发表机构
Istituto Nazionale di Geofisica e Vulcanologia (INGV); Università della Calabria; KU Leuven; University of Maria Curie-Skłodowska（意大利国家地球物理与火山学研究所; 卡塔尼亚大学; 荷语鲁汶大学; 玛丽亚·居里-斯可多夫斯卡大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对空间天气的跨尺度挑战，提出MICMAC模型结合湍流微观扩散与EUHFORIA宏观模拟，揭示湍流会扭曲CME与地球的磁连接，其跨尺度耦合需纳入空间天气模型，对SEP预报有重要意义。
AI 中文摘要
日冕物质抛射（CME）是空间天气最强大的驱动因素之一，但对其的预测仍难以实现。一个根本障碍是该问题的多尺度特性：大尺度磁流体动力学模型无法解析控制粒子输运和磁连接的湍流涨落。我们提出了一种新模型，将湍流的微观扩散方法与宏观的EUHFORIA模拟相结合（MICMAC），以应对空间天气的跨尺度挑战。通过将湍流特性纳入此类小尺度蒙特卡罗模拟，我们描述了一次极端CME事件，追踪从CME驱动的激波到1天文单位（AU）的磁力线和100 MeV质子。我们发现，湍流会显著拓宽并扭曲CME前端与地球之间的磁连接，产生高度非高斯、各向异性且呈斑块状的足点分布。MICMAC表明，该分布的涡量（非高斯性）会随CME接近地球而增长，标志着异常扩散行为。一个简单的剪切层玩具模型再现了观测到的面内各向异性，表明局部电流片几何结构会对湍流场留下持久的记忆。我们的结果表明，空间天气模型必须考虑CME的大尺度结构与环境湍流之间的跨尺度耦合。我们还讨论了其对太阳高能粒子（SEP）预报和解释多航天器观测的意义。
英文摘要
Coronal Mass Ejections (CMEs) are among the most powerful drivers of space weather, yet their prediction remains elusive. A fundamental obstacle is the problem's multiscale nature: large-scale magnetohydrodynamic models do not resolve the turbulent fluctuations that govern particle transport and magnetic connectivity. We present a new model that combines a MICroscopic diffusion approach of turbulence with MACroscopic EUHFORIA simulations (MICMAC) to address the cross-scale challenge of space weather. By incorporating turbulence properties into such small-scale Monte Carlo simulations, we describe an extreme CME event, tracing both magnetic field lines and 100 MeV protons from the CME-driven shock to 1 AU. We find that turbulence dramatically broadens and distorts the magnetic connection between the CME nose and Earth, producing footpoint distributions that are highly non-Gaussian, anisotropic, and patchy. MICMAC suggests that the distribution's enstrophy (non-Gaussianity) grows as the CME approaches Earth, signaling anomalous diffusive behavior. A simple shear-layer toy model reproduces the observed in-plane anisotropy, suggesting that local current sheet geometry imprints a persistent memory on the turbulent field. Our results demonstrate that cross-scale coupling between the CME's large-scale structure and ambient turbulence must be accounted for in space weather models. We discuss implications for SEP forecasting and interpreting multi-spacecraft observations.
