Validation for solar wind prediction at Earth: Comparison of coronal and heliospheric models installed at the CCMC
Validation for solar wind prediction at Earth: Comparison of coronal and heliospheric models installed at the CCMC
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DOI：
10.1002/2015sw001174
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发表时间：
2015-05
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影响因子：
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通讯作者：
L. Jian;P. MacNeice;A. Taktakishvili;D. Odstrcil;B. Jackson;H.‐S. Yu;P. Riley;I. Sokolov;R. E
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文献类型：
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作者：
L. Jian;P. MacNeice;A. Taktakishvili;D. Odstrcil;B. Jackson;H.‐S. Yu;P. Riley;I. Sokolov;R. E
社区协调建模中心(CCMC)最近升级了多种日冕和日球层模型，包括Wang-Sheeley-Arge(WSA)-Enlil模型、MHD-Above-a-Sphere(MAS)-Enlil模型、空间天气模型框架(SWMF)和利用行星际闪烁数据的日球层析成像。为了研究来自不同来源、不同日冕模式和不同模式版本的光球层磁图对模式性能的影响，我们将这些模式分成10个组合。选择2007年的7次卡林顿自转作为时间窗口，将模拟结果与运行任务作为节点在互联网上比较了第23太阳周期末期的近地空间环境数据。目视比较被证明是对模式再现太阳风参数的时间序列和统计数据的能力的定量评估的必要补充。MAS-Enlil模式较好地捕捉了太阳风参数的时间模式，而WSA-Enlil模式与归一化太阳风参数的时间序列更好地匹配。模型通常高估了慢风温度，低估了快风温度和磁场。使用改进的算法，我们已经确定磁场扇区边界(SBS)和慢到快的流相互作用区(SIRS)是聚焦结构。捕获它们的成功率和时间偏差在很大程度上因模型而异。对于这段平静的时期，新版本的MAS-Enlil模型最适合于SBS，而日球层层析成像最适合SIRS。新版本的SWMF增加了更多的物理内容，需要进一步开发。对每个模型的一般优点和缺点进行了诊断，以便为模型开发人员和用户提供公正的参考。
Multiple coronal and heliospheric models have been recently upgraded at the Community Coordinated Modeling Center (CCMC), including the Wang‐Sheeley‐Arge (WSA)‐Enlil model, MHD‐Around‐a‐Sphere (MAS)‐Enlil model, Space Weather Modeling Framework (SWMF), and heliospheric tomography using interplanetary scintillation data. To investigate the effects of photospheric magnetograms from different sources, different coronal models, and different model versions on the model performance, we run these models in 10 combinations. Choosing seven Carrington rotations in 2007 as the time window, we compare the modeling results with the Operating Mission as Nodes on the Internet data for near‐Earth space environment during the late declining phase of solar cycle 23. Visual comparison is proved to be a necessary addition to the quantitative assessment of the models' capabilities in reproducing the time series and statistics of solar wind parameters. The MAS‐Enlil model captures the time patterns of solar wind parameters better, while the WSA‐Enlil model matches with the time series of normalized solar wind parameters better. Models generally overestimate slow wind temperature and underestimate fast wind temperature and magnetic field. Using improved algorithms, we have identified magnetic field sector boundaries (SBs) and slow‐to‐fast stream interaction regions (SIRs) as focused structures. The success rate of capturing them and the time offset vary largely with models. For this quiet period, the new version of MAS‐Enlil model works best for SBs, while heliospheric tomography works best for SIRs. The new version of SWMF with more physics added needs more development. General strengths and weaknesses for each model are diagnosed to provide an unbiased reference to model developers and users.