Evaluating Pointing Strategies for Future Solar Flare Missions

SOLAR PHYSICS(2021)

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摘要
Solar flares are events of intense scientific interest. Although certain solar conditions are known to be associated with flare activity, the exact location and timing of an individual flare on the Sun cannot as yet be predicted with certainty. Missions whose science objectives depend on observing solar flares must often make difficult decisions on where to target their observations if they do not observe the full solar disk. Yet, there is little analysis in the literature that might guide these mission operations to maximize their opportunities to observe flares. In this study, we analyze and simulate the performance of different observation strategies using historical flare and active region data from 2011 to 2014. We test a number of different target selection strategies based on active region complexity and recent flare activity, each of which is examined under a range of operational assumptions. In each case, we investigate various metrics such as the number of flares observed, the size of flares observed, and operational considerations such as the number of instrument repoints required. Overall, target selection methods based on recent flare activity showed the best overall performance but required more repointings than other methods. The mission responsiveness to new information is identified as another strong factor determining flare observation performance. It is also shown that target selection methods based on active region complexities show a significant pointing bias toward the western solar hemisphere. As expected, the number of flares observed grows quickly with field-of-view size until the approximate size of an active region is reached, but further improvements beyond the active region size are much more incremental. These results provide valuable performance estimates for a future mission focused on solar flares and inform the requirements that would ensure mission success.
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关键词
Flares, Active regions, Instrumentation and data management
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