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A comparison of flare forecasting methods, I: Results from the 'All-Clear' Workshop

机译:耀斑预测方法的比较,I:“全透明”研讨会的结果

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摘要

Solar flares produce radiation which can have an almost immediate effect on the near-Earth environment, making it crucial to forecast flares in order to mitigate their negative effects. The number of published approaches to flare forecasting using photospheric magnetic field observations has proliferated, with varying claims about how well each works. Because of the different analysis techniques and data sets used, it is essentially impossible to compare the results from the literature. This problem is exacerbated by the low event rates of large solar flares. The challenges of forecasting rare events have long been recognized in the meteorology community, but have yet to be fully acknowledged by the space weather community. During the interagency workshop on “all clear” forecasts held in Boulder, CO in 2009, the performance of a number of existing algorithms was compared on common data sets, specifically line-of-sight magnetic field and continuum intensity images from MDI, with consistent definitions of what constitutes an event. We demonstrate the importance of making such systematic comparisons, and of using standard verification statistics to determine what constitutes a good prediction scheme. When a comparison was made in this fashion, no one method clearly outperformed all others, which may in part be due to the strong correlations among the parameters used by different methods to characterize an active region. For M-class flares and above, the set of methods tends towards a weakly positive skill score (as measured with several distinct metrics), with no participating method proving substantially better than climatological forecasts.
机译:太阳耀斑产生的辐射几乎可以对近地环境产生直接影响,因此预测耀斑对减轻其负面影响至关重要。使用光球磁场观测进行耀斑预测的已发布方法的数量激增,人们对每种方法的工作原理有不同的主张。由于使用了不同的分析技术和数据集,因此根本无法比较文献结果。大型太阳耀斑的低发生率使这个问题更加严重。预报罕见事件的挑战早已在气象界得到认可,但尚未得到太空天气界的充分认识。在2009年在科罗拉多州博尔德举行的关于“所有清晰”预测的机构间研讨会上,在通用数据集(特别是MDI的视线磁场和连续谱强度图像)上比较了许多现有算法的性能,构成事件的定义。我们展示了进行此类系统比较以及使用标准验证统计信息确定构成良好预测方案的重要性。当以这种方式进行比较时,没有一种方法明显胜过所有其他方法,这可能部分是由于不同方法用来表征有源区域的参数之间存在很强的相关性。对于M级以上的耀斑,该方法集倾向于获得较弱的正技能得分(用几个不同的指标衡量),没有一种参与方法被证明比气候预报更好。

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