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arXiv 2003.04563astro-ph.SRnlin.CDphysics.data-anphysics.space-ph
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太阳磁场的全球演化与活动周期预测

Global Evolution of Solar Magnetic Fields and Prediction of Activity Cycles

Irina N. Kitiashvili

摘要:

太阳活动周期的预测是具有挑战性的,因为太阳内部的物理过程涉及广泛的多尺度动态,没有模型可以复制,因为现有的观测非常有限,主要覆盖表面层。日震学使探测对流区的太阳动力学成为可能,但目前只有两个太阳活动周期的差异旋转和纬向环流的变化。已经证明,覆盖400多年的太阳黑子观测数据可以用来校准Parker-Kleeorin-Ruzmaikin发电机模型,并且可以使用Ensemble卡尔曼滤波器(EnKF)方法将建模的磁场与太阳黑子观测数据联系起来,并对下一个活动周期进行可靠的预测。然而,为了更准确的预测,有必要使用对太阳磁场的实际观测,这些观测仅适用于最近四个太阳活动周期。在本文中,我简要地讨论了有限数量的可用观测对太阳周期参数的EnKF估计的准确性的影响,评估预测的标准,以及天气磁图预测太阳活动的应用。

英文摘要:

Prediction of solar activity cycles is challenging because physical processes inside the Sun involve a broad range of multiscale dynamics that no model can reproduce and because the available observations are highly limited and cover mostly surface layers. Helioseismology makes it possible to probe solar dynamics in the convective zone, but variations in differential rotation and meridional circulation are currently available for only two solar activity cycles. It has been demonstrated that sunspot observations, which cover over 400 years, can be used to calibrate the Parker-Kleeorin-Ruzmaikin dynamo model, and that the Ensemble Kalman Filter (EnKF) method can be used to link the modeled magnetic fields to sunspot observations and make reliable predictions of a following activity cycle. However, for more accurate predictions, it is necessary to use actual observations of the solar magnetic fields, which are available only for the last four solar cycles. In this paper I briefly discuss the influence of the limited number of available observations on the accuracy of EnKF estimates of solar cycle parameters, the criteria to evaluate the predictions, and application of synoptic magnetograms to the prediction of solar activity.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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