Mathematics – Probability
Scientific paper
Sep 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010amos.confe..32r&link_type=abstract
Proceedings of the Advanced Maui Optical and Space Surveillance Technologies Conference, held in Wailea, Maui, Hawaii, September
Mathematics
Probability
Scientific paper
Rapid assessment of space weather effects on satellites is a critical step in anomaly resolution and satellite threat assessment. That step, however, is often hindered by a number of factors including timely collection and delivery of space weather data and the inherent complexity of space weather information. As part of a larger, integrated space situational awareness program, Los Alamos National Laboratory has developed prototype operational space weather tools that run in real time and present operators with customized, user-specific information. The Dynamic Radiation Environment Assimilation Model (DREAM) focuses on the penetrating radiation environment from natural or nuclear-produced radiation belts. The penetrating radiation environment is highly dynamic and highly orbitdependent. Operators often must rely only on line plots of 2 MeV electron flux from the NOAA geosynchronous GOES satellites which is then assumed to be representative of the environment at the satellite of interest. DREAM uses data assimilation to produce a global, real-time, energy dependent specification. User tools are built around a distributed service oriented architecture (SOA) which allows operators to select any satellite from the space catalog and examine the environment for that specific satellite and time of interest. Depending on the application operators may need to examine instantaneous dose rates and/or dose accumulated over various lengths of time. Further, different energy thresholds can be selected depending on the shielding on the satellite or instrument of interest. In order to rapidly assess the probability that space weather effects, the current conditions can be compared against the historical distribution of radiation levels for that orbit. In the simplest operation a user would select a satellite and time of interest and immediately see if the environmental conditions were typical, elevated, or extreme based on how often those conditions occur in that orbit. This allows users to rapidly rule in or out environmental causes of anomalies. The same user interface can also allow users to drill down for more detailed quantitative information. DREAM can be run either from a distributed web-based user interface or as a stand-alone application for secure operations. We will discuss the underlying structure of the DREAM model and demonstrate the user interface that we have developed. We will also discuss future development plans for DREAM and how the same paradigm can be applied to integrating other space environment information into operational SSA systems.
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