Comparison of Surface Tidal and Mean Currents in the Gulf of the Farallones between HF Radar Observations and Operational Model Simulations
Abstract
The Gulf of the Farallones, an ecologically significant region off northern California, is characterized by complex ocean currents influenced by seasonal winds and tidal forces. However, the performance of the operational models in the bay remains unclear. This study compares surface tidal and mean currents derived from high-frequency (HF) radar observations (2012–18) with outputs from three operational ocean models: the Oregon State University (OSU) tidal model, the Copernicus Marine Environment Monitoring Service (CMEMS), and the Hybrid Coordinate Ocean Model (HYCOM). The spatial patterns of tidal currents generally show good overall agreement between the tidal model and the observations, with notable differences near the mouth of San Francisco Bay and over the continental slope. The observations reveal three distinct seasonal flow patterns: strong equatorward currents during upwelling, weak currents during relaxation, and poleward flows during storm periods. The CMEMS agrees well with the observations, particularly over the shelf regions during upwelling and relaxation periods, while HYCOM tends to overestimate flow velocities with larger misfits. These findings highlight the potential of integrating radar data and operational ocean models to enhance our understanding of coastal oceanography.
Significance Statement
This study presents a comprehensive comparison between surface tidal and mean currents observed through high-frequency (HF) radar and operational model simulations in the Gulf of the Farallones. The findings reveal the agreements and discrepancies between observed and simulated currents. This research not only enhances our understanding of coastal circulation patterns but also offers valuable insights into the potential improvements needed for operational models, ultimately contributing to more accurate predictions of oceanographic conditions essential for navigation, environmental monitoring, and resource management.
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