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”