New data product updates: New versions of SMAP Level-1, -2, -3, and -4 data products now available at NSIDC

The SMAP Project performs annual reprocessing of all its science data products based on improvements in the algorithms and supporting information. As part of this routine reprocessing, the SMAP Science Data System (SDS) has now released new versions of Level-1, -2, -3, and -4 data products, accessible through the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC). Several improvements were made to both standard and enhanced SMAP data products, including the following highlights:

  • Level-1 Brightness Temperatures: Applied an enhanced calibration methodology to the brightness temperatures, which improves absolute radiometric calibration and reduces the biases between ascending and descending passes. The impact on soil moisture products is small, but will enhance the use of SMAP Level-1 data for other applications, such as sea surface salinity and winds.
  • Level-2 and -3 Soil Moisture: Improved the soil moisture geophysical retrieval algorithm ancillary data inputs such as a new high-resolution soil database. Also updated the products to use the land surface temperature from the upgraded NASA GMAO model. The Dual Channel Algorithm (DCA) now has comparable performance as the baseline Single Channel Algorithm-Vertical polarization (SCA-V) and additionally provides retrievals of Vegetation Optical Depth (VOD). Added both optional soil moisture algorithms (Single Channel Algorithm-Horizontal polarization and DCA) to the Level-3 daily composite product files.
  • Level-3 Freeze/Thaw: Adjusted the normalized polarization ratio (NPR) and V-polarization threshold parameters per the Level-1 brightness temperature recalibration. Also improved the false-flag mitigation.
  • Level-4 Soil Moisture and Carbon: Updated the algorithms per the Level-1 brightness temperature recalibration and revised underpinning models.

The NSIDC DAAC provides access to these data sets and documentation from

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