83rd Annual

Monday, 10 February 2003
Future Architectures for Operational Forecasting: Two-way Interacting SensorWeb and Model/Assimilation System
Mark Steiner, NASA/GSFC, Greenbelt, MD; and M. Seablom, S. Neeck, G. McConaughy, M. Clausen, M. Kalb, and R. Muller
Poster PDF (673.9 kB)
NASA’s Earth Science Technology Office (ESTO) appointed NASA’s Goddard Space Flight Center to perform an advanced concept study that would identify science knowledge and technology improvements needed to enable skilled weather forecasts out to 10 - 14 days in the 2025 timeframe.

This presentation will provide an overview of the phase I study results, including development of the science needs for the analysis, and a notional architecture concept for a future operational system. The architecture concept is used as a starting point for gap analyses that identify technologies needed to provide the technical capabilities that would enable the proposed improvements in weather forecasting.

The central premise of the study approach is that a global observing system and a forecast modeling/ assimilation system interactively feeding information to one another in real-time could constitute a new type of operational weather forecast system whose skill improvements would represent a leap forward, and whose performance would be self-optimizing for any level of resources invested. The primary capabilities needed to execute this futuristic concept include a global mesoscale model with 1 – 25 km horizontal resolution, and a fully integrated ground-space global observing system (SensorWeb) providing high time resolution (1 –3 hourly) and space resolution (1- 25 km) global coverage of key geophysical variables. A seamless ground–space communications network linking these two segments will enable both coordinated global observing among spacecraft and delivery of those observations in near real time for integration into the model forecast system.

Among the larger challenges identified is designing a software system that would possess such an unprecedented level of semi-autonomous intelligence, that it would actually be able to make informed “scientific” judgments, weigh priorities, then direct the coordinated tasking of in situ and space-based platforms and instruments based on observational needs identified from a ground-based modeling system. All this would have to occur continuously and in real-time in order to meet operational forecast requirements. Greater reliance on high performance on-board computing seems essential for supporting both system intelligence as well as data analysis functions.

Also to be presented are preliminary ideas on how the entire system must be designed and operated in order to provide the needed coordination between and among space platforms, instruments and ground. Given initial notions of the desired interactions, phase II of this study (in progress) will be to consider in more detail the system logic, architectures and technologies, as well as advances in system theory, communications and artificial intelligence that could provide the necessary interactivity and results from a highly intelligent, highly integrated operational weather forecast system.

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