Assimilating Near-Surface Wind Retrievals from High-Frequency Radars

Abstract

Abstract High-frequency radars (HFR) are traditionally used in coastal environments to observe ocean current and wave characteristics. With an HFR forward model, HFR adjoint model, and the Simulating Waves Nearshore model, HFR Doppler spectra observations were used to estimate near-surface winds in the Southern California Bight in October 2017. The HFR 10-m wind retrievals were assimilated into the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) with the COAMPS four-dimensional variational (4DVar) assimilation system to integrate the HFR wind retrievals into the initial conditions. Impact of the HFR-derived winds on the forecast are evaluated in terms of adjoint-derived forecast sensitivity observation impact (FSOI), and by an observing system experiment that compared forecasts from simulations that assimilated the HFR wind retrievals to a control simulation that excluded HFR winds. The addition of the HFR-estimated wind observations reduced the error in the forecasted dry energy norm in the lowest model level and also contributed to small improvements in the 10-m wind field over a 25-day experiment. The potential benefit of this new method to estimate near-surface ocean winds near the coast for data assimilation and improved numerical weather prediction is an exciting advancement in remote sensing of coastal winds and expands the benefit of existing HFR networks beyond their intended use. More importantly, wind fields retrieved from HFR have the potential to fill an observation gap near the shoreline where ship and buoy observations are sparse and scatterometer observations are unavailable due to land contamination.