SWOT

SWOT Data Tutorials

SWOT Background

The Surface Water and Ocean Topography (SWOT) mission aims to provide valuable data and information about the world’s oceans and its terrestrial surface water such as lakes, rivers, and wetlands. SWOT is jointly developed by NASA and Centre National D’Etudes Spatiales (CNES), with contributions from the Canadian Space Agency (CSA) and United Kingdom Space Agency (UKSA). The satellite launched on December 16, 2022. PO.DAAC is the NASA archive for the SWOT mission, and has made data available via the NASA Earthdata Cloud (hosted in AWS) with direct download capabilities available. PO.DAAC hosts a variety of SWOT data products, whose product description documents can be found in the chart listing each dataset. More information can be found on PO.DAAC’s SWOT webpage.

SWOT Data Resources & Tutorials

Search & Download

Via Graphical User Interface:

Programmatically: ie. within Python code workflows

Via Command Line - PO.DAAC subscriber/downloader examples:

Hydrology: These examples will download either the river vector files or the raster files for February 2024:

podaac-data-downloader -c SWOT_L2_HR_RiverSP_2.0 -d ./SWOT_L2_HR_RiverSP_2.0/ --start-date 2024-02-01T00:00:00Z --end-date 2024-02-29T23:59:59Z

This only downloads 1 hours worth of data for the globe:

podaac-data-downloader -c SWOT_L2_HR_Raster_2.0 -d ./SWOT_L2_HR_Raster_2.0/ --start-date 2024-02-01T00:00:00Z --end-date 2024-02-29T00:59:59Z

Oceanography: These examples will download modeled sea surface heights for the whole SSH collection and then the anomalies using the subscriber then downloader:

podaac-data-subscriber -c SWOT_L2_LR_SSH_2.0 -d ./SWOT_L2_LR_SSH_2.0/ --start-date 2023-03-29T00:00:00Z 
podaac-data-subscriber -c SWOT_L2_NALT_OGDR_SSHA_2.0 -d ./data/SWOT_L2_NALT_OGDR_SSHA_2.0 --start-date 2023-08-01T00:00:00Z --end-date 2023-08-02T00:00:00Z
podaac-data-downloader -c SWOT_L2_NALT_OGDR_SSHA_2.0 -d ./data/SWOT_L2_NALT_OGDR_SSHA_2.0 --start-date 2023-06-23T00:00:00Z --end-date 2023-06-23T06:00:00Z

See how to Download/Subscribe for more information on how to use the PO.DAAC subscriber/downloader including with spatial queries.

Search SWOT Passes over Time

CNES developed this dedicated visualization tool for a quick look at where SWOT has been, where it is, and where it will be. Once you have selected the area of interest, click the Search button to search for SWOT passes. The results are displayed in a table and the swaths that intersect the area of interest are displayed on the map. Click on the marker to view the pass number.

To launch the Binder application, click on this link.

To launch jupyterlab in binder, clink on this link.

SWOT Spatial Coverage

To identify spatial coverage/search terms for the science 21-day orbit, PO.DAAC has created a KMZ file that has layers of the SWOT passes and tiles, with corresponding scene numbers identified in the pop-up when a location is selected (see screenshot below). Each layer has direct links to Earthdata Search results (the ‘search’ links) for corresponding files. The passes layer has useful information for all SWOT products, but links to the LR products specifically, the tiles layer is useful for HR products (L1B_HR_SLC, L2_HR_PIXC, and L2_HR_PIXCVec products use tile spatial extents while the L2_HR_Raster product uses scenes. L2_HR_RiverSP and L2_HR_LakeSp use continent-level passes).

To download the KMZ file, for the science 21-day orbit, click here.

For the Beta Pre-validated data KMZ that used the cal/val 1-day orbit, click here.

These files can be opened in the Google Earth desktop application and viewed like the following:

Screenshot of pass and tile layer in spatial coverage KMZ file viewed in the Google Earth Desktop application

The KaRIN HR Masks true/false text pop up for tiles comes from the two different masks used for different parts of the year. The ‘Seasonal’ mask is used from Dec 1st to March 1st and removes part of the Canadian archipelago coverage to collect additional data over sea ice instead, indicated by true/false statements.

Access & Visualization

Access SWOT Hydrology data in the cloud | locally

Access SWOT Oceanography data in the cloud | locally

SWOT Raster Multifile Access & Quality Flag Application in the cloud | locally

Tips for Quality Flags

Quality flags are associated with measurement variables and have different syntax depending on which data product is being used. If a measurement has a quality flag, it can also have a bit flag that provides the detail of why the quality flags are set as they are (see Product Description Documents (PDDs) for specific value meanings). In addition to the ’_qual’ or ’_q’ indications, ’_flag’ or ’_f’ (e.g., ‘ice_flag’) may be used in each data product to raise different flags with unique values and meanings. See specific PDDs for more information.

SWOT Product Quality Flag Identifier Values and Meanings
L2_HR_RiverSP
L2_HR_RiverAvg
Var + ’_q’

Overall Quality Variables:
‘reach_q’ or ‘node_q’

Bitwise:
Var + ’_q_b’
0 = good
1 = suspect - may have large errors
2 = degraded - likely to have large errors
3 = bad - may be nonsensical and should be ignored

For discharge parameters: (e.g., ‘dschg_c_q’)
0 = valid
1 = questionable
2 = invalid
L2_HR_LakeSP
L2_HR_LakeAvg
Overall quality Variable: ‘quality_f’ 0 = good
1 = bad
L2_HR_Raster Var + ’_qual’

Ex: ‘wse_qual’

Bitwise:
Var + ’_qual_bitwise’
0 = good
1 = suspect - may have large errors
2 = degraded - likely to have large errors
3 = bad - may be nonsensical and should be ignored
L2_NALT_GDR
L2_NALT_IGDR
L2_NALT_OGDR
L2_RAD_GDR
L2_RAD_IGDR
L2_RAD_OGDR
L2_FPDEM
Var + ’_qual’
Ex: ‘rad_water_vapor_qual’
0 = good
1 = bad
L2_LR_SSH
L2_HR_PIXC
L1B_HR_SLC
L1B_LR_INTF
Var + ’_qual’ Varies, see PDDs

Data Story

SWOT Hydrology Science Workflow in the Cloud - Retrieving SWOT attributes (WSE, width, slope) and plotting a longitudinal profile along a river or over a basin

GIS workflows

SWOT: Through a GIS Lens StoryMap

Shapefile exploration

Transform SWOT Datetime field for use in GIS Software

Transform

Transform SWOT Hydrology river reach shapefiles into time series

NetCDF to Geotiff Conversion - mac or Linux | Windows

Tools

Hydrocron - an API that repackages the river shapefile dataset (L2_HR_RiverSP) into csv or GeoJSON formats that make time-series analysis easier. SWOT data is archived as individually timestamped shapefiles, which would otherwise require users to perform potentially thousands of file operations per river feature to view the data as a timeseries. Hydrocron makes this possible with a single API call. -in development

SWODLR - a system for generating on demand raster products from SWOT L2 raster data with custom resolutions, projections, and extents. -in development

Additional Resources

Features of KaRIn Data that Users Should be Aware of

Slide Deck Presented at the SWOT Science Team by Curtis Chen

Addresses practical aspects of interpreting SWOT KaRIn data products, answers frequently asked questions, and provides tips to hopefully avoid misinterpretation and confusion of the data.

Latest Release Notes - Version C KaRIn Science Data Products (aka 2.0) - See section 6 for current issues and features of the datasets!

A Priori Databases

SWOT River Database (SWORD) - the database for rivers SWOT products are based upon, great for discovering river reach IDs!

Prior Lake Database (PLD) - Add in the PLD layer into Hydroweb.next to see the lakes SWOT products are based upon, great for discovering lake IDs!

Earthdata Webinar

Accessing Data for the World’s Water with SWOT

Watch the Recording! Learn how to discover, access, and use SWOT mission data and how these data can lead to new, innovative science and applications in the world of water.

2024 SWOT Hydrology Data Access Workshop

https://podaac.github.io/2024-SWOT-Hydro-Workshop/

This workshop focuses on the SWOT Hydrology datasets including river and lake vector data in shapefiles, and raster, pixel cloud, and pixel vector data in netCDF. In this pre-meeting workshop for the AGU Chapman: Remote Sensing of the Water Cycle Conference, participants are introduced to SWOT and the various ways to access and utilize its data products, including via cloud computing, local download, and data transformation tools.

SWOT Community GitHub Repository

https://github.com/SWOT-community

This is a code space for the global SWOT mission community. We share experience, code, research and much more. Our mission is to increase the value of SWOT.

2022 SWOT Ocean Cloud Workshop

https://podaac.github.io/2022-SWOT-Ocean-Cloud-Workshop/

The goal of the workshop was to enable the (oceanography) science team to be ready for processing and handling the large volumes of SWOT SSH data in the cloud. Learning objectives focus on how to access the simulated SWOT L2 SSH data from Earthdata Cloud either by downloading or accessing the data on the cloud.