Space Weather Modeling Capabilities Assessment: Neutral Density for Orbit Determination at low Earth orbit
Space Weather Modeling Capabilities Assessment: Neutral Density for Orbit Determination at low Earth orbit
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DOI：
10.1029/2018sw002027
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发表时间：
2018-11
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影响因子：
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通讯作者：
S. Bruinsma;Eric K. Sutton;Stanley C. Solomon;Tim Fuller-Rowell;M. Fedrizzi
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作者：
S. Bruinsma;Eric K. Sutton;Stanley C. Solomon;Tim Fuller-Rowell;M. Fedrizzi
热层密度变化的描述和预测是空间气象观测和建模的一项关键挑战，因为它是太阳和地面大气之间复杂相互作用的结果之一，也因为它对于跟踪在近地空间轨道上的物体具有重要的业务意义。对于近地轨道，中性密度变化是轨道要素传播和预报的最重要的不确定性。最近在国家航空航天局社区协调建模中心的主持下举行的一次国际会议包括一个关于中性密度建模的讲习班，利用经验方法和数值方法，并组织了模型比较和评价方面的初步工作。在这里，我们报告了可用的可开发密度数据集、选定的年份和风暴事件，以及用于完整模型评估的指标。五个模型(三个经验模型和两个数值模型)和中性密度数据集之间的比较包括CHAMP、GRACE和GOCE卫星的测量，作为将在社区协调建模中心实施的评估程序的例子。这些模型总体上表现得相当不错，尽管有时会出现季节性误差，而且冲动性地磁风暴事件仍然具有挑战性。在统计的基础上，数值模型仍在追赶经验方法，但在描述这些短期变化方面具有巨大的潜力。
The specification and prediction of density changes in the thermosphere is a key challenge for space weather observations and modeling, because it is one result of complex interactions between the Sun and the terrestrial atmosphere and also because it is of operational importance for tracking objects orbiting in near‐Earth space. For low Earth orbit, neutral density variation is the most important uncertainty for propagation and prediction of orbital elements. A recent international conference conducted under the auspices of the National Aeronautics and Space Administration Community Coordinated Modeling Center included a workshop on neutral density modeling, using both empirical and numerical methods, and resulted in organization of an initial effort in model comparison and evaluation. Here we report on the exploitable density data sets available, the selected years and storm events, and the metrics for complete model assessment. Comparisons between five models (three empirical and two numerical) and neutral density data sets that include measurements by the CHAMP, GRACE, and GOCE satellites are presented as examples of the assessment procedure that will be implemented at Community Coordinated Modeling Center. The models in general performed reasonably well, although seasonal errors sometimes are present, and impulsive geomagnetic storm events remain challenging. Numerical models are still catching up to empirical methods on a statistical basis, but hold great potential for describing these short‐term variations.