论文标题

了解HASDM的可变性以支持太空流量管理

Understanding variability in HASDM to support space traffic management

论文作者

Tobiska, W. Kent, Pilinski, Marcin D., Mutschler, Shaylah, Wahl, Kaiya, Yoshii, Jean, Bouwer, Dave, Mehta, Piyush, Licata, Richard

论文摘要

随着计划更多的商业星座,低地球轨道(LEO)对象的数量将在两年内设置为三倍。狮子座物体的生长直接增加了由于空间碎屑而引起的物体之间无意碰撞的可能性。有效的空间交通管理需要准确了解上层大气密度的变异性。数据同化建模,其中基于物理的模型是通过测量来告知的,它提供了当今指定和预测空间天气的最佳功能。该建模的基础来自设置高精度卫星阻力模型(HASDM)密度数据库。我们报告了了解HASDM的变异性的研究。我们从集合HASDM密度数据库中确定两个热圈特征。首先,我们已经证实,分子传导的时间尺度非常快(1小时)以上200 km,以在热圈中垂直转移能量。这导致在100-200 km区域的传导时间更长的时间尺度,在该区域中,通过分子传导耗能最多2天才能在该区域跨该区域过渡。现在,我们对整个热圈的能量变化的时间刻度有了很好的了解。其次,尽管AP代表的每日平均地磁活动水平,但集合HASDM密度数据显示了常见的可变性范围。在较高水平的平均地磁活动中,密度平均值和中位数在所有高度水平上都会增加。但是,从AP的每日平均值到下一个的相对可变性范围是一致的。原因很可能是热层的潜在预态密度取决于太阳能和fuv辐照,从而造成了上层大气的热基础。每日平均地磁活动是对该基础的扰动。

With more commercial constellations planned, the number of Low Earth Orbit (LEO) objects is set to TRIPLE in two years. The growth in LEO objects directly increases the probability of unintentional collisions between objects due to accumulating space debris. Effective space traffic management needs accurate knowledge of the variability in upper atmosphere densities. Data assimilative modeling, where physics-based models are informed by measurements, supplies the best capability today for specifying and predicting space weather. The foundation for this modeling comes from the SET High Accuracy Satellite Drag Model (HASDM) density database. We report on studies to understand the variabilities in HASDM. We identify two thermospheric features from the SET HASDM density database. First, we have confirmed that the time scale is very rapid (1-hour) for molecular conduction above 200 km to transfer energy vertically in the thermosphere. This results couples with a longer timescale for conduction in the 100-200 km region where it takes up to 2 days for energy to transition across that region via molecular conduction. We now have an excellent picture of the timescales of energy change throughout the thermosphere. Second, the SET HASDM density data display a common range of variability despite the level of daily averaged geomagnetic activity as represented by Ap. During higher levels of daily averaged geomagnetic activity, the density mean and median values increase at all altitude levels. However, the relative range of variability is consistent from one daily average of Ap to the next. The reason is likely to be that the underlying pre-storm density of the thermosphere is determined by the solar EUV and FUV irradiances that create a thermal foundation of the upper atmosphere. The daily averaged geomagnetic activity is a perturbation upon that foundation.

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