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Full catalog/SWOT_L1B_LR_INTF_D
SWOT_L1B_LR_INTF_D·vD·dataset

Raw radar signal used to map water heights (SWOT)

SWOT Level 1B Low-Rate Interferogram Data Product, Version D
land NASA POCLOUD Level 1B netCDF-4
In plain English

What it measures. The raw radar interferogram signals SWOT uses to eventually map water heights, along with the measurement geometry needed to process them further.

How it's made. Formed onboard SWOT from its radar's nine beams, spatially averaged, then corrected on the ground for processing biases; delivered as gridded Level 1B data.

How & where you'd use it. A low-level building-block input; most people use SWOT's finished water-height products rather than these raw interferograms directly.

What's measured

SPECTRAL/ENGINEERING › RADAR › SIGMA NAUGHTSPECTRAL/ENGINEERING › SENSOR CHARACTERISTICS › PHASE AND AMPLITUDESPECTRAL/ENGINEERING › RADAR › RADAR BACKSCATTERSPECTRAL/ENGINEERING › RADAR › RADAR CROSS-SECTION

Coverage & cadence

  • Time span2022-12-16 → ongoing
  • Measured bySWOT (KaRIn, Jason-class Altimeter, AMR, DORIS, GPSP, LRA)
  • Processing levelLevel 1B
  • Spatial extent-180, -90, 180, 90
  • FormatsnetCDF-4
  • StatusACTIVE

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

Interferograms for each of the 9 Doppler beams formed and spatially averaged (low rate) by the On Board Processor, corrected on the ground for phase biases (inherent to the processing applied on board). The geometry of the measurements is also reported for use in subsequent processing. Gridded; full swath for each half orbit. Available in netCDF-4 file format.

Get the data

swot_l1b_lr_intf_d_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="SWOT_L1B_LR_INTF_D",
    version="D",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from POCLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.