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Random Forest Model of Ultralow‐Frequency Magnetospheric Wave Power
Earth and Space Science ( IF 2.9 ) Pub Date : 2020-08-15 , DOI: 10.1029/2020ea001274
S. N. Bentley 1 , J. R. Stout 1 , T. E. Bloch 1 , C. E. J. Watt 1, 2
Affiliation  

Models of magnetospheric ultralow‐frequency (ULF) waves can be used to study wave phenomena and to calculate the effect of these waves on the energization and transport of radiation belt electrons. We present a decision tree ensemble (i.e., a random forest) model of ground‐based ULF wave power spectral density driven by solar wind speed vsw, north‐south component of the interplanetary magnetic field Bz, and variance of proton number density var(Np). This model corresponds to four radial locations in the magnetosphere (roughly L ∼ 4.21 to 7.94) and spans 1–15 mHz, with hourly magnetic local time resolution. The decision tree ensembles are easier to use than the previous model generation; they have better coverage, perform better at predicting power, and have reduced error due to intelligently chosen bins in parameter space. We outline the difficulties in extracting physics from parameterized models and demonstrate a hypothesis testing framework to iteratively explore finer driving processes. We confirm a regime change for ULF driving about Bz = 0. We posit that ULF wave power directly driven by magnetopause perturbations corresponds to a latitude‐dependent dawn‐dusk asymmetry, which we see with increasing speed. Model uncertainty identifies where the underlying physics is not fully captured; we find that power due to substorms is less well characterized by Bz > 0, with an effect that is seen globally and not just near midnight. The largest uncertainty is seen for the smallest amounts of solar wind driving, suggesting that internal magnetospheric properties may play a significant role in ULF wave occurrence.

中文翻译:

超低频磁层波功率的随机森林模型

磁层超低频(ULF)波的模型可用于研究波现象并计算这些波对辐射带电子的激发和传输的影响。我们提出了由太阳风速v s w,行星际磁场B z的南北分量和质子数密度的变化驱动的地面ULF波功率谱密度的决策树集合模型(即随机森林)模型。var(N p。该模型对应于四个径向位置在磁层(大致大号 〜4.21至7.94),跨度为1–15 mHz,具有每小时的磁性本地时间分辨率。决策树集成比上一代模型更易于使用。由于参数空间中的智能选择仓,它们具有更好的覆盖范围,更好的功率预测性能并减少了错误。我们概述了从参数化模型中提取物理过程的困难,并演示了一个假设测试框架来迭代探索更精细的驾驶过程。我们确认ULF驱动的状态变化约为B z  = 0。我们认为,由磁成磁扰动直接驱动的ULF波功率对应于纬度相关的黎明-黄昏不对称性,随着速度的增加,我们看到了这种不对称性。模型不确定性确定了未完全捕获基础物理的位置;我们发现,由于亚暴引起的功率的特征不太好,其B z  > 0,其影响在全球范围内可见,而不仅仅是在午夜附近。对于最小量的太阳风驱动,可以看到最大的不确定性,这表明内部磁层性质可能在ULF波的发生中起重要作用。
更新日期:2020-10-07
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