|Paper title||Exploring SWIM and Sentinel-1 wave spectra measurements complementarities|
|Form of presentation||Poster|
The wave spectrum is a representation of the state of the ocean surface from which many parameters can be deduced: significant wave height, peak parameters of dominant waves, directional parameters, etc... For more than 30 years, Synthetic Aperture Radars allow their routine montoring far from the coast in all surface conditions (through clouds and despite night), where buoys cannot be deployed. These measurements benefit from scientific efforts that now make it a reliable measurement technique. Sentinel-1 constellation is one of them and operates since 2016. However known limitations, including wave blurring caused by the azimuth cut-off, limit the performance of wave spectra measurement to long swells.
SWIM is a new rotating Radar onboard the Chinese-French CFOSAT satellite dedicated to directional wave spectra measurement. Not suffering from the cut-off limitations, new horizons and perspectives for synergies are opened in terms of spectral limit and directionality.
Sentinel-1 wave spectra measurements are limited to Wave Mode acquisitions, only available over deep ocean basins and away from the North-East Atlantic Oean. SWIM measurements offer hundreds of co-located measurements over these regions, but also extends the coverage to closed seas worldwide and European waters. Other complementarities exist in wave measured wavelengths : Sentinel-1 extends to long swell (up to 800 m wavelength) while SWIM shows greater ability to measure wind sea components (close or below 50 m).
Those complementarities are assessed at different levels and with different comparisons methodologies. First, partition integral parameters are compared between SWIM Level-2P products or S1 Level-2 products and numerical wave model outputs alone. Second, dynamical co-locations are performed between S1 and SWIM, using cross-overs given by Level-3 spectral produtcs. These measurements, also referred to as Fireworks, allow to dramatically increase the number of co-located points and better inter-compare.
These new performances have applications in data assimilation and prospects for new products such as Stokes drift, a first-estimated spaceborne measurement.