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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。据估计，目前有超过90万块直径超过1厘米的碎片绕地球运行。与这些物体的碰撞会摧毁卫星仪器、子系统，甚至卫星本身。平均而言，美国战略司令部每天向用户发布约900条连接数据信息（提供预期脱手距离、估计碰撞概率、最接近时间、最接近相对位置和速度）。欧洲航天局目前估计，欧洲卫星运营商每年因碰撞和不必要的规避操作而遭受的经济损失超过2亿英镑。此外，随着天体数量每年增加约70,000个，碰撞将不可避免地增加，如果碎片达到临界密度，可能会发生被称为凯斯勒综合征的不受控制的级联碰撞。这有可能限制近地轨道的使用，并增加对所有航天飞行安全的担忧。因此，有两个主要问题：长期的空间活动的可持续性和短期的空间飞行的安全性。因此，不仅要减少近地轨道碎片物体的数量，而且要提高近距离脱靶预测的准确性，并能够及时有效地规划避碰机动。然而，一个主要问题是，由于上层大气对卫星的时变阻力影响，目前的轨道建模和预测不够准确。在近地轨道物体的轨道预测中，主要的未知因素是上层大气（热层）的密度，它会产生与时间和位置相关的阻力。考虑到热层密度每天可以变化80%，在太阳风暴期间可以变化250%，这是一个主要的建模挑战。用于预测轨道轨迹的现代模型是经验性的，可能导致很大的不确定性，相当于仅仅一天之后的位置误差达到千米。这些不准确性导致了不必要的卫星回避操作，给卫星运营商带来了巨大的成本。为了更好地预测轨道连接，需要一个低层和高层大气的完全耦合（中性和电离）模型，其中可以使用新颖的数学技术吸收广泛的测量数据。这种方法将提供电离层和热层的完整而准确的图像。我们的项目旨在确保英国气象局（以及更广泛的英国）在确定和预测热层方面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授予和合同的背景知识产权，探索新技术。在杠杆IP的情况下，我们预计所有模型将在拨款结束时达到TRL 6，新的研究将在最大努力的基础上进行。我们将受益于由该国一些主要专家组成的四机构联合体，从而实现我们的目标。该计划的大部分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、卫星运营商的应用的认识。