2025-07-17T11:56 AM
Hi Claude,
I guess the next step would be to check that similar results are obtained when switching to the sla_unfiltered variable, as we used only the ssha_filtered variable so far. It would highlight:
Also please note that I heard about an upcoming new version of SWOT L3 products (at least for products at 2km resolution), so it is important to mention that the plots have been generated using v2_0_1 data. This new version should notably include some corrections/changes related to the geoid and MSS (see https://youtu.be/bsjv4Z2duYk?feature=shared&t=851).
Cheers,
Sylvain
I guess the next step would be to check that similar results are obtained when switching to the sla_unfiltered variable, as we used only the ssha_filtered variable so far. It would highlight:
- potential effects of the experimental algorithm used for filtering data on the structures contour. Note that there is a disclaimer regarding the filter: "Experimental algorithm. This parameter is the noise-mitigated counterpart of the ‘ssha_unfiltered’ variable. The noise was mitigated through a machine-learning algorithm (Treboutte et al., 2024). Caution is advised because the algorithm validation is still ongoing: some of the ocean features less than 50km in wavelength may also be affected by the de-noising algorithm"
- how the filter discards potentially useful data: as the ssha_unfiltered variable is said to be equivalent to the nadir data where you managed to spot the lowering even on areas where SSHA is masked on my plots, I guess the masked areas in pass 541 on 2024-01-02 and 2024-01-23 would be narrower and more measurements of the lowering would be revealed.
Also please note that I heard about an upcoming new version of SWOT L3 products (at least for products at 2km resolution), so it is important to mention that the plots have been generated using v2_0_1 data. This new version should notably include some corrections/changes related to the geoid and MSS (see https://youtu.be/bsjv4Z2duYk?feature=shared&t=851).
Cheers,
Sylvain