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Proceedings Paper

Simulation for the design of next-generation global Earth observing systems
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Paper Abstract

Under a recently-funded NASA Earth Science Technology Office (ESTO) award we are now designing, and will eventually implement, a sensor web architecture that couples future Earth observing systems with atmospheric, chemical, and oceanographic models and data assimilation systems. The end product will be a "sensor web simulator" (SWS), based upon the proposed architecture, that would objectively quantify the scientific return of a fully functional modeldriven meteorological sensor web. Our proposed work is based upon two previously-funded ESTO studies that have yielded a sensor web-based 2025 weather observing system architecture, and a preliminary SWS software architecture that had been funded by NASA's Revolutionary Aerospace Systems Concept (RASC) and other technology awards. Sensor Web observing systems have the potential to significantly improve our ability to monitor, understand, and predict the evolution of rapidly evolving, transient, or variable meteorological features and events. A revolutionary architectural characteristic that could substantially reduce meteorological forecast uncertainty is the use of targeted observations guided by advanced analytical techniques (e.g., prediction of ensemble variance). Simulation is essential: investing in the design and implementation of such a complex observing system would be very costly and almost certainly involve significant risk. A SWS would provide information systems engineers and Earth scientists with the ability to define and model candidate designs, and to quantitatively measure predictive forecast skill improvements. The SWS will serve as a necessary trade studies tool to: evaluate the impact of selecting different types and quantities of remote sensing and in situ sensors; characterize alternative platform vantage points and measurement modes; and to explore potential rules of interaction between sensors and weather forecast/data assimilation components to reduce model error growth and forecast uncertainty. We will demonstrate key SWS elements using a proposed future lidar wind measurement mission as a use case.

Paper Details

Date Published: 24 September 2007
PDF: 11 pages
Proc. SPIE 6684, Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS, 668413 (24 September 2007); doi: 10.1117/12.735746
Show Author Affiliations
Michael S. Seablom, NASA Goddard Space Flight Ctr. (United States)
Stephen J. Talabac, NASA Goddard Space Flight Ctr. (United States)
Glenn J. Higgins, Northrop Grumman IT TASC (United States)
Brice T. Womack, Northrop Grumman IT TASC (United States)

Published in SPIE Proceedings Vol. 6684:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS
Mitchell D. Goldberg; Hal J. Bloom; Allen H.-L. Huang; Philip E. Ardanuy, Editor(s)

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