Surface ocean wind datasets are required to be of high spatial and temporal resolution and high precision to accurately force or be assimilated into coupled atmosphere–ocean numerical models and to understand ocean–atmospheric processes. In situ observed sea surface winds from the Southern Ocean are scarce and, consequently, the validity of simulation models is often questionable. Multiple wind data products were compared to the first known high-resolution in situ measurements of wind speed from Wave Glider (WG) deployments in the Southern Ocean with the intent to determine which blended satellite or reanalysis product best represents the magnitude and variability of the observed wind field. Results show that the ECMWF reanalysis product is the most accurate in representing the temporal variability of winds, exhibiting consistently higher correlation coefficients with in situ data across all wind speed categories. However, the NCEP–DOE AMIP-II Reanalysis product matches in situ trends of deviation from the mean and performs best in depicting the mean wind state, especially during high wind states. The ECMWF product also leads to smaller differences in wind speeds from the in situ data, while CFSv2 showed slightly higher biases and a greater RMSE. The SeaWinds (SW) product consistently performed poorly at representing the mean or wind stress variability compared to those observed by the WG. Overall, the study shows autonomous surface vehicles provide valuable observations by which to validate, understand, and potentially assist in correcting satellite/reanalysis products, particularly in remote regions, where few in situ estimates exist.

Comparison of wind products with in situ (CSIR1 WG) data collected December 2015–February 2016 (austral summer). Wind speed categories are determined using the lower and upper quartiles of the in situ data. Linear fit for each wind speed category is shown.

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