Towards Full-scale Reprocessing of GOES-R ABI L1b Products

The Advanced Baseline Imager (ABI) on-board the GOES-R Series spacecraft plays a critical role in near-real-time monitoring of the Earth’s surface & atmosphere. Given this, the calibration and operations teams are focused on providing the best possible products through continual improvements to the instrument calibration, algorithms, semi-static parameters (Look-Up Tables [LUTs]), and data formatting. These updates provide better products going forward, but as a result the long-term data record suffers from calibration discontinuities, artifacts, and other errors. In order to produce a consistent long-term Earth science data record, reprocessing of the historical data record is needed.

To address this, a NOAA/NASA Geostationary Imager Support Team (GIST) was formed to develop and implement a capability to reprocess Level-1b (L1b) radiance products for the ABIs on-board GOES-16 and GOES-17. The team has successfully modified the existing offline L0-L1b capability developed by the GOES-R Program, the GOES-R ABI Trending and Data Analysis Toolkit (GRATDAT), by implementing the latest operational algorithm and LUT updates along with other improvements named rGRATDAT (reprocessing GRATDAT). rGRATDAT has demonstrated the ability to reduce calibration errors in historical data. In this talk we will provide an update on recent efforts to deploy rGRATDAT to the NOAA NESDIS Cloud-sandbox Infrastructure Service (NCIS) environment and establish a large-scale reprocessing pipeline. Reprocessing of the entire 2019 calendar year for both GOES-16 and GOES-17 ABI is currently underway, while plans to reprocess the entire data record are in work. Highlights from data validation studies will be presented.