara, Santa Barbara, CA 93106. Email: carter@icess.ucsb.edu

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-km2 (San Diego) or 4-km2 (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 km2) 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−1. 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−1 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−1 within 2 h. The RMS difference and bias (mean absolute difference) for that day exceed 7 and 12 cm s−1, respectively.

Corresponding author address: Dr. Carter Ohlmann, Institute for Computational Earth System Science, University of California, Santa Barbara, Santa Barbara, CA 93106. Email: carter@icess.ucsb.edu

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