Development of Space Weather Reasonable Worst‐Case Scenarios for the UK National Risk Assessment

Hapgood, M. A.; Angling, Matthew; Attrill, G. D. R.; Bisi, M. M.; Cannon, Paul S.; Dyer, C. S.; Eastwood, J. P.; Elvidge, Sean; Gibbs, Mark; Harrison, R. A.; Hord, Colin; Horne, Richard B.; Jackson, D. R.; Jones, Bryn; Machin, Simon; Mitchell, Cathryn N.; Preston, John; Rees, John; Rogers, Neil; Routledge, Graham; Ryden, Keith; Tanner, Rick; Thomson, Alan; Wild, J. A.; Willis, M.J.

doi:10.1029/2020sw002593

Cited by 58 publications

(44 citation statements)

References 192 publications

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“…Previous reviews on extreme events have been published by Riley (2012), , Hudson (2015Hudson ( , 2021, Riley et al (2018), Gopalswamy (2018) and Hapgood et al (2021). Here, in addition to the phenomena of solar flares, CMEs, geomagnetic storms, and low-energy proton events, we consider sunspot groups, flares on Sun-like stars, solar radio bursts, fast transit interplanetary coronal mass ejections (ICMEs), low-latitude aurorae, and high-energy proton events that give rise to cosmogenic nuclide enhancements-topics that were not included or were more lightly treated in the reviews of extreme events listed above.…”

Section: Related Workmentioning

confidence: 99%

Extreme solar events

Cliver

Schrijver

Shibata

et al. 2022

Living Rev Sol Phys

103

100

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We trace the evolution of research on extreme solar and solar-terrestrial events from the 1859 Carrington event to the rapid development of the last twenty years. Our focus is on the largest observed/inferred/theoretical cases of sunspot groups, flares on the Sun and Sun-like stars, coronal mass ejections, solar proton events, and geomagnetic storms. The reviewed studies are based on modern observations, historical or long-term data including the auroral and cosmogenic radionuclide record, and Kepler observations of Sun-like stars. We compile a table of 100- and 1000-year events based on occurrence frequency distributions for the space weather phenomena listed above. Questions considered include the Sun-like nature of superflare stars and the existence of impactful but unpredictable solar "black swans" and extreme "dragon king" solar phenomena that can involve different physics from that operating in events which are merely large.

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Section: Related Workmentioning

confidence: 99%

Extreme solar events

Cliver

Schrijver

Shibata

et al. 2022

Living Rev Sol Phys

103

100

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“…Magnetospheric convection electric field (E M ) is a key parameter in all existing theories when it comes to the mechanism of magnetic disturbances in the upper atmosphere. These disturbances, more intense via the solar flux at high speed, can have a possible impact on human health (Schwenn, 2006;Belisheva, 2019;Abdullrahman and Marwa, 2020;Hapgood et al, 2021) as well as technological systems (satellites, planes, telecommunications, etc).…”

Section: Introductionmentioning

confidence: 99%

Variability of the magnetospheric electric field due to high-speed solar wind convection from 1964 to 2009

Gnanou¹,

Zoundi²,

Salfo³

et al. 2022

Afr. J. Environ. Sci. Technol.

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Focusing on the classification of solar winds into three types of flux: (1) slow winds, (2) fluctuating winds, and (3) high speed-solar winds HSSW (V ≥ 450 km/s on average day), the influence of the convection electric field (E M ) via the flow of HSSWs during storms in the internal magnetosphere and on the stability of magnetospheric plasma at high latitudes was investigated. The study involved 1964-2009 period, which encompasses solar cycles 20, 21, 22 and 23. The results show a weak correlation of the frozen electric field profiles with the HSSWs overall solar cycles and a very large number of HSSWs recorded in cycle 23. Particular attention has been paid to solar cycle 22 which rather presents a fairly disturbed profile with sudden variations in solar flux and E M field; however, solar cycle 21 records the lowest level of HSSW.Overall, over all the studied solar cycles, it can be seen that the E M field from HSSWs of very low intensity increases progressively from solar cycle 20 to cycle 23, respectively with a minimum occurrence of 8.48% and a maximum of 9.36%. The results reached show, on one hand, that the magnetosphere is very stable from 15:00UT to 21:00UT, and on the other hand, that there is a significant transfer of mass in the night sector (21:00UT-24:00UT) than on the day side (00:00UT-15:00UT) for all solar cycles over the long period of 45 years.

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“…

Coronal Mass Ejections (CMEs) are eruptions of magnetised plasma from the Sun's atmosphere, which then propagate outward through the heliosphere and solar wind (Webb & Howard, 2012). CMEs play a central role in the evolution of the Sun's magnetic field and the heliosphere (Owens & Forsyth, 2013), and they are also the main driver of severe space weather throughout the solar system, but particularly at Earth (Cannon et al, 2013;Hapgood et al, 2020). Consequently the study of CMEs is important from both the space science and space weather perspectives (Editors, 2021).For example, effective space-weather forecasting requires the observation and modeling of the evolution of CMEs, to predict not only CME arrival times at Earth, but also CME properties such as arrival speed (Owens, Lockwood, & Barnard, 2020).

…”

mentioning

confidence: 99%

Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data

et al. 2022

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Geometric modeling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modeling, such as ELEvoHI, are being developed into forecast tools for space weather prediction. These models assume that solar wind structure does not affect the evolution of the CME, which is an unquantified source of uncertainty. We use a large number of Cone CME simulations with the HUXt solar wind model to quantify the scale of uncertainty introduced into geometric modeling and the ELEvoHI CME arrival times by solar wind structure. We produce a database of simulations, representing an average, a fast, and an extreme CME scenario, each independently propagating through 100 different ambient solar wind environments. Synthetic heliospheric imager observations of these simulations are then used with a range of geometric models to estimate the CME kinematics. The errors of geometric modeling depend on the location of the observer, but do not seem to depend on the CME scenario. In general, geometric models are biased towards predicting CME apex distances that are larger than the true value. For these CME scenarios, geometric modeling errors are minimised for an observer in the L5 region. Furthermore, geometric modeling errors increase with the level of solar wind structure in the path of the CME. The ELEvoHI arrival time errors are minimised for an observer in the L5 region, with mean absolute arrival time errors of 8.2 ± 1.2 h, 8.3 ± 1.0 h, and 5.8 ± 0.9 h for the average, fast, and extreme CME scenarios.

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Development of Space Weather Reasonable Worst‐Case Scenarios for the UK National Risk Assessment

Cited by 58 publications

References 192 publications

Extreme solar events

Extreme solar events

Variability of the magnetospheric electric field due to high-speed solar wind convection from 1964 to 2009

Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data

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