Lessons Learned From Implementing Operational Algorithms for Product Generation During GOES-R Ground Segment Development

NOAA's Geostationary Operational Environmental Satellite (GOES R-series) Ground Segment Project has implemented several algorithms to process raw data from the Advanced Baseline Imager (ABI) to higher level L1b and Level 2+ products. The operational software was implemented based on L1b algorithms provided by the instrument manufacturer as Ground Processing Algorithm (GPA) documents and to higher level 2+ products using algorithms provided by the Algorithm Working Group in Algorithm Theoretical Basis Documents (ATBD). The operational software developed from these documents is expected to produce meteorological products at low latency reliably to meet functional and performance requirements. Developing operational science software from algorithm documents within cost and schedule constraints was a unique challenge. Some of these challenges include the uniqueness of test data to verify implementation results, differences in approaches for software development among research scientists and computer engineers, metrics to verify and validate science software implementation, differences in hardware and software implementation choices among research and operational systems, and the lack of test data that is a good representation of the operational data flow. This presentation will highlight lessons learned from this project which are applicable to current and future earth science missions for successful development of an operational Product Generation and Distribution system.