Fusing SAR and SWIM observations to improve the global stokes drift estimates
Abstract
Stokes drift of ocean surface waves is an important quantity in wave-current coupling theories that affects the dynamics and tracer transport in the upper ocean. However, direct measurement of Stokes drift is elusive. More commonly, it is computed from measured wave spectrum. While in situ measurements of wave spectrum are available from wave buoys, they are mostly limited to coastal regions. Remote sensing of wave spectrum by the Synthetic Aperture Radar (SAR) or the Surface Wave Investigation and Monitoring (SWIM) instrument enables wave spectrum observations globally. Yet both systems present distinct constraints: SAR provides directional information but suffers from velocity bunching effects that restrict measurable wavenumbers and cause spectral distortions, while SWIM offers broader spectral coverage with minimal amplitude underestimation but produces directionally ambiguous spectra. To address these complementary limitations, we propose a novel fusion framework to combine SAR and SWIM using conventional signal processing techniques. We validate the fused Stokes drift against in situ wave buoy measurements at Ocean Station Papa, Southeast Hawaii, and Southern Ocean Flux Station. Compared to the standalone SAR and SWIM results, our fusion approach improves Stokes drift estimates and demonstrates robust performance for the mean Stokes drift vector across various sea states. In addition, we categorize the error sources of the fusion approach into distinct types to guide future improvements. Finally, we apply this fusion approach to the global ocean, which yields seasonal Stokes drift estimates that are more consistent with the established understanding of global wave patterns than estimates based on SWIM alone. These findings show the potential of the fusion approach toward an improved estimate of global Stokes drift.
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BibTeX
@article{zou2026fusing,
title = {{Fusing SAR and SWIM observations to improve the global stokes drift estimates}},
author = {Shihao Zou and Danièle Hauser and Charles Peureux and Qing Li},
journal = {Remote Sensing of Environment},
year = {2026},
month = sep,
doi = {10.1016/j.rse.2026.115687},
url = {https://hal.science/hal-05780898v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Fusing SAR and SWIM observations to improve the global stokes drift estimates
AU - Shihao Zou
AU - Danièle Hauser
AU - Charles Peureux
AU - Qing Li
PY - 2026
DA - 2026/09/23
JO - Remote Sensing of Environment
DO - 10.1016/j.rse.2026.115687
UR - https://hal.science/hal-05780898v1
AB - Stokes drift of ocean surface waves is an important quantity in wave-current coupling theories that affects the dynamics and tracer transport in the upper ocean. However, direct measurement of Stokes drift is elusive. More commonly, it is computed from measured wave spectrum. While in situ measurements of wave spectrum are available from wave buoys, they are mostly limited to coastal regions. Remote sensing of wave spectrum by the Synthetic Aperture Radar (SAR) or the Surface Wave Investigation and Monitoring (SWIM) instrument enables wave spectrum observations globally. Yet both systems present distinct constraints: SAR provides directional information but suffers from velocity bunching effects that restrict measurable wavenumbers and cause spectral distortions, while SWIM offers broader spectral coverage with minimal amplitude underestimation but produces directionally ambiguous spectra. To address these complementary limitations, we propose a novel fusion framework to combine SAR and SWIM using conventional signal processing techniques. We validate the fused Stokes drift against in situ wave buoy measurements at Ocean Station Papa, Southeast Hawaii, and Southern Ocean Flux Station. Compared to the standalone SAR and SWIM results, our fusion approach improves Stokes drift estimates and demonstrates robust performance for the mean Stokes drift vector across various sea states. In addition, we categorize the error sources of the fusion approach into distinct types to guide future improvements. Finally, we apply this fusion approach to the global ocean, which yields seasonal Stokes drift estimates that are more consistent with the established understanding of global wave patterns than estimates based on SWIM alone. These findings show the potential of the fusion approach toward an improved estimate of global Stokes drift.
SN - 0034-4257
SN - 1879-0704
ER -