Satellite Radiation Risk Forecasts (Sat-Risk)

卫星辐射风险预测（Sat-Risk）

• 批准号: NE/V00249X/1
• 负责人: Richard Horne
• 金额: $ 206.42万
• 依托单位: British Antarctic Survey
• 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: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV00249X%2F1
• 关键词: Satellite; Radiation; Risk; Forecasts; Sat

SummaryOur society relies on satellites more than ever before, from the use of mobile phones to broadcasting and Earth observation. The use of GPS navigation, positioning and timing signals has grown considerably and we now use these signals in ways that were never foreseen, for example in agriculture and stock market trading. The modern world has also become more connected and built up dependencies that are no longer clearly identifiable. It is therefore essential that we take every reasonable precaution to ensure that satellites are protected.Space Weather poses one of the most important threats to satellites in orbit, primarily through radiation exposure. Radiation exposure can increase within a few minutes, by a ten thousand fold or more, and remain high for days, even months. For example, in 2003 during a large space weather event known as the Halloween storm radiation levels were highly disturbed and approximately 10% of the entire satellite fleet were affected by satellite anomalies (malfunctions) leading to service interruption and in one case the complete loss of a scientific satellite costing $640 million (Cannon et al., 2013). In 2012 the UK Government recognised the importance of space weather as a low frequency high impact event and included it on the National Risk Register (Cabinet Office, 2012). This was revised in 2017 with a recommendation for more investment into forecasting as a means of mitigating the impact. More recent research suggests that with current forecasting capability the loss of gross domestic product to the UK would be around £2.9 billion but with more investment in enhanced forecasting this could be reduced to £0.9 billion (Oughton et al., 2019). The purpose of this proposal is to provide enhanced forecasting to help reduce the impact on satellites. Currently there are over 2,200 operational satellites in orbit (December 2019).This proposal brings together scientists from across the UK with stakeholders from the UK Met Office. The goal is to develop a real-time system to forecast radiation exposure to satellites for a range of different orbits, and quantify the risk of damage or degradation. We will do this by taking research models of the Earth's radiation belts - regions of high energy electrons and protons trapped by the external geomagnetic field and which circulate around the Earth - and turn them into operational forecasting models. The models will use real-time data from ground and space to forecast radiation exposure up to 24 hours ahead for different orbits, including geostationary orbit, low Earth orbit and medium Earth orbit. It will also include data on radiation storms and cosmic rays. The particle radiation levels will then be used to calculate the damaging radiation effects on electronic components and solar arrays and compared to design guidelines to assess the risk of damage. The project will also include four research elements which are specifically targeted at reducing the uncertainty in the forecasts. The project will deliver a world leading forecasting capability for the Met Office that will help satellite operators take mitigating action, help satellite designers develop more resilient design and space insurance reduce the risk of loss. It will also support the growth of the satellite industry and the UK National Risk Register.1. Cannon, P, S., et al. (2013), Extreme Space Weather: Impacts on Engineered Systems and Infrastructure, Royal Academy of Engineering, London, SW1A 2WH.2. Cabinet Office, (2012), National risk register of civil emergencies, Whitehall, London SW1A 2WH, www.cabinetoffice.gov.uk3. Oughton et al., (2019), A Risk Assessment Framework for the Socioeconomic Impacts of Electricity Transmission Infrastructure Failure Due to Space Weather: An Application to the United Kingdom, Risk Analysis, https://doi.org/10.1111/risa.13229

从移动的电话到广播和地球观测，我们的社会比以往任何时候都更加依赖卫星。全球定位系统导航、定位和定时信号的使用已经大大增加，我们现在以前所未有的方式使用这些信号，例如在农业和股票市场交易中。现代世界也变得更加相互联系，并建立了不再明确可识别的依赖关系。因此，我们必须采取一切合理的预防措施，以确保卫星得到保护。空间天气对轨道上的卫星构成最重要的威胁之一，主要是通过辐射照射。辐射暴露可以在几分钟内增加一万倍或更多，并保持高水平数天，甚至数月。例如，2003年，在一次被称为万圣节风暴的大型空间天气事件期间，辐射水平受到严重干扰，整个卫星群中约有10%受到卫星异常（故障）的影响，导致服务中断，在一次情况下，一颗科学卫星完全损失，损失6.4亿美元（Cannon等人，2013年）。2012年，联合王国政府认识到空间气象作为一种低频高影响事件的重要性，并将其列入国家风险登记册（内阁办公室，2012年）。2017年对这一点进行了修订，建议增加对预测的投资，以减轻影响。最近的研究表明，以目前的预测能力，英国的国内生产总值损失将约为29亿英镑，但随着对增强预测的更多投资，这一损失可能会减少到9亿英镑（Oughton等人，2019年）。这项建议的目的是提供更好的预报，以帮助减少对卫星的影响。目前有超过2，200颗在轨运行的卫星（2019年12月）。该提案汇集了来自英国各地的科学家与英国气象局的利益相关者。其目标是开发一个实时系统，以预测不同轨道的卫星受到的辐射，并量化损坏或退化的风险。为此，我们将采用地球辐射带的研究模型-被外部地磁场捕获并围绕地球循环的高能电子和质子区域-并将其转化为业务预测模型。这些模型将使用来自地面和空间的实时数据，预测不同轨道（包括地球静止轨道、低地球轨道和中地球轨道）未来24小时的辐射暴露。它还将包括关于辐射风暴和宇宙射线的数据。粒子辐射水平将用于计算电子元件和太阳能电池阵列的破坏性辐射影响，并与设计准则进行比较，以评估损坏风险。该项目还将包括四项研究内容，专门针对减少预测中的不确定性。该项目将为英国气象局提供世界领先的预报能力，帮助卫星运营商采取缓解措施，帮助卫星设计师开发更具弹性的设计和太空保险，降低损失风险。它还将支持卫星产业和英国国家风险登记册的发展。1.坎农，P，S.，等（2013），极端空间天气：对工程系统和基础设施的影响，皇家工程学院，伦敦，SW 1A 2WH.2。内阁办公室，（2012年），国家民事紧急情况风险登记册，白厅，伦敦SW 1A 2 WH，www.cabinetoffice.gov.uk3。Oughton等人，（2019），空间天气导致输电基础设施故障的社会经济影响的风险评估框架：对英国的应用，风险分析，https://doi.org/10.1111/risa.13229

项目成果

Active Precipitation of Radiation Belt Electrons Using Rocket Exhaust Driven Amplification (REDA) of Man-Made Whistlers.

使用火箭排气驱动的放大（REDA）的辐射带电子的主动沉淀。

• DOI: 10.1029/2022ja030358
• 发表时间: 2022-06
• 期刊: JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS
• 影响因子: 2.8
• 作者: Bernhardt, P. A.;Hua, M.;Bortnik, J.;Ma, Q.;Verronen, P. T.;McCarthy, M. P.;Hampton, D. L.;Golkowski, M.;Cohen, M. B.;Richardson, D. K.;Howarth, A. D.;James, H. G.;Meredith, N. P.
• 通讯作者: Meredith, N. P.

Electron Microbursts Induced by Nonducted Chorus Waves

• DOI: 10.3389/fspas.2021.745927
• 发表时间: 2021-10
• 作者: Lunjin Chen;Xiao‐jia Zhang;A. Artemyev;Liheng Zheng;Z. Xia;A. Breneman;R. Horne

Forecasting Extreme Ultraviolet Thermospheric Drivers from Solar Imaging using Deep Learning

使用深度学习从太阳成像预测极端紫外线热层驱动因素

• DOI: 10.22541/essoar.168500301.13213549/v1
• 发表时间: 2023
• 作者: Brown E

Passing the Alfven Layer by Means of Chorus Acceleration

通过合唱加速通过阿尔芬层

• DOI: 10.1002/essoar.10510991.1
• 发表时间: 2022
• 作者: Allison H

Variations in Observations of Geosynchronous Magnetopause and Last Closed Drift Shell Crossings With Magnetic Local Time

地球同步磁层顶和最后闭合漂移壳穿越的观测随磁本地时的变化

• DOI: 10.1029/2022sw003105
• 发表时间: 2022
• 期刊: Space Weather
• 影响因子: 3.7
• 作者: Daggitt T