Abstract
Many activities require accurate wind and wave forecasts in the coastal ocean. The assimilation of fixed buoy observations into spectral wave models such as SWAN (Simulating Waves Nearshore) can provide improved estimates of wave forecasts fields. High-frequency (HF) radar observations provide a spatially expansive dataset in the coastal ocean for assimilation into wave models. A forward model for the HF Doppler spectrum based on first- and second-order Bragg scattering was developed to assimilate the HF radar wave observations into SWAN. This model uses the spatially varying wave spectra computed using the SWAN model, forecast currents from the Navy Coastal Ocean Model (NCOM), and system parameters from the HF radar sites to predict time-varying range-Doppler maps. Using an adjoint of the HF radar model, the error between these predictions and the corresponding HF Doppler spectrum observations can be translated into effective wave-spectrum errors for assimilation in the SWAN model for use in correcting the wind forcing in SWAN. The initial testing and validation of this system have been conducted using data from ten HF radar sites along the Southern California Bight during the CASPER-West experiment in October 2017. The improved winds compare positively to independent observation data, demonstrating that this algorithm can be utilized to fill an observational gap in the coastal ocean for winds and waves.
Highlights
Regional coastal modeling of the ocean and the atmosphere have come a long way in the last 20 years but most models still suffer from errors due to parameterization or inaccurate model inputs
We examine coastal wind estimation by assimilating observations of Doppler spectra from coastal high-frequency (HF) radar sites into a regional wave model with a variational assimilation approach
The HFR inverse modeling framework developed here was applied for estimation of the 10-m winds in the Southern California Bight during the CASPER-West field experiment in October 2017
Summary
Regional coastal modeling of the ocean and the atmosphere have come a long way in the last 20 years but most models still suffer from errors due to parameterization or inaccurate model inputs (i.e., bathymetry, initial or boundary conditions). These model errors can be addressed with the assimilation of local observations. We examine coastal wind estimation by assimilating observations of Doppler spectra from coastal high-frequency (HF) radar sites into a regional wave model with a variational assimilation approach. The use of HF radar Doppler spectra to correct wave models is less widely used. Siddons et al (2009) [6]
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