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SWOT Level-3 LR SSH v1.0 on AVISO

The v1.0 of the SWOT Level-3 (L3_LR_SSH) product is now online on AVISO. Compared to the beta release (a.k.a L3 v0.3), the main differences are:

  • This release covers one full year from April 2023 to April 2024(1) and both phases/orbits of the mission.
  • Significant upgrade of various Level-3 algorithms layers for performance or robustness(2).
  • This release is now derived from the Level-2 version C, with additional enhancements and bug fixes from the NASA/CNES project.
  • This release combines the reprocessed data and the short latency L2 products, i.e. PGC and PIC in SWOT Project nomenclature(1).

Note also that the main L3 assets are still relevant(3). This release should have fewer artifacts, better coverage, and provide more flexibility on how to mix and match L2 and L3 algorithms, or to mix SWOT with other satellites.
Now that the v1.0 is available online, a draft data paper will be submitted for peer-review soon.

The SWOT L3_LR_SSH product page is available here, the user manual is here, and the data is available at your usual AVISO access point(4). Everything else related to SWOT can be found on AVISO’s one-stop page here. The L3 product is also available on the CNES Cloud (see this link for the free hosting offer). If you need any help getting started, please feel free to contact the AVISO's dedicated SWOT helpdesk  (

As usual, this SWOT product is made by and for the SWOT Science Team and other research groups(5)

[1] The schematic below gives an overview of the input Level-2 (blue) and output Level-3 (red) of the beta release (from L2 version B to L3 v0.3) and current release (from L2 version C to L3 v1.0). Note the mix between reprocessed and forward/nrt products (i.e. PIC & PGC) in the L3 v1.0.

[2] Some notable changes from v0.3 to v1.0:

  • Improved editing layers, addition of finer outlier detections, and addition of granularity and flexibility to the editing flags (e.g. coastal regions, major versus minor flags…). So if you want more control over a comprehensive L3 editing process, you can have it (otherwise, the ‘basic L3’ is still a good default starting point).
  • Enhancement of the so-called ‘phase screen’ correction to better mitigate small-scale semi-static calibration residuals o(mm). This should be transparent to most oceanographers and hopefully a good addition for geodesists and all applications where mm-scale biases are relevant.
  • Improvement of the L3 calibration mechanism to reconcile the L2 and L3 calibrations : a bias from KaRIn to the SWOT Nadir altimeter, and a bias from SWOT to the rest of the nadir constellation and Sentinel-6. 
  • Addition of a quality flag for the L3 calibration to isolate outliers and suspicious segments.
  • Revision of the Deep Learning (CNN) based noise reduction algorithm for better and more stable performances (re-training, new ocean models, style transfer for measurement errors). 
  • Refine the L3 format to make it more compatible with various standards and generic libraries and tools.

[3] Among other things:

  • L3_LR_SSH still provides better ocean calibration and consistency with the Nadir altimeter constellation
  • L3_LR_SSH continues to blend KaRIn and the SWOT Nadir altimeter into a single consistent product
  • L3_LR_SSH continues to provide updated geophysical corrections and references (e.g. MSS)
  • L3_LR_SSH still provides other convenience layers (noise reduction, SSH derivatives…)
  • All the L3 layers are optional (use the ‘expert L3’, take what you want, ignore the rest)
  • The L3 is compatible with the L2 products (you can mix and match what you want from either source)

[4] If you already have an AVISO account, you should see the data in your repository (ftp/sftp, opendap, thredds…).

v1.0 product:

v0.3 product:

[5] The Level-3 was produced as part of our SWOT ST project (DESMOS) and with support from the NASA/CNES Project and the AVISO team. Note that some parameters and algorithms of the L3_LR_SSH product were provided by other members and projects of the SWOT Science Team and OSTST (e.g. research-grade algorithms and corrections).

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