论文标题
使用HMI光电矢量和空间标准偏差概要图的太阳风预测的不确定性估计值
Uncertainty Estimates of Solar Wind Prediction using HMI Photospheric Vector and Spatial Standard Deviation Synoptic Maps
论文作者
论文摘要
当前的太阳风预测基于在1 AU处观察到的太阳风速与光电球和内电晕之间的太阳风速与磁通管膨胀速率（FTE）之间的基于王的经验关系，在该冠状动脉上计算了FTE，其中FTE是由冠状模型计算的，这些模型是通过光球密度的磁场和磁场散布的磁场的冠状模型来计算的。 配置。由于这些概要图是所有太阳磁数据产品中最广泛使用的，因此由概要图中的不确定性引起的模型预测中的不确定性值得研究。然而，直到Bertello等人，才可用与天气图构造有关的估计值。 （太阳能物理学，289，2014）获得了空间标准偏差概要图； 98个光电概要图的空间标准偏差图的蒙特卡罗实现。在本文中，我们介绍了CSSS模型在1 AU预测的太阳风速中的不确定性的估计值，这是由于光电概要图中的不确定性。我们还提供了与立体/secchi euv天气图预测的冠状孔位置的比较。为了量化所涉及的不确定性的程度，我们将预测速度与同一时期的Omni太阳风数据进行了比较（考虑到太阳能风流时间），并在它们之间获得了均方根误差。为了说明在太阳风预测中的不确定性估计值的重要性，我们在太阳周期的不同阶段进行了三个Carrington旋转的分析，CR 2102，CR 2137和CR 2160。不确定性估计是改善太阳风预测准确性的当前和未来努力所必需的关键信息。
Current solar wind prediction is based on the Wang & Sheeley empirical relationship between the solar wind speed observed at 1 AU and the rate of magnetic flux tube expansion (FTE) between the photosphere and the inner corona, where FTE is computed by coronal models that take the photospheric flux density synoptic maps as their inner boundary conditions to extrapolate the photospheric magnetic fields to deduce the coronal and the heliospheric magnetic field configuration. Since these synoptic maps are among the most widely-used of all solar magnetic data products, the uncertainties in the model predictions that are caused by the uncertainties in the synoptic maps are worthy of study. However, such an estimate related to synoptic map construction was not available until Bertello et al. (Solar Physics, 289, 2014) obtained the spatial standard deviation synoptic maps; 98 Monte-Carlo realizations of the spatial standard deviation maps for each photospheric synoptic maps. In this paper, we present an estimate of uncertainties in the solar wind speed predicted at 1 AU by the CSSS model due to the uncertainties in the photospheric synoptic maps. We also present a comparison of the coronal hole locations predicted by the models with the STEREO/SECCHI EUV synoptic maps. In order to quantify the extent of the uncertainties involved, we compared the predicted speeds with the OMNI solar wind data during the same period (taking the solar wind transit time into account) and obtained the root mean square error between them. To illustrate the significance of the uncertainty estimate in the solar wind prediction, we carried out the analysis for three Carrington rotations, CR 2102, CR 2137 and CR 2160 at different phases of the solar cycle. The uncertainty estimate is critical information necessary for the current and future efforts of improving the solar wind prediction accuracies.
