CSPP Geo AIT Framework for ABI

The AIT Framework was developed by NOAA STAR as an integration point for GOES-R Level 2 product algorithms. Reference implementations of most of GOES-R product algorithms currently run in the framework. It has been used for validation of products from the operational system, and is being used operationally to generate products for the Suomi NPP mission.

Future Releases

The initial release of the CSPP Geo AIT Framework package will process ABI Level 1 data in the mission-standard NetCDF-4 format, as written by the GRB software package. Output will be written to NetCDF-4 files, in the native AIT Framework file format. It will generate a subset of the GOES-R baseline Level 2 products, including imagery and cloud products (see the list below). Note that the while the versions of the product algorithms will be the same as those in the operational ground system, users should not expect an exact match in products because of differences in implementation.

Products planned for the initial release:

  • Aerosol Detection: Smoke and Dust
  • Aerosol Optical Depth
  • Clear Sky Masks
  • Cloud and Moisture Imagery
  • Cloud Optical Depth (day/night)
  • Cloud Particle Size Distribution (day/night)
  • Cloud Top Height
  • Cloud Top Phase
  • Cloud Top Pressure
  • Cloud Top Temperature
  • Land Surface Temperature (skin)

The initial release is planned for Spring of 2017, after ABI data has been added to the GRB stream and the software has been successfully tested on real ABI data. Note that the products generated by the initial release will not have been validated and should be considered preliminary. As updates to the algorithms and look-up tables become available they will be released in future versions of the AIT Framework package.

System Requirements

  • Intel Xeon E5 v2 “Ivy Bridge” or better, 20-core (2 x 10-core), 2.8GHz CPU with 64-bit instruction support,
  • 192 GB RAM
  • CentOS 6 64-bit Linux (or other compatible 64-bit Linux distribution),
  • 14 TB disk space (does not include long-term storage)

Note that the computational cost of routine quicklook image generation is not accounted for in this hardware recommendation.