Thursday, 26 January 2012: 11:45 AM
GOES-R Software Implementation Design: Design and Implementation of GOES-R Level 2+ Product Generation Algorithms
Room 356 (New Orleans Convention Center )
The next generation of NOAA's Geostationary Operational Environmental Satellite system, Series R (GOES-R) provides continuity of the GOES mission and improvement of its remotely-sensed environmental data. The GOES-R system consists of the Space and Ground Segments. The Space Segment consists of spacecraft bus, its remote- sensing instruments, and communications payloads; while the Ground Segment consists of all Earth-based functions, provides satellite operations and instrument product generation and distribution. The GOES-R Ground Segment operates from three sites: the NOAA Satellite Operations Facility (NSOF) in Suitland, MD; the Wallops Command and Data Acquisition Station (WCDAS), located in Wallops, VA; and a geographically diverse remote backup facility (RBU) located at Fairmont, WV. The architecture has been developed to allow integrated operation within a geographically distributed information systems framework. GOES-R will provide advanced products, based on government-supplied algorithms, that describe the state of the atmosphere, land, and oceans over the Western Hemisphere as well as products for monitoring the local space environment and the solar state. The Harris GOES-R Core Ground Segment (GS) Team will provide the software and engineering infrastructures to produce and distribute these next-generation data products both directly to users and to the archival systems. Within the Ground Segment, the Product Generation Element (PG) is responsible for the software implementations of scientific algorithms.
In this presentation we provide an overview of how Product Generation software works with the other elements of the Ground Segment to produce Level 2+ end-products. We discuss the specific software structures used to implement Level 2+ algorithms, and how those structures interface with other components in a way that meets the needs of a distributed, high- performance computational environment.