372 Rapid Algorithm Integration in the JPSS CGS

Monday, 11 January 2016
Kerry Grant, Raytheon Intelligence, Information and Services, Aurora, CO; and M. Jamilkowski and S. W. Miller

1. INTRODUCTION

The National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation civilian weather and environmental satellite system: the Joint Polar Satellite System (JPSS). The Joint Polar Satellite System will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental Satellites (POES) managed by the National Oceanic and Atmospheric Administration. The Joint Polar Satellite System satellites will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground processing system for the Joint Polar Satellite System is known as the Common Ground System (JPSS CGS), and provides command, control, and communications (C3) and data processing and product delivery. As a multi-mission system, CGS provides combinations of C3, data processing, and product delivery for numerous NASA, NOAA, Department of Defense (DoD), and international missions, such as NASA's Earth Observation System (EOS), NOAA's current POES, the Japan Aerospace Exploration Agency's (JAXA) Global Change Observation Mission Water (GCOM-W1), and DoD's Defense Meteorological Satellite Program (DMSP).

2. ALGORITHM INTEGRATION CGS's data processing capability processes the satellite data from the Joint Polar Satellite System satellites to provide environmental data products (including Sensor Data Records (SDRs) and Environmental Data Records (EDRs)) to the National Oceanic and Atmospheric Administration and Department of Defense processing centers operated by the United States government. The first satellite in the JPSS constellation, known as the Suomi National Polar-orbiting Partnership (S-NPP) satellite, was launched on 28 October 2011. CGS is currently processing and delivering SDRs and EDRs for S-NPP and will continue through the lifetime of the Joint Polar Satellite System programs. As the science behind the environmental products evolves through new techniques that improve, supplement, or replace existing products, these changes will require implementation into the operational system. In the past, operationalizing science algorithms and integrating them into active systems often required months of work. In order to significantly shorten the time and effort required for this activity, Raytheon has developed tools, processes, and techniques to enable rapid algorithm integration into the CGS. These include the Algorithm Development Library (ADL), the Algorithm Integration Framework (AIF) and the Accelerated Release Cycle (ARC). The ADL enables scientist and researchers to develop algorithms on their own platforms, and provide these to Raytheon in a form that can be rapidly integrated directly into the operational baseline. Over the course of the Suomi NPP Calibration/Validation campaign, numerous participating scientists have adopted the ADL to ensure rapid transition of their updates into the operational system. Their feedback has been the driver to numerous improvements in the tool, many of which are seen in the latest release. As the JPSS CGS is a multi-mission ground system, algorithms are not restricted to Suomi NPP or JPSS missions. The ADL provides a development environment that any environmental remote sensing mission scientist can use to create algorithms that will plug into a JPSS CGS instantiation. Supplementing ADL is the AIF. AIF allows Raytheon to integrate binary algorithms directly into the operational system, without modification of the original source code. This technique is used primarily with legacy algorithms with a history of successful operations on other systems. Finally, the Accelerated Release Cycle provides a stable, rapid release cycle into the operational system providing for shorter cycle times between science updates and operations. This paper describes the tools and processes CGS has implemented to speed the science to operations implementation process.

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