Comparative analyses of current three-dimensional numerical solar wind models

被引:0
|
作者
Shi Tsan WU [1 ]
Murray DRYER [2 ]
机构
[1] Center for Space Plasma and Aeronomic Research, the University of Alabama in Huntsville
[2] Space Weather Predictions Center, National Weather Service, National Oceanic and Atmospheric Administration
基金
美国国家科学基金会;
关键词
space weather; solar wind models; comparative analyses;
D O I
暂无
中图分类号
P353.8 [星际磁场和太阳风];
学科分类号
070802 ;
摘要
We present a comparative study of the most advanced three-dimensional time-dependent numerical simulation models of solar wind. These models can be classified into two categories:(I) theoretical, empirical and numerically based models and(II) self-consistent multi-dimensional numerical magnetohydrodynamic(MHD) models. The models of Category I are used to separately describe the solar wind solution in two plasma flows regions: transonic/trans-Alfvénic and supersonic/super-Alfvénic, respectively. Models of Category II construct a complete, single, numerical solar wind solution through subsonic/sub-Alfvénic region into supersonic/super-Alfvénic region. The Wang-Sheeley-Arge(WSA)/ENLIL in CISM is the most successful space weather model that belongs to Category I, and the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme(BATS-R-US) code in SWMF(Space Weather Modeling Framework) and the solar-interplanetary conservative element solution element MHD(SIP-CESE MHD) model in SWIM(Space Weather Integrated Model) are the most commonly-used models that belong to Category II. We review the structures of their frameworks, the main results for solar wind background studies that are essential for solar transient event studies, and discuss the common features and differences between these two categories of solar wind models. Finally, we conclude that the transition of these two categories of models to operational use depends on the availability of computational resources at reasonable cost and point out that the models’ prediction capabilities may be improved by employing finer computational grids, incorporating more observational data and by adding more physical constraints to the models.
引用
收藏
页码:839 / 858
页数:20
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