论文标题

通过数值模型预测环境太阳风。 ii。一种适应性预测系统,用于指定太阳速度附近的太阳速度

Forecasting the Ambient Solar Wind with Numerical Models. II. An Adaptive Prediction System for Specifying Solar Wind Speed Near the Sun

论文作者

Reiss, Martin A., MacNeice, Peter J., Muglach, Karin, Arge, Charles N., Möstl, Christian, Riley, Pete, Hinterreiter, Jürgen, Bailey, Rachel, Owens, Mathew J., Amerstorfer, Tanja, Amerstorfer, Ute

论文摘要

环境太阳风流和田地影响行星际介质中冠状质量弹出的复杂传播动力学,并在塑造地球太空天气环境中起着至关重要的作用。太空天气研究和预测界的一个关键科学目标是开发,实施和优化数值模型,以指定在地球层模型域内边界的太阳风条件的大规模特性。在这里,我们提出了一个自适应预测系统,该系统将太阳风的原位测量信息融合到数值模型中,以更好地匹配太阳附近的全球太阳风模型解决方案,并在地球附近具有盛行的物理条件。通过这种方式,我们试图推进建立良好的太阳风模型的预测能力,以指定太阳风速,包括Wang-Sheeley-Arge(WSA)模型。特别是,我们使用Heliosperic向上伸出(HUX)模型将太阳能解决方案从近阳性环境绘制到地球附近。此外,我们还提出了新开发的可调式HUX(THUX)模型,该模型解决了基础汉堡方程的粘性形式。我们对2006-2015期间产生的太阳风预测进行统计分析。提出的预测方案改善了所有研究的冠状/地层模型组合,并比我们的参考基线模型更好地估计地球太阳风状态。我们讨论了为什么是这种情况,并得出结论,我们的发现对应用太空天气研究和预测的未来实践具有重要意义。

The ambient solar wind flows and fields influence the complex propagation dynamics of coronal mass ejections in the interplanetary medium and play an essential role in shaping Earth's space weather environment. A critical scientific goal in the space weather research and prediction community is to develop, implement and optimize numerical models for specifying the large-scale properties of solar wind conditions at the inner boundary of the heliospheric model domain. Here we present an adaptive prediction system that fuses information from in situ measurements of the solar wind into numerical models to better match the global solar wind model solutions near the Sun with prevailing physical conditions in the vicinity of Earth. In this way, we attempt to advance the predictive capabilities of well-established solar wind models for specifying solar wind speed, including the Wang-Sheeley-Arge (WSA) model. In particular, we use the Heliospheric Upwind eXtrapolation (HUX) model for mapping the solar wind solutions from the near-Sun environment to the vicinity of Earth. In addition, we present the newly developed Tunable HUX (THUX) model which solves the viscous form of the underlying Burgers equation. We perform a statistical analysis of the resulting solar wind predictions for the time 2006-2015. The proposed prediction scheme improves all the investigated coronal/heliospheric model combinations and produces better estimates of the solar wind state at Earth than our reference baseline model. We discuss why this is the case, and conclude that our findings have important implications for future practice in applied space weather research and prediction.

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