GOES-R Algorithm Working Group’s (AWG) Product Processing System Framework is currently being run both in operations and in near real-time to support algorithm verification and validation over extended seasonal datasets. The algorithms are being tested using a variety of data sets, including: MODIS, SEVIRI, GOES, VIIRS data, and ABI WRF simulated data. The Advanced Himawari Imager(AHI) data will also be used as ABI proxy data to test the GOES-R algorithms in the Framework. AWG Integration Team (AIT) has developed a suite of tools to monitor product quality, product processing, and system performance for the near real-time product generation. These capabilities have allowed the framework to be expanded for use in transitioning algorithms to operations. The GOES-R AWG Derived Atmospheric Motion Vector Winds algorithm has been successfully updated and transitioned to operations running on existing GOES and VIIRS data. Other GOES-R algorithms that are being upgraded for operational use on VIIRS include the Clouds, Aerosols, and Cryosphere products. In addition, legacy operational cloud systems will be integrated into the Framework. The design details of the AWG Framework, near real-time algorithm product generation system, monitoring tools, transitioning of the framework to operations, and future algorithm implementation plans shall be discussed.
The Advanced Baseline Imager (ABI) is the primary instrument onboard GOES-R for imaging Earth’s weather, climate,
and environment and will be used for a wide range of applications related to weather, oceans, land, climate, and hazards
(fires, volcanoes, hurricanes, and storms that spawn tornados). It will provide over 65% of all the mission data products
currently defined. ABI views the Earth with 16 different spectral bands, including two visible channels, four nearinfrared
channels and ten infrared channels at 0.5, 1, and 2 km spatial resolutions respectively. For most of the
operational ABI retrieval algorithms, the collocated/co-registered radiance dataset are at 2 km resolution for all of the
bands required. This requires down-scaling of the radiance data from 0.5 or 1 km to 2 km for ABI visible and near-IR
bands (2 or 1, 3 & 5 respectively), the reference of 2 km is the nominal resolution at the satellite sub-point. In this paper,
the spatial resolution characteristic of the ABI fixed grid level1b radiance data is discussed. An optimum interpolation
algorithm which has been developed for the ABI multiple channel radiance down-scaling processing is present.
NOAA/NESDIS/STAR has designed, developed, and implemented the Geostationary Operational Environmental Satellite – R Series (GOES-R) Algorithm Working Group (AWG) Product Processing System Framework. The
Framework enabled the development and testing of the Level 2 Advance Baseline Imager (ABI) and the GOES-R Lightning Mapper (GLM) products within a single system. Fifty-six GOES-R ABI algorithms and one GLM algorithm have been integrated and run within the framework with product precedence. The Framework has been modified to be a
plug-and-play system with the scientific algorithms. To enable the plug-and-play capabilities, the fifty-seven ABI and
GLM algorithms were adjusted such that any data required by the algorithm is brought into the algorithm through
function calls. These modifications allowed an algorithm to be developed either within the Framework or within the
scientist’s offline research system. This approach provided both the algorithm developers and algorithm integrators the ability to work on the same software since the algorithm may be “dropped” into both systems resulting in simple
algorithm rollbacks. The design features and the current status of the framework will be discussed.