Raw microwave brightness for wind and water (WindSat)
What it measures. Records how much microwave energy rises off the ocean and atmosphere at several frequencies, the basic signal a satellite uses to figure out ocean surface wind speed and direction. The numbers are 'brightness temperatures' — essentially how warm the surface looks to a microwave sensor.
How it's made. Built from the WindSat radiometer on the U.S. Navy's Coriolis satellite, with the raw readings corrected for instrument quirks and laid onto a fixed map grid.
How & where you'd use it. This is a low-level building-block product: scientists who study ocean winds, weather and the sea surface use it mainly as an input to higher-level wind and water products rather than reading it directly.
What's measured
Coverage & cadence
- Time span2003-02-01 → 2020-10-19
- Measured byCORIOLIS (WINDSAT)
- Processing levelLevel 1C
- 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
The WindSat Polarimetric Radiometer, launched on January 6, 2003 aboard the Department of Defense Coriolis satellite, was designed to measure the ocean surface wind vector from space. It developed by the Naval Research Laboratory (NRL) Remote Sensing Division and the Naval Center for Space Technology for the U.S. Navy and the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Integrated Program Office (IPO). The dataset contains the Level 1C WindSat Top of the Atmosphere (TOA) TB processed by RSS. The WindSat radiances are turned into TOA TB after correction for hot and cold calibration anomalies, receiver non-linearities, sensor pointing errors, antenna cross-polarization contamination, spillover, Faraday rotation and polarization alignment. The data are resampled on a fixed regular 0.125 deg Earth grid using Backus-Gilbert Optimum Interpolation. The sampling is done separately for fore and aft looks. The 10.7, 18.7, 23.8, 37.0 GHz channels are resampled to the 10.7 GHz spatial resolution. The 6.8 GHz channels are given at their native spatial resolution. The 10.7, 18.7, 23.8, 37.0 GHz channels are absolutely calibrated using the GMI sensor as calibration reference. The 6.8 GHz channels are calibrated using the open ocean with the RSS ocean emission model and the Amazon rain forest as calibration targets. The Faraday rotation angle (FRA) and geometric polarization basis rotation angle (PRA) were added in the last run.
Get the data
import earthaccess
earthaccess.login(strategy="netrc") # free Earthdata Login
results = earthaccess.search_data(
short_name="RSS_WindSat_L1C_TB_V08.0",
version="8.0",
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. Official links
- Data Use and Citation Guidelines VIEW RELATED INFORMATION
- Generic Data Readers VIEW RELATED INFORMATION
- T. Meissner and F. Wentz, Intercalibration of AMSR-E and WindSat brightness temperature measurements over land scenes, 2010 IEEE International Geoscience and Remote Sensing Symposium, 2010, pp. 3218-3219, doi: 10.1109/IGARSS.2010.5649513 VIEW RELATED INFORMATION
- P. Gaiser, The WindSat Spaceborne Polarimetric Microwave Radiometer: Sensor Description and Early Orbit Performance,in IEEE Transactions on Geoscience and Remote Sensing, VOL. 42, NO. 11, NOVEMBER 2004, doi: 10.1109/TGRS.2004.836867 VIEW RELATED INFORMATION
- HTTPS endpoint for data browse and download GET DATA
- Browse granule search results in Earthdata Search GET DATA
- User's Guide VIEW RELATED INFORMATION
- T. Meissner and F. Wentz, Polarization rotation and the third Stokes parameter: the effects of spacecraft attitude and Faraday rotation, in IEEE Transactions on Geoscience and Remote Sensing, vol. 44, no. 3, pp. 506-515, March 2006, doi: 10.1109/TGRS.2005.858413 VIEW RELATED INFORMATION