I recently returned from the 2015 NOAA Satellite Conference, a widely attended international conference sponsored by NOAA's National Satellite and Information Service (NESDIS). It was exciting to spend a full week interacting with an internationally diverse set of environmental satellite data users, scientists and algorithm/software developers, all interested in current and future NOAA programs and products.
At the conference, I worked with an AER team to present and demonstrate the Algorithm Workbench (AWB), a comprehensive toolkit facilitating the transition of remote sensing algorithms from research to operations (and back again) – also referred to as the R2O and O2R processes. The AER Algorithm Workbench is the outcome of decades of experience at Atmospheric and Environmental Research (AER) transitioning science/scientific software to practical solutions. It evolved from the algorithm development and test framework we developed and employed as part of our work implementing and testing the level 1 and 2 product generation algorithms for GOES-R.
The Algorithm Workbench is designed to support the larger objectives of NOAA, as well as other research/operational institutions, to evolve to a standardized enterprise ground architecture. The science algorithm development/processing framework is a key element of any ground processing architecture. We designed the Algorithm Workbench to fit in this niche. It supports a common set of interfaces across the development, test and production environments along with a standardized algorithm template. The Algorithm Workbench provides multi-language support including C++, FORTRAN and Python.
At the conference, we presented some recent results evaluating a multi-cloud-algorithm precedence network (producing a cloud mask, cloud phase and cloud top properties) on data from Japan's recently launched Himawari satellite. The Himawari imager <<link>> has the same basic design as the GOES-R imager with only minor channel differences and so is an excellent basis for testing the GOES-R algorithms. With only minor tuning, the out of the box products look excellent. Although this is only the first step in a rigorous validation process, these initial result indicate both the exciting capabilities that will be available in the US with the upcoming GOES-R launch next year.
I am looking forwards to next year's NSC, which will be held shortly before the GOES-R satellite launch ushers in a new era for geosynchronous satellite remote sensing.
Here are a few items of interest.
- Summary of the AER Algorithm Workbench
- Technical overview of the Algorithm Workbench is given in this paper titled “Process and Technologies for the Transition of Research Algorithms to Operations for Real-time Satellite Processing”, at from a recent AMS Annual Meeting at ams.confex.com/ams/94Annual/webprogram/Manuscript/Paper241471/AMS-2014-RTO-Werbos-3.4.pdf.
- The Algorithm Workbench is the outcome of decades of experience at AER transitioning science/scientific software to practical solutions. A good overview is provided in the article “A Geoscience and Remote Sensing Research Paradigm in Industry”
If you would like to learn more about the Algorithm Workbench and see how it might support your needs, please contact myself, Scott Zaccheo, or David Hogan.