Skip to content
DraconiticResearch
Search Sources API
203,203 studies31 sourcesUpdated 13 min ago
PreprintarXiv licencearXiv

Surface Stokes drift from compact drifting wave buoys

Abstract

Surface Stokes drift depends strongly on the energy and directions of short waves, which are incompletely resolved by routine wave observations. We derive surface Stokes drift vectors from wave measurements collected by compact drifting buoys during three deployments in the North-East Atlantic and the Alboran Sea. The calculation uses vertical-acceleration spectra and first directional Fourier moments, which describe the mean wave direction and directional concentration at each frequency; it accounts for the Doppler shift caused by buoy motion relative to the water and adds a calibrated high-frequency tail above an intrinsic frequency of 0.7 Hz. Across 13,139 records, the median estimated speed is 0.081 m/s at a median wind speed of 6.8 m/s. Over the measured band of 0.04-1 Hz, accounting for wave directions reduces the magnitude by a median 39% relative to the unidirectional assumption. The median ratio of the parameterised tail magnitude above 0.7 Hz to the total estimated magnitude is 0.37. Comparisons with WAVEWATCH III and Copernicus Marine MFWAM show strong covariation and similar wind-dependent differences from the buoy-derived estimates. On the station-matched sample from the two Atlantic deployments, WAVEWATCH III directional spectra indicate that these differences within the compared band arise mainly from spectral levels rather than from net directional reduction. The observations provide constraints for model evaluation; the contribution of the unresolved short waves remains sensitive to the assumed spectral tail and its directional spreading.

Versions

Related

  1. Fusing SAR and SWIM observations to improve the global stokes drift estimates
    Shihao Zou, Danièle Hauser, Charles Peureux +1
    Remote Sensing of EnvironmentPeer-reviewedCC BY 4.0Full textEnvironmental science & pollutionOceanography & cryosphereHAL
  2. Parametric wave spectrum models for prediction of Stokes drift profiles
    W. Erick Rogers, Yalin Fan, Luis Zamudio +1
    arXivPreprintCC BY-SA 4.0Full textAtmospheric science & meteorologyarXiv
  3. A windy sea surface with Stokes waves
    Nikhil Yewale, Anil Kumar, Vinod Kumar Kadari +1
    arXivPreprintCC BY 4.0Full textAtmospheric science & meteorologyFluid dynamicsarXiv
  4. Applications of a moving surface drag model: From Stokes waves to offshore wind farms
    Manuel Ayala, Zein Sadek, Raul. B Cal +2
    arXivPreprintCC BY 4.0Full textAtmospheric science & meteorologyFluid dynamicsarXiv
  5. A drifting GPS buoy for retrieving effective riverbed bathymetry
    Renaud Hostache, P. Matgen, L. Giustarini +4
    Journal of HydrologyPeer-reviewedLicence not statedFull text30 citedEnvironmental science & pollutionHAL
BibTeX
@misc{mironov2026surface,
  title = {{Surface Stokes drift from compact drifting wave buoys}},
  author = {Alexey S. Mironov and Fabrice Collard and Gwenaele Jan and Bertrand Chapron},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.21592},
  eprint = {2609.21592},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.21592},
}
RIS
TY  - UNPB
TI  - Surface Stokes drift from compact drifting wave buoys
AU  - Alexey S. Mironov
AU  - Fabrice Collard
AU  - Gwenaele Jan
AU  - Bertrand Chapron
PY  - 2026
DA  - 2026/09/18
PB  - arXiv
DO  - 10.48550/arxiv.2609.21592
UR  - https://arxiv.org/abs/2609.21592
AB  - Surface Stokes drift depends strongly on the energy and directions of short waves, which are incompletely resolved by routine wave observations. We derive surface Stokes drift vectors from wave measurements collected by compact drifting buoys during three deployments in the North-East Atlantic and the Alboran Sea. The calculation uses vertical-acceleration spectra and first directional Fourier moments, which describe the mean wave direction and directional concentration at each frequency; it accounts for the Doppler shift caused by buoy motion relative to the water and adds a calibrated high-frequency tail above an intrinsic frequency of 0.7 Hz. Across 13,139 records, the median estimated speed is 0.081 m/s at a median wind speed of 6.8 m/s. Over the measured band of 0.04-1 Hz, accounting for wave directions reduces the magnitude by a median 39% relative to the unidirectional assumption. The median ratio of the parameterised tail magnitude above 0.7 Hz to the total estimated magnitude is 0.37. Comparisons with WAVEWATCH III and Copernicus Marine MFWAM show strong covariation and similar wind-dependent differences from the buoy-derived estimates. On the station-matched sample from the two Atlantic deployments, WAVEWATCH III directional spectra indicate that these differences within the compared band arise mainly from spectral levels rather than from net directional reduction. The observations provide constraints for model evaluation; the contribution of the unresolved short waves remains sensitive to the assumed spectral tail and its directional spreading.
ER  -