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arXiv 1206.2106astro-ph.SRphysics.plasm-phphysics.space-ph
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磁通量的湍流抽运减少太阳周期记忆并因此影响太阳活动的可预测性

Turbulent Pumping of Magnetic Flux Reduces Solar Cycle Memory and thus Impacts Predictability of the Sun's Activity

Bidya Binay Karak, Dibyendu Nandy

摘要:

太阳磁活动对空间环境和气候有重要影响,因此预测太阳磁活动具有重要意义。然而,最近对太阳活动周期振幅的预测导致了不同的预测,没有达成共识。Yeates等人(2008年)已经表明,太阳发电机机制的动态记忆控制着可预测性,这种记忆对于平流和扩散主导的太阳对流区是不同的。通过利用随机强迫,运动发电机模拟,我们表明,列入向下湍流抽运的磁通量减少了平流和扩散为主的太阳能发电机的记忆只有一个周期,更强的抽运进一步降低这种记忆。因此,我们的研究结果调和了对太阳活动周期24振幅的不同的基于发电机模型的预测。我们的结论是,只有在最低限度之前才能对太阳活动的最大限度作出可靠的预测-允许对空间天气进行大约5年的提前规划。为了更准确的预测,在预测模型中有必要进行连续的数据同化,以解释太阳的短暂记忆。

英文摘要:

Prediction of the Sun's magnetic activity is important because of its effect on space environment and climate. However, recent efforts to predict the amplitude of the solar cycle have resulted in diverging forecasts with no consensus. Yeates et al. (2008) have shown that the dynamical memory of the solar dynamo mechanism governs predictability and this memory is different for advection- and diffusion-dominated solar convection zones. By utilizing stochastically forced, kinematic dynamo simulations, we demonstrate that the inclusion of downward turbulent pumping of magnetic flux reduces the memory of both advection- and diffusion-dominated solar dynamos to only one cycle; stronger pumping degrades this memory further. Thus, our results reconcile the diverging dynamo-model-based forecasts for the amplitude of solar cycle 24. We conclude that reliable predictions for the maximum of solar activity can be made only at the preceding minimum--allowing about 5 years of advance planning for space weather. For more accurate predictions, sequential data assimilation would be necessary in forecasting models to account for the Sun's short memory.

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