VIIRS/NPP+JPSS Combined Vegetation Index and Snow Products from MAIAC Daily L3 Global at 0.05Deg CMG V002

The VCD19A3CMG Version 2 data product is a combined NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Vegetation Index and Snow Products Level 3 product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG). The VCD9A3CMG product is corrected for atmospheric gases and aerosols using a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm that is based on a time series analysis and a combination of pixel- and image-based processing.

The VCD19A3CMG Vegetation Index and Snow product contains variables for NDVI (Normalized Difference Vegetation Index), NDVI normalized to a fixed geometry, gap_filled daily NDVI for forward and backward scattering, daily Enhanced Vegetation Index (EVI) normalized to a fixed geometry, snow fraction, and snow grain size.

Known Issues

• MAIAC Lookup Tables (LUTs) are built assuming pseudo-spherical correction in single scattering which has a reduced accuracy for high sun/view zenith angles. A reduced MAIAC performance is expected at solar zenith angles > 78°.
• MAIAC may be missing bright salt pans in several world deserts. In such cases, it may generate a persistent high Aerosol Optical Depth (AOD) resulting in missing surface retrievals.
• Because of inherent uncertainties of gridding on the coastline, the area of 1-3 pixels from the coastline may contain frequent artifacts in cloud mask (usually over-detection), AOD (higher values) and surface BRF. Users should exercise caution near the coastline as represented by the AOD QA bit 1010 (See Table 5.4 of the User Guide bits 8-11, 1010 -- AOD within +-2 km from the coastline is replaced by nearby AOD).
• Atmospheric Correction (AC) over detected snow: as MAIAC does not retrieve AOD over snow, it assumes a low climatology AOD=0.05 globally and 0.02 at high elevations (H>4.2 km). Over north-central China, which is often heavily polluted and low AOD assumption can lead to a significant bias, we use AOD averaged over mesoscale area of 150 km using reliable AOD retrievals over snow-free pixels. Such approach does improve quality of AC as compared to low-AOD assumption as judged by the reduced boundaries and color artifacts, but it does not account for the aerosol variability inside 150 km area.
• Ice mask is currently unreliable