VNP21 v002

• Improved calibration algorithm and coefficients for entire Suomi NPP mission.
• Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.
• Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo.
• Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data.
• Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.
• Replaced MERRA2 inputs with GEOS5.
• Included inland water body pixels to allow for LST retrieval over these areas.
• Introduced daily, 8-day, and monthly LST CMG products.

More details can be found in this VIIRS Land V2 Changes document.

Validation at stage 1 has been achieved for the VIIRS Land Surface Temperature and Emissivity product suite. Visit VIIRS Land Product Quality Assessment Product Maturity for information on product maturity status.

Ocean-land mask Values

The bit flags for the QC layer are defined in Table 5 of the User Guide.

The quality layer is stored in an efficient bit-encoded manner. The unpack_sds_bits executable from the LDOPE Tools is available to the user community to help parse and interpret the quality layer.

Quality assurance information should be considered when determining the usability of data for a particular science application. The ArcGIS MODIS-VIIRS Python Toolbox contains tools capable of decoding quality data layers while producing thematic quality raster files for each quality attribute.

For additional information on product quality, refer to the VIIRS Land Product Quality website.

Users of VIIRS and MODIS LST products may notice an increase in occurrences of extreme high temperature outliers in the unfiltered VNP21 and MxD21 products compared to the heritage MxD11 LST products. This can occur especially over desert regions like the Sahara where undetected cloud and dust can negatively impact MxD11, MxD21, and VNP21 retrieval algorithms.

In the MxD11 LST products, these contaminated pixels are flagged in the algorithm and set to fill values in the output products based on differences in the band 32 and band 31 radiances used in the generalized split window algorithm. In the VNP21 and MxD21 LST products, values for the contaminated pixels are retained in the output products (and may result in overestimated temperatures), and users need to apply Quality Control (QC) filtering and other error analyses for filtering out bad values. High temperature outlier thresholds are not employed in VNP21 and MxD21 since it would potentially remove naturally occurring hot surface targets such as fires and lava flows.

High atmospheric aerosol optical depth (AOD) caused by vast dust outbreaks in the Sahara and other deserts highlighted in the example documentation are the primary reason for high outlier surface temperature values (and corresponding low emissivity values) in the VNP21 and MxD21 LST products. Future versions of the VNP21 and MxD21 products will include a dust flag from the MODIS aerosol product and/or brightness temperature look up tables to filter out contaminated dust pixels. It should be noted that in the MxD11B day/night algorithm products, more advanced cloud filtering is employed in the multi-day products based on a temporal analysis of historical LST over cloudy areas. This may result in more stringent filtering of dust contaminated pixels in these products.

To mitigate the impact of dust in the VNP21 and MxD21 products, the science team recommends using a combination of the existing QC bits, emissivity values, and estimated product errors, to confidently remove bad pixels from analysis. For more details, refer to this dust and cloud contamination example documentation.

For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.