VJ143D53: Global Land Surface Albedo Uncertainty at 1km Resolution

NOAA-20 VIIRS satellite data provides daily global maps of uncertainty for land surface albedo and reflectance anisotropy, a critical input for climate models. Each pixel's uncertainty range is derived from 16 days of observations, temporally weighted to the ninth day and gridded at a 30-arc-second (1km) Climate Modeling Grid resolution. The product incorporates improvements in sensor calibration, geolocation, and aerosol flagging from the S-NPP VIIRS V002 algorithm suite.

Use Cases

• Propagating uncertainty in climate model forecasts based on albedo uncertainty ranges.
• Assessing retrieval quality for land surface change studies using the BRDF/Albedo Quality layer.
• Analyzing observation density for surface reflectance studies using the Valid Observations count layer.
• Modeling surface energy balance by incorporating pixel-level albedo uncertainty.

Strengths

• Provides a dedicated, single-layer global uncertainty product for albedo at 1km resolution.
• Incorporates algorithm improvements for calibration and geolocation across the entire NOAA-20 mission.
• Produced daily using a 16-day composite to improve signal-to-noise, with temporal weighting documented in filenames.

Limitations

• Key metadata such as specific column names, row counts, and file sizes are not provided across any platform.
• Relies on an external 'other-license-specified' with no details provided in the available metadata.
• Known issues exist and require consultation of an external website for complete understanding.

Provenance

Source

NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensor.

Collection Method

Processed daily using 16 days of data, temporally weighted to the ninth day, using the VJ143 algorithm.

Time Range

Covers the operational period of the NOAA-20 satellite; specific start date not provided.

Freshness

Last updated metadata date is 2026-04-09, as recorded on nasa_earthdata and datagov.

Geography

Global coverage on a Climate Modeling Grid (CMG).