Awesome

SWOT-OpenToolkit

⚠️ An open repository of community-contributed codes for processing SWOT data. Official project algorithms are not included.

The current code focuses on dealing with the KaRIn during the fast-repeat phase. The following image is used to quick search the pass numbers that are relavent to regional interests.

Get started

• A Handbook on level-2 SSH products
• How to contribute

Quick Examples

1. Remove cross-swath bias in 2km-resolution ssha_Karin_2. The following is an example output.

   <img src="media/figures/ssha_karin_2_california.png" alt="Alt Text" width="200">

2. Sea ice and iceberg in sig0 at 250m resolution.

   <img src="media/figures/Unsmoothed_sig0_images/SWOT_L2_LR_SSH_Unsmoothed_486_005_20230409T233402_20230410T002508_PIA1_01.png" alt="sig0 over sea ice" width="200"> <img src="media/figures/worldview/snapshot-2023-04-09T00_00_00Z.png" alt="sig0 over sea ice" width="200">

3. Identify the pass number and timing of the science orbit over a region.

   Run the program as follows:

      python find_swot_passes_science.py -sw_corner -130.0 35.0 -ne_corner -125.0 40.0 -output_filename /tmp/test.png
   

   You will get something like the following figure. It contains the pass number, the satellite passing time (UTC) and the associated visualization.

   <img src="media/figures/science_orbit_timing_example_quebec.png" alt="Alt Text" width="200">

4. Plot the unsmoothed SSH (250m posting) near coast

   <img src="media/figures/unsmoothed_SF_coast.png" alt="unsmoothed SSH" width="200">

Additional Resources:

• Consider visiting the NASA PO.DAAC Cookbook: SWOT Chapter for more data resources and tutorials related to both the hydrology and oceanography SWOT communities.
• Product description documents for every SWOT collection in the table here.