USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - VIIRS C2 Subset
The VIIRS aerosol daily Level-3 Climate Modeling Grid (CMG) is used in Landsat 8-9 Surface Reflectance algorithm. The VIIRS CMG products are accessed from the Global daily level 3 retrieved from the NASA's Level 1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC). The ozone and water vapor datasets are extracted, and gap filled for LaSRC processing.
Dataset Citation
Please cite this dataset in the following manner:
Earth Resources Observation and Science (EROS) Center. (2023). VIIRS, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9BSEWK7
These data are available for users wanting to generate custom Level-2 products using the Collection 2 surface reflectance and surface temperature algorithms. It is not necessary for users to download the atmospheric auxiliary data for use with Collection 2 Level-2 products.
The VIIRS aerosol daily Level-3 Climate Modeling Grid (CMG) is used in Landsat 8-9 Surface Reflectance algorithm. The VIIRS CMG products are accessed from the Global daily level 3 retrieved from the NASA's Level 1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC). The ozone and water vapor datasets are extracted, and gap filled for LaSRC processing.
Currently, two sources of VIIRS CMG data are public. NOAA-20 (designated as JPSS-1 prior to launch) CMG data (VJ104ANC) is currently the primary source. If NOAA-20 data is unavailable for specific day, Suomi National Polar-orbiting Partnership (Suomi-NPP) data (VNP04ANC) will be used instead. Once the data from recently launched NOAA-21 (designated as JPSS-2 prior to launch) becomes available (currently scheduled for late 2023/early 2024), the NOAA-21 data (VJ204ANC) will be the highest priority. If NOAA-21 data is unavailable for a day, then NOAA-20 and Suomi-NPP will be considered.
The VIIRS CMG ozone and water vapor datasets contain orbital gaps over polar regions and open ocean. The gaps are filled using precalculated full resolution monthly averages of the VIIRS datasets from the previous month, the current month of the previous year, and the next month of the previous year. The weight that each monthly average contributes to the final fill value is dependent on the day of the month, and whether the corresponding pixel in the monthly average files contain fill.
The gap filled ozone and water vapor datasets are compressed and archived in daily HDF5 files. These HDF5 files contain the “Coarse Resolution Ozone” SDS (unsigned 8-bit integers) and the “Coarse Resolution Water Vapor” SDS (unsigned 16-bit integers). The LocalGranuleID (e.g., ‘VJ104ANC.A2018005.002.2022256072652.h5’) and PlatformShortName (e.g., ‘JPSS-1’) are also carried over to the HDF5 file for data provenance.
Additional Information
- Landsat Collection 2 Atmospheric Auxiliary Home Page
- Landsat Atmospheric Auxiliary Data - Data Format Control Book (DFCB)
Access Data
Use EarthExplorer to search and download the VIIRS C2 Subset Product. The data are located under the Landsat category, Atmospheric Auxiliary Data, and listed as VIIRS C2 Subset.
Data Citation History
The preferred citation for this dataset was revised in 2024 to improve accuracy and alignment with USGS Fundamental Science Practices. The dataset digital object identifier (DOI) and version did not change.
Please cite this dataset in the following manner:
Earth Resources Observation and Science (EROS) Center. (2023). VIIRS, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9BSEWK7
The previously used citation shown below is provided here for historical reference only:
U. S. Geological Survey. (2023). USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - VIIRS C2 Subset [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9BSEWK7
USGS EROS Archive - Landsat - Atmospheric Auxiliary Data
USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - TOMS C2
USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - NCEP/NCAR Reanalysis C2
USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - MODIS Fused C2
USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - MERRA-2 C2
USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - GEOS-5 FP-IT C2
USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - ASTER GED C2
EarthExplorer
The VIIRS aerosol daily Level-3 Climate Modeling Grid (CMG) is used in Landsat 8-9 Surface Reflectance algorithm. The VIIRS CMG products are accessed from the Global daily level 3 retrieved from the NASA's Level 1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC). The ozone and water vapor datasets are extracted, and gap filled for LaSRC processing.
Dataset Citation
Please cite this dataset in the following manner:
Earth Resources Observation and Science (EROS) Center. (2023). VIIRS, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9BSEWK7
These data are available for users wanting to generate custom Level-2 products using the Collection 2 surface reflectance and surface temperature algorithms. It is not necessary for users to download the atmospheric auxiliary data for use with Collection 2 Level-2 products.
The VIIRS aerosol daily Level-3 Climate Modeling Grid (CMG) is used in Landsat 8-9 Surface Reflectance algorithm. The VIIRS CMG products are accessed from the Global daily level 3 retrieved from the NASA's Level 1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC). The ozone and water vapor datasets are extracted, and gap filled for LaSRC processing.
Currently, two sources of VIIRS CMG data are public. NOAA-20 (designated as JPSS-1 prior to launch) CMG data (VJ104ANC) is currently the primary source. If NOAA-20 data is unavailable for specific day, Suomi National Polar-orbiting Partnership (Suomi-NPP) data (VNP04ANC) will be used instead. Once the data from recently launched NOAA-21 (designated as JPSS-2 prior to launch) becomes available (currently scheduled for late 2023/early 2024), the NOAA-21 data (VJ204ANC) will be the highest priority. If NOAA-21 data is unavailable for a day, then NOAA-20 and Suomi-NPP will be considered.
The VIIRS CMG ozone and water vapor datasets contain orbital gaps over polar regions and open ocean. The gaps are filled using precalculated full resolution monthly averages of the VIIRS datasets from the previous month, the current month of the previous year, and the next month of the previous year. The weight that each monthly average contributes to the final fill value is dependent on the day of the month, and whether the corresponding pixel in the monthly average files contain fill.
The gap filled ozone and water vapor datasets are compressed and archived in daily HDF5 files. These HDF5 files contain the “Coarse Resolution Ozone” SDS (unsigned 8-bit integers) and the “Coarse Resolution Water Vapor” SDS (unsigned 16-bit integers). The LocalGranuleID (e.g., ‘VJ104ANC.A2018005.002.2022256072652.h5’) and PlatformShortName (e.g., ‘JPSS-1’) are also carried over to the HDF5 file for data provenance.
Additional Information
- Landsat Collection 2 Atmospheric Auxiliary Home Page
- Landsat Atmospheric Auxiliary Data - Data Format Control Book (DFCB)
Access Data
Use EarthExplorer to search and download the VIIRS C2 Subset Product. The data are located under the Landsat category, Atmospheric Auxiliary Data, and listed as VIIRS C2 Subset.
Data Citation History
The preferred citation for this dataset was revised in 2024 to improve accuracy and alignment with USGS Fundamental Science Practices. The dataset digital object identifier (DOI) and version did not change.
Please cite this dataset in the following manner:
Earth Resources Observation and Science (EROS) Center. (2023). VIIRS, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9BSEWK7
The previously used citation shown below is provided here for historical reference only:
U. S. Geological Survey. (2023). USGS EROS Archive - Landsat - Atmospheric Auxiliary Data - VIIRS C2 Subset [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9BSEWK7