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Space Weather Instrumentation, Measurement, Modelling and Risk: Thermosphere (SWIMMR-T)

空间天气仪器、测量、建模和风险：热层 (SWIMMR-T)

基本信息

批准号：
NE/V00283X/1
负责人：
Adrian Grocott
金额：
$ 18.73万
依托单位：
Lancaster University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FV00283X%2F1
关键词：
Space Weather Instrumentation Measurement Modelling

项目摘要

Space debris is emerging as a key problem with the potential to cause major socio-economic impacts. It is currently estimated that there are over 900,000 pieces of debris greater than 1 cm orbiting the Earth. Collisions with such objects can destroy satellite instruments, subsystems and even the satellite itself. On average the United States Strategic Command issue ~900 Conjunction Data Messages (providing expected miss distance, estimated probability of collision, time of closest approach, and closest approach relative position and velocity) to users every day.The European Space Agency currently estimates that the economic loss to European satellite operators from collisions and unnecessary avoidance manoeuvres is in excess of £200 million per year. Moreover, with the number of objects (> 1 cm) increasing by ~70,000 per year, collisions will inevitably increase and if the debris reaches a critical density, an uncontrolled collision cascade known as the Kessler Syndrome is likely to occur. This has the potential to limit use of LEO and to increase concerns for the safety of all spaceflight. As such, there are two primary concerns: the sustainability of space activities over the longer-term, and the safety of spaceflight over the shorter-term. Therefore it is essential not only to reduce the number of debris objects in LEO, but also to improve the accuracy in predictions of near misses and to enable timely and efficient planning of collision avoidance manoeuvres. However, a major problem is that current orbit modelling and prediction is insufficiently accurate because of the time varying drag effect of the upper atmosphere on satellites. The dominant unknown in orbital trajectory predictions of LEO objects is the density of the upper atmosphere (thermosphere), which exerts a time and location dependent drag. Given that the thermospheric density can vary by 80% diurnally and by 250% during a solar storm this is a major modelling challenge. Contemporary models used to forecast orbit trajectories are empirical and can result in large uncertainties corresponding to positional errors of kilometres after just one day. These inaccuracies result in unnecessary satellite avoidance manoeuvres at great cost to satellite operators.In order to better predict orbital conjunctions a fully coupled (neutral and ionized) model of the lower and upper atmosphere is required into which a broad range of measurement data can be assimilated using novel mathematical techniques. This approach will provide a complete and accurate picture of the ionosphere and thermosphere.Our programme seeks to secure a step-change in the Met Office's (and more broadly the UK's) ability to specify and forecast the thermosphere. To achieve our objectives, we will leverage background IP from previous NERC, EPSRC, UKSA, ESA and Dstl grants and contracts and explore new techniques. In the case of the leveraged IP we expect that all models will be at TRL 6 by the grant end and new research will be on a best efforts basis. We will achieve our objectives by benefitting from a four-institution consortium of some of the country's principal experts. The majority of the programme will focus on environmental models, but while doing this we will maintain an awareness of the applications for these models, satellite operators.

空间碎片正在成为一个可能造成重大社会经济影响的关键问题。目前估计有90多万块大于1厘米的碎片绕地球运行。与这类物体的碰撞可能会摧毁卫星仪器、子系统，甚至卫星本身。美国战略司令部平均每天向用户发布约900条联合数据报文(提供预期脱靶量、预计碰撞概率、最近接近时间、最近接近相对位置和速度)。欧洲航天局目前估计，碰撞和不必要的避让演习每年给欧洲卫星运营商造成的经济损失超过2亿GB。此外，随着物体(&gt；1厘米)的数量以每年约70,000的速度增加，碰撞将不可避免地增加，如果碎片达到临界密度，很可能会发生被称为凯斯勒综合症的失控碰撞级联。这有可能限制LEO的使用，并增加对所有航天飞行安全的担忧。因此，有两个主要关切：较长期的空间活动的可持续性和较短期的空间飞行安全。因此，不仅必须减少近地轨道中碎片物体的数量，而且还必须提高预测近地未命中的准确性，并能够及时和有效地规划避碰演习。然而，一个主要的问题是，由于高层大气对卫星的时变阻力效应，目前的轨道建模和预测不够准确。在低轨天体轨道预测中，主要的未知数是高层大气(热层)的密度，它施加了与时间和位置有关的阻力。考虑到热层密度可以在一天中变化80%，在太阳风暴期间变化250%，这是一个重大的建模挑战。目前用于预测轨道轨迹的模型是经验性的，可能会在仅仅一天后导致相当于几公里的位置误差的巨大不确定性。为了更好地预测轨道连接，需要一个完全耦合的(中性和电离的)低层和高层大气模式，该模式可以利用新的数学技术将广泛的测量数据同化到其中。这种方法将提供电离层和热层的完整和准确的图像。我们的计划寻求确保气象局(更广泛地说是英国)指定和预报热层的能力发生阶段性变化。为了实现我们的目标，我们将利用以前NERC、EPSRC、UKSA、ESA和DSTL赠款和合同的背景知识产权，并探索新技术。在杠杆知识产权的情况下，我们预计所有模型将在赠款结束时达到TRL 6，并将尽最大努力进行新的研究。我们将通过受益于由该国一些主要专家组成的四个机构联合体来实现我们的目标。该方案的大部分内容将集中在环境模型上，但在这样做的同时，我们将保持对这些模型的应用的认识，即卫星运营商。