Using Multiple Signatures to Improve Accuracy of Substorm Identification
Using Multiple Signatures to Improve Accuracy of Substorm Identification
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DOI：
10.1029/2019ja027559
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发表时间：
2019-11
期刊：
影响因子：
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通讯作者：
J. Haiducek;D. Welling;S. Morley;N. Ganushkina;X. Chu
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文献类型：
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作者：
J. Haiducek;D. Welling;S. Morley;N. Ganushkina;X. Chu
我们已经开发了一个新的程序，用于将多个来源的实体发作时间列表结合在一起。在各个列表中出现的正面标识和填充数据差距。结果以及在结果时间内的太阳风驱动条件和磁层响应的超级时期分析也可与先前的结果比较。在太阳能驱动，磁层响应和等待时间分布方面，观察到的实量的特征特征表明MHD模型在预测实量发作时间方面具有统计学意义。
We have developed a new procedure for combining lists of substorm onset times from multiple sources. We apply this procedure to observational data and to magnetohydrodynamic (MHD) model output from 1–31 January 2005. We show that this procedure is capable of rejecting false positive identifications and filling data gaps that appear in individual lists. The resulting combined onset lists produce a waiting time distribution that is comparable to previously published results, and superposed epoch analyses of the solar wind driving conditions and magnetospheric response during the resulting onset times are also comparable to previous results. Comparison of the substorm onset list from the MHD model to that obtained from observational data reveals that the MHD model reproduces many of the characteristic features of the observed substorms, in terms of solar wind driving, magnetospheric response, and waiting time distribution. Heidke skill scores show that the MHD model has statistically significant skill in predicting substorm onset times.