SearcharxivSearch

arXiv · 2607.08947

Implications of Doppler shift for High Frequency Ocean Waves Measured Using Drifting Buoys

Abstract

The advent of expendable wave buoys has greatly expanded the data available for evaluating and calibrating wave models. Ideally, the newer buoys now drifting around the world's oceans would be merged with conventional time series measurements from moored buoys to form a consistent dataset of in situ observations. However, a comparison across several buoy types (moored Datawell, moored NDBC, and two types of drifting buoys) suggests large differences in the high frequency portion of the observed wave energy spectra (0.2 to 0.6 Hz). When binned by wind speed, the moored Datawell buoys have higher energy in the high frequency tail vs. drifting buoys, by factor 1.2 to 1.6. The moored Datawell buoys also have far better agreement with high-frequency energy levels predicted by a numerical wave model. The key to the difference appears to be the reference frame of the observations. To test this hypothesis, the spectra are adjusted from the drifting reference frame to the fixed reference frame. The adjustment is a two-step process, in which the buoy-observed frequencies are first shifted to an intrinsic reference frame, providing wavenumber at each frequency, and then the drifter-observed spectrum is Doppler shifted to the fixed reference frame. Two methods for estimation of buoy drift are tested; one is based on wind speed, and one is based on buoy positions. With this adjustment, the observations from the drifting buoys become more consistent with the moored Datawell buoys, though discrepancies still exist with the moored NDBC buoys.

Explore related subjects

Keep this discovery

BibTeXRIS

W. Erick Rogers, Jim Thomson, Clarence O. Collins. 2026-07-09. Implications of Doppler shift for High Frequency Ocean Waves Measured Using Drifting Buoys. https://arxiv.org/abs/2607.08947

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Windowed Envelope Statistics for Time-Domain Significant Wave Height Estimation From HF Radar

Significant wave height (SWH) retrieval from high-frequency (HF) radar typically relies on a weak second-order Doppler continuum that is sensitive to noise, interference, and spectral leakage. This letter presents a Windowed Envelope Statistics Estimator (WESE) that operates directly on beam-formed time-domain voltages. A second-order term obtained from a Neumann expansion of the rough-surface field equation motivates quadratic compensation of localized radar features. WESE extracts the mean, standard deviation, or variance from overlapping windows of the in-phase, quadrature, or envelope-magnitude sequence, followed by quadratic compensation, rank ordering, least-squares regression, and causal smoothing. Evaluation used 335 synchronized hourly observations from a 13.385 MHz, 12-element WERA system at Argentia, Newfoundland and Labrador. The optimal configuration used quadrature variance, a 16-sample window, 896 retained chronological samples, and 30-h smoothing, achieving an RMSE of 0.152 m and a Pearson correlation of 0.978. This represents RMSE reductions of 32.1% and 18.7% relative to previously reported linear and second-order compensated ordered-statistics models, respectively. The results demonstrate robust time-domain SWH estimation without explicit Doppler-spectrum construction.

physics.ao-ph

KiloDA: Reconstructing kilometer-scale near-surface wind states from sparse station observations

Accurate kilometer-scale near-surface winds are important for understanding atmospheric processes over complex terrain, yet remain difficult to reconstruct from sparse and unevenly distributed observations. Here we introduce KiloDA, a diffusion framework for hourly kilometer-scale wind reconstruction from surface stations. KiloDA learns the statistical distribution and spatial structure of wind fields from historical 3-km Weather Research and Forecasting (WRF) model forecasts. At each reconstruction time, no contemporaneous WRF field is used. Instead, station observations provide the only constraints on the current atmospheric state and guide posterior sampling from the learned prior. In idealized WRF experiments, KiloDA recovers localized wind structures when only 0.24% of grid cells are observed and shows an overall advantage over conventional interpolation across terrain conditions and wind speed regimes. This capability largely transfers to real observations. In a fully withheld region, KiloDA reduces the median wind speed root mean square error (RMSE) by 19% relative to ERA5 reanalysis, using only observations outside the region, with the largest improvements over high-elevation and high-relief terrain. A random station holdout further confirms that this advantage extends across different complex-terrain locations and holdout configurations. These results show that historical model archives can provide useful structural knowledge for reconstructing kilometer-scale wind fields from sparse observations without requiring an accurate model estimate of the current atmospheric state.

physics.ao-ph