Operational marine buoys provide essential in situ wind observations, but platform attitude variations induced by wind–wave forcing can affect wind-speed measurement quality. Existing high-frequency motion-correction methods are difficult to apply to routine buoy archives that contain only averaged outputs. This study analyzed 6964 quality-screened half-hourly observations from an operational 10 m buoy in the Changjiang Estuary (7 July–1 December 2025) and developed a Motion Impact Index (MII)-based quality classification framework for buoy wind-speed measurements under attitude and sea-state variations. The composite tilt angle was right-skewed (mean 10.68°, 95th percentile 23.09°) and significantly correlated with significant wave height (r=0.388, p<0.001). Theoretical cosine-response analysis indicated a geometric projection effect of −1.7% at the mean tilt and about −8% at the 95th percentile, whereas wind-direction dispersion showed no significant attitude dependence under U≥5m/s. The MII was defined as MII=θtilt×(1+k∙HsHref), with k = 1.0 adopted as an engineering default, and four quality classes were established using the 50th, 80th, and 95th percentiles. Time-split testing, parameter-sensitivity analysis, and bootstrap resampling indicated that the thresholds were statistically stable. When stratified by ERA5 wind speed, the buoy–ERA5 bias increased systematically across the four classes, supporting their interpretation as progressively different measurement conditions. The numerical MII thresholds reported here are specific to the platform type and deployment site; when applied to other buoy designs or sea areas, the thresholds should be recalibrated from local data.
Cao et al. (Sat,) studied this question.
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