论文标题
为2000年7月14日的巴士底日活动模拟了充满活力的质子传播和加速度
Energetic Proton Propagation and Acceleration Simulated for the Bastille Day Event of July 14, 2000
论文作者
论文摘要
这项工作是由2000年7月14日(“ Bastille Day”)太阳能质子事件的模拟引起的。我们在SPE威胁评估工具(STAT)框架内使用了高能粒子辐射环境模型(EPREM)和Corona-Heliosphere(Corhel)软件套件,以模型质子加速到GEV Enver,由于CME通过低太阳能电晕,并将模型结果与GONE-08的观察进行了比较。耦合模拟模型从1到20 $ r_ \ odot $的粒子加速度,之后仅建模粒子传输。模拟大致重现了峰值事件通量,以及能量粒子事件的时间和空间位置。虽然模拟的前几个小时内的峰通量和总体变化与观测非常吻合,但建模的CME在数小时后移动到内部模拟边界之外。因此,该模型准确地描述了低电晕中的加速过程,并解决了靠近太阳的最快加速的位置。来自地球附近多个模拟观察者的整体通量信封的图进一步改善了与观测值的比较,并增加了预测太阳颗粒事件的潜力。损坏的law拟合在低能范围内的扩散加速度理论一致。在高能量范围内,它们证明了加速度的变化,并反映了事件间可变化的可变性,观察到的太阳能周期23 Gles。我们讨论改善统计预测的方法,包括使用校正后的gos能池和计算符合种子光谱的方法。本文展示了一种用于模拟低频SEP加速度的预测工具。
This work presents results from simulations of the 14 July 2000 ("Bastille Day") solar proton event. We used the Energetic Particle Radiation Environment Model (EPREM) and the CORona-HELiosphere (CORHEL) software suite within the SPE Threat Assessment Tool (STAT) framework to model proton acceleration to GeV energies due to the passage of a CME through the low solar corona, and compared the model results to GOES-08 observations. The coupled simulation models particle acceleration from 1 to 20 $R_\odot$, after which it models only particle transport. The simulation roughly reproduces the peak event fluxes, and timing and spatial location of the energetic particle event. While peak fluxes and overall variation within the first few hours of the simulation agree well with observations, the modeled CME moves beyond the inner simulation boundary after several hours. The model therefore accurately describes the acceleration processes in the low corona and resolves the sites of most rapid acceleration close to the Sun. Plots of integral flux envelopes from multiple simulated observers near Earth further improve the comparison to observations and increase potential for predicting solar particle events. Broken-power-law fits to fluence spectra agree with diffusive acceleration theory over the low energy range. Over the high energy range, they demonstrate the variability in acceleration rate and mirror the inter-event variability observed solar-cycle 23 GLEs. We discuss ways to improve STAT predictions, including using corrected GOES energy bins and computing fits to the seed spectrum. This paper demonstrates a predictive tool for simulating low-coronal SEP acceleration.