地磁感应电流（GIC）与太阳风条件的经验关系
Empirical Relationship for Geomagnetically Induced Currents (GIC) and Solar Wind Conditions
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中文总结 AI 辅助
本研究基于67个站点9次强风暴数据建立经验模型，利用太阳风参数与局地因子估算地磁感应电流，为空间天气从业者提供高效的GIC估算替代方案
中文摘要 AI 辅助
极端空间天气事件期间的地磁感应电流（GIC）对现代基础设施构成重大危害，包括电网、电信系统、管道和铁路。本研究提出经验模型，旨在快速、针对站点地估算风暴期间预期的最大GIC |GIC|_max。利用2020年至2025年间发生的9次K_p≥8的强地磁风暴中67个站点的数据，我们开展了多元线性回归和分位数回归，纳入太阳风参数和局地缩放因子。太阳风参数用于表征风暴强度，包括行星际磁场z分量最小值（B_z^IMF）_min和太阳风速度x分量最大值（V_x）_max；缩放因子则考虑地磁纬度（α）和地表电导率（β）导致的局地差异。通过最优子集选择和校正赤池信息准则（AICc）确定的6参数模型，是平均|GIC|_max的最优预测器，得出皮尔逊相关系数r=0.73，决定系数R²=0.54。为研究风暴期间的峰值GIC，开发了7参数分位数回归模型以估算|GIC|_max的上80%边界。对1995年以来39次强风暴的统计分析显示，|GIC|_max的上边界符合对数正态分布。这些关系为复杂的基于物理的模拟提供了计算高效的替代方案，使空间天气从业者能够在高级分析中估算站点特异性GIC。
英文摘要
Geomagnetically induced currents (GICs) during extreme space weather events represent a critical hazard to modern infrastructure, including electrical power grids, telecommunication systems, pipelines, and railways. This study presents empirical models designed to provide rapid, site-specific estimates of the maximum GIC, $|\text{GIC}|_{\text{max}}$, expected during a storm. Utilizing data from 67 sites across nine major geomagnetic storms ($K_p \ge 8$) occurring between 2020 and 2025, we performed multivariate linear and quantile regressions incorporating solar wind parameters and local scaling factors. The solar wind parameters address storm intensity and are the minimum interplanetary magnetic field $z$-component, $(B_{z}^{\tiny{\text{IMF}}})_{\text{min}}$, and the maximum magnitude of the solar wind velocity $x$-component, $(V_{x})_{\text{max}}$. The scaling factors account for local differences due to geomagnetic latitude ($α$) and ground conductivity ($β$). A 6-parameter model was identified via best subset selection and the corrected Akaike Information Criterion (AICc) as the optimal predictor for mean $|\text{GIC}|_{\text{max}}$, yielding a Pearson correlation of $r = 0.73$ and a coefficient of determination of $R^2 = 0.54$. To examine peak GICs during storms, a 7-parameter quantile regression model was developed to estimate the upper 80% bound of $|\text{GIC}|_{\text{max}}$. Statistical analysis of 39 severe storms since 1995 shows that the $|\text{GIC}|_{\text{max}}$ upper bounds are consistent with a lognormal distribution. These relationships offer a computationally efficient alternative to complex physics-based simulations, enabling space weather practitioners to estimate site-specific GICs in high-level analyses.
