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Predicting the magnetic vectors within coronal mass ejections arriving at Earth: 2. Geomagnetic response

机译:预测到达地球的日冕物质抛射中的磁矢量:2.地磁响应

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摘要

This is a companion to Savani et al. (2015) that discussed how a first-order prediction of the internal magnetic field of a coronal mass ejection (CME) may be made from observations of its initial state at the Sun for space weather forecasting purposes (Bothmer-Schwenn scheme (BSS) model). For eight CME events, we investigate how uncertainties in their predicted magnetic structure influence predictions of the geomagnetic activity. We use an empirical relationship between the solar wind plasma drivers and Kp index together with the inferred magnetic vectors, to make a prediction of the time variation of Kp (Kp). We find a 2σ uncertainty range on the magnetic field magnitude (|B|) provides a practical and convenient solution for predicting the uncertainty in geomagnetic storm strength. We also find the estimated CME velocity is a major source of error in the predicted maximum Kp. The time variation of Kp is important for predicting periods of enhanced and maximum geomagnetic activity, driven by southerly directed magnetic fields, and periods of lower activity driven by northerly directed magnetic field. We compare the skill score of our model to a number of other forecasting models, including the NOAA/Space Weather Prediction Center (SWPC) and Community Coordinated Modeling Center (CCMC)/SWRC estimates. The BSS model was the most unbiased prediction model, while the other models predominately tended to significantly overforecast. The True skill score of the BSS prediction model (TSS = 0.43 ± 0.06) exceeds the results of two baseline models and the NOAA/SWPC forecast. The BSS model prediction performed equally with CCMC/SWRC predictions while demonstrating a lower uncertainty.
机译:这是Savani等人的伴侣。 (2015)讨论了如何从太阳在太阳的初始状态的观测结果中对日冕物质抛射(CME)的内部磁场进行一阶预测(Bothmer-Schwenn方案(BSS)模型)。对于八个CME事件,我们调查了其预测磁结构的不确定性如何影响地磁活动的预测。我们使用太阳风等离子体驱动器和Kp指数以及推断的磁矢量之间的经验关系,来预测Kp(Kp)的时间变化。我们发现磁场强度(| B |)的2σ不确定性范围为预测地磁风暴强度的不确定性提供了一种实用且方便的解决方案。我们还发现,估计的CME速度是预测的最大Kp误差的主要来源。 Kp的时间变化对于预测由南向磁场驱动的增强和最大地磁活动的周期以及由北向磁场驱动的较低活动的周期很重要。我们将模型的技能得分与许多其他预测模型进行了比较,包括NOAA /太空天气预测中心(SWPC)和社区协调建模中心(CCMC)/ SWRC估算。 BSS模型是最没有偏见的预测模型,而其他模型则主要倾向于明显的过度预测。 BSS预测模型的真实技能得分(TSS = 0.43±0.06)超过了两个基线模型和NOAA / SWPC预测的结果。 BSS模型预测与CCMC / SWRC预测性能相同,同时显示出较低的不确定性。

著录项

  • 来源
    《Space Weather》 |2017年第2期|441-461|共21页
  • 作者单位

    Goddard Planetary Heliophysics Institute, University of Maryland, Baltimore, Maryland, USA, NASA, Goddard Space Flight Center, Greenbelt, Maryland, USA;

    Solar Section, Applied Physics Laboratory Johns Hopkins University, Laurel, Maryland, USA;

    Department of Astronomy, University of Maryland, College Park, Maryland, USA, NASA, Goddard Space Flight Center, Greenbelt, Maryland, USA;

    NASA, Goddard Space Flight Center, Greenbelt, Maryland, USA;

    NASA, Goddard Space Flight Center, Greenbelt, Maryland, USA;

    NASA, Goddard Space Flight Center, Greenbelt, Maryland, USA;

    Institute for Astrophysics and Computational Sciences, Catholic University of America, Washington, District of Columbia, USA, NASA, Goddard Space Flight Center, Greenbelt, Maryland, USA;

    Institute for Astrophysics and Computational Sciences, Catholic University of America, Washington, District of Columbia, USA, NASA, Goddard Space Flight Center, Greenbelt, Maryland, USA;

    Institute for Astrophysics, Georg-August-University of Göttingen, Göttingen, Germany;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Magnetosphere; Predictive models; Weather forecasting; Earth; Uncertainty; Storms;

    机译:磁层;预测模型;天气预报;地球;不确定性;风暴;
  • 入库时间 2022-08-17 23:56:38

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