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Modern civilization relies on a complex, globally interconnected industrial agriculture system to produce food. Its unprecedented yields hinge on external inputs like machinery, fertilizers, and pesticides, rendering it vulnerable to disruptions in production and international trade. Such a disruption could be caused by large‐scale damage to the electrical grid. Solar storms, nuclear detonations in the upper atmosphere, pandemics, or cyber‐attacks, could cause this severe damage to electrical infrastructure. To assess the impact of such a global catastrophic infrastructure loss on major food crops (corn, rice, soybean, wheat), we employ a generalized linear model. The predictions show a crop‐specific yield reduction between 15% and 37% in phase 1, the year after the catastrophe, assuming rationed use of fertilizers, pesticides, and fuel stocks. In phase 2, when all stocks are depleted, yields decrease by 35%–48%. Soybean is less affected in phase 1, while all crops experience strong declines in phase 2. Europe, North and South America, and parts of India, China, and Indonesia face major yield reductions, potentially up to 75%, while most African countries are less affected. These findings underscore the necessity for preparation by highlighting the vulnerability of the food system. [ABSTRACT FROM AUTHOR]

Abstract Modern civilization relies on a complex, globally interconnected industrial agriculture system to produce food. Its unprecedented yields hinge on external inputs like machinery, fertilizers, and pesticides, rendering it vulnerable to disruptions in production and international trade. Such a disruption could be caused by large‐scale damage to the electrical grid. Solar storms, nuclear detonations in the upper atmosphere, pandemics, or cyber‐attacks, could cause this severe damage to electrical infrastructure. To assess the impact of such a global catastrophic infrastructure loss on major food crops (corn, rice, soybean, wheat), we employ a generalized linear model. The predictions show a crop‐specific yield reduction between 15% and 37% in phase 1, the year after the catastrophe, assuming rationed use of fertilizers, pesticides, and fuel stocks. In phase 2, when all stocks are depleted, yields decrease by 35%–48%. Soybean is less affected in phase 1, while all crops experience strong declines in phase 2. Europe, North and South America, and parts of India, China, and Indonesia face major yield reductions, potentially up to 75%, while most African countries are less affected. These findings underscore the necessity for preparation by highlighting the vulnerability of the food system.

The recent superstorm of 2024 May 10–11 is the second largest geomagnetic storm in the space age and the only one that has simultaneous interplanetary data (there were no interplanetary data for the 1989 March storm). The May superstorm was characterized by a sudden impulse (SI ^+ ) amplitude of +88 nT, followed by a three-step storm main-phase development, which had a total duration of ∼9 hr. The cause of the first storm main phase with a peak SYM-H intensity of −183 nT was a fast-forward interplanetary shock (magnetosonic Mach number M _ms ∼ 7.2) and an interplanetary sheath with a southward interplanetary magnetic field component B _s of ∼40 nT. The cause of the second storm's main phase with an SYM-H intensity of −354 nT was a deepening of the sheath B _s to ∼43 nT. A magnetosonic wave ( M _ms ∼ 0.6) compressed the sheath to a high magnetic field strength of ∼71 nT. Intensified B _s of ∼48 nT were the cause of the third and most intense storm main phase, with an SYM-H intensity of −518 nT. Three magnetic cloud events with B _s fields of ∼25–40 nT occurred in the storm recovery phase, lengthening the recovery to ∼2.8 days. At geosynchronous orbit, ∼76 keV to ∼1.5 MeV electrons exhibited ∼1–3 orders of magnitude flux decreases following the shock/sheath impingement onto the magnetosphere. The cosmic-ray decreases at Dome C, Antarctica (effective vertical cutoff rigidity

The prediction of solar energetic particle (SEP) events garners increasing interest as space missions extend beyond Earth’s protective magnetosphere. These events, which are, in most cases, products of magnetic-reconnection-driven processes during solar flares or fast coronal-mass-ejection-driven shock waves, pose significant radiation hazards to aviation, space-based electronics, and particularly space exploration. In this work, we utilize the recently developed data set that combines the Solar Dynamics Observatory/Space-weather Helioseismic and Magnetic Imager Active Region Patches and the Solar and Heliospheric Observatory/Space-weather Michelson Doppler Imager Active Region Patches. We employ a suite of machine learning strategies, including support vector machines (SVMs) and regression models, to evaluate the predictive potential of this new data product for a forecast of post-solar flare SEP events. Our study indicates that despite the augmented volume of data, the prediction accuracy reaches 0.7 ± 0.1 (experimental setting), which aligns with but does not exceed these published benchmarks. A linear SVM model with training and testing configurations that mimic an operational setting (positive–negative imbalance) reveals a slight increase (+0.04 ± 0.05) in the accuracy of a 14 hr SEP forecast compared to previous studies. This outcome emphasizes the imperative for more sophisticated, physics-informed models to better understand the underlying processes leading to SEP events.

This study investigates the impact of spacecraft positioning and trajectory on in situ signatures of coronal mass ejections (CMEs). Employing the 3DCORE model, a 3D flux rope model that can generate in situ profiles for any given point in space and time, we conduct forward modeling to analyze such signatures for various latitudinal and longitudinal positions, with respect to the flux rope apex, at 0.8 au. Using this approach, we explore the appearance of the resulting in situ profiles for different flux rope types, with different handedness and inclination angles, for both high- and low-twist CMEs. Our findings reveal that CMEs exhibit distinct differences in signatures between apex hits and flank encounters, with the latter displaying elongated profiles with reduced rotation. Notably, constant, nonrotating in situ signatures are only observed for flank encounters of low-twist CMEs, suggesting the existence of untwisted magnetic field lines within CME legs. Additionally, our study confirms the unambiguous appearance of different flux rope types in in situ signatures in all of the cases, barring some indistinguishable cases, contributing to the broader understanding and interpretation of observational data. Given the model assumptions, this may refute trajectory effects as the cause for mismatching flux rope types as identified in solar signatures. While acknowledging limitations inherent in our model, such as the assumption of constant twist and a nondeformable torus-like shape, we still draw relevant conclusions within the context of the global magnetic field structures of CMEs and the potential for distinguishing flux rope types based on in situ observations.

It is under debate whether the magnetic field in the solar atmosphere carries neutralized electric currents, in particular, whether a magnetic flux rope (MFR), which is considered the core structure of coronal mass ejections, carries neutralized electric currents. Recently Wang et al. (2023) studied magnetic flux and electric current measured at the footpoints of 28 eruptive MFRs from 2010 to 2015. Because of the small sample size, no rigorous statistical analysis has been done. Here, we include nine more events from 2016 to 2023 and perform a series of nonparametric statistical tests at a significance level of 5%. The tests confirm that there exist no significant differences in magnetic properties between conjugated footpoints of the same MFR, which justifies the method of identifying the MFR footpoints through coronal dimming. The tests demonstrate that there exist no significant differences between MFRs with preeruption dimming and those with only posteruption dimming. However, there is a medium level of association between MFRs carrying substantial net current and those producing preeruption dimming, which can be understood by the Lorentz self-force of the current channel. The tests also suggest that in estimating the magnetic twist of MFRs, it is necessary to take into account the spatially inhomogeneous distribution of electric current density and magnetic field.

Magnetospheric relativistic electrons are accelerated during substorms and strong convection events that occur during high-intensity long-duration continuous auroral electrojet activity (HILDCAA) events, associated with solar wind high-speed streams (coming from coronal holes). From an analysis of ∼2–20 MeV electrons at L ∼ 2–7 measured by the Van Allen Probe satellite, it is shown that ∼3.4–4.1 days long HILDCAA events are characterized by ∼7.2 MeV electron acceleration in the L ∼ 4.0–6.0 region, which occurs ∼2.9–3.4 days after the onset of HILDCAA. The dominant acceleration process is due to wave–particle interactions between magnetospheric electromagnetic chorus waves and substorm-injected ∼100 keV electrons. The longer the HILDCAA and chorus last, the higher the maximum energy of the accelerated relativistic electrons. The acceleration to higher and higher energies is due to a bootstrap mechanism.

Powerful solar storms emit plasma that may travel towards the earth. Interactions between the plasma and the earth magnetic field cause geomagnetic disturbances (GMDs), which in turn induce quasi-dc voltage along long conductors in power systems. The induced electric field can be calculated by magnetic field data measured by magnetometers at several stations. In this paper, a set of online processing methods are proposed to improve signal to noise ratio (SNR) of the calculated electric field signals. In the first step, magnetic field signals are denoised inside a sliding window by a wavelet transform. The sliding window width is optimized and the introduced transients are compensated. Time derivative of magnetic field signals are estimated by a continuous wavelet transform in the next step, and the size of the sliding window is minimized for optimal computational speed. Ultimately, a method is proposed to further enhance the SNR by updating the previously processed data points. The magnetic and electric field signals obtained by the online and offline processing methods are compared with each other. It is demonstrated that the online processing methods can decrease the noises to a level comparable to that obtained by the offline methods. The results of this study can be implemented to protect key elements of power systems against severe solar storms. [ABSTRACT FROM AUTHOR]

The Carrington flare in 1859 September is a benchmark, as the earliest reported solar flare and as an event with one of the greatest terrestrial impacts. To date, no rigorous estimate of the energy of this flare has been made on the basis of the only direct observation available, its white-light emission. Here, we exploit the historical observations to obtain a magnitude estimate and express it in terms of its GOES soft X-ray class. From Carrington’s original drawings, we estimated the area of the white-light flaring region to be 116 ± 25 msh. Carrington’s account allows us to estimate the flare blackbody brightness temperature as ≈8800–10,900 K, given the most plausible interpretation of the reported flare brightness. This leads to an unprecedented class estimate of ≈X80 (X46–X126), on the modern revised GOES scale (a factor 1.43 higher than the traditional one). This substantially exceeds earlier estimates but is based on an explicit interpretation of Carrington’s description. We also describe an alternative but less plausible estimation of the flare brightness, as adopted previously, to obtain a class estimate of ≈X14 (X9–X19). This now-deprecated scenario gives an estimate similar to that of with those of directly observed modern great flares. Approximations with “equivalent area,” based on the Hinode observations, lead to comparable magnitudes and approve our estimates, though with a larger uncertainty range. We note that our preferred estimate is higher than the currently used value of X64.4 ± 7.2 (revised) based on indirect geomagnetic measurements.

Abstract Extreme solar storms, high-altitude electromagnetic pulses, and coordinated cyber attacks could disrupt regional/global electricity. Since electricity basically drives industry, industrial civilization could collapse without it. This could cause anthropological civilization (cities) to collapse, from which humanity might not recover, having long-term consequences. Previous work analyzed technical solutions to save nearly everyone despite industrial loss globally, including transition to animals powering farming and transportation. The present work estimates cost-effectiveness for the long-term future with a Monte Carlo (probabilistic) model. Model 1, partly based on a poll of Effective Altruism conference participants, finds a confidence that industrial loss preparation is more cost-effective than artificial general intelligence safety of ~ 88% and ~ 99+% for the 30 millionth dollar spent on industrial loss interventions and the margin now, respectively. Model 2 populated by one of the authors produces ~ 50% and ~ 99% confidence, respectively. These confidences are likely to be reduced by model and theory uncertainty, but the conclusion of industrial loss interventions being more cost-effective was robust to changing the most important 4–7 variables simultaneously to their pessimistic ends. Both cause areas save expected lives cheaply in the present generation and funding to preparation for industrial loss is particularly urgent.

We investigate whether global toroid patterns and the local magnetic field topology of solar active region (AR) 12673 together can hindcast the occurrence of the biggest X-flares of solar cycle (SC)-24. Magnetic toroid patterns (narrow latitude belts warped in longitude, in which ARs are tightly bound) derived from the surface distributions of ARs, prior and during AR 12673 emergence, reveal that the portions of the south toroid containing AR 12673 was not tipped away from its north-toroid counterpart at that longitude, unlike the 2003 Halloween storms scenario. During the minimum phase there were too few emergences to determine multimode longitudinal toroid patterns. A new emergence within AR 12673 produced a complex nonpotential structure, which led to the rapid buildup of helicity and winding that triggered the biggest X-flare of SC-24, suggesting that this minimum-phase storm can be anticipated several hours before its occurrence. However, global patterns and local dynamics for a peak-phase storm, such as that from AR 11263, behaved like the 2003 Halloween storms, producing the third biggest X-flare of SC-24. AR 11263 was present at the longitude where the north and south toroids tipped away from each other. While global toroid patterns indicate that prestorm features can be forecast with a lead time of a few months, their application to observational data can be complicated by complex interactions with turbulent flows. Complex nonpotential field structure development hours before the storm are necessary for short-term prediction. We infer that minimum-phase storms cannot be forecast accurately more than a few hours ahead, while flare-prone ARs in the peak phase may be anticipated much earlier, possibly months ahead from global toroid patterns.

Gradual solar proton events are thought to consist of solar components originating near the Sun and interplanetary components associated with interplanetary shocks, and the role of interplanetary shocks is considered to be crucial in supplying particles to regions that are not magnetically connected to the solar source region. We calculate the ratios of the peak intensities for the four energy channels (13–16, 20–25, 32–40, and 40–64 MeV) and compare the ratios observed by multiple spacecraft at different locations. We often find that the ratio of peak intensities observed at different locations in the same event remains almost constant as the energy varies. In other words, the ratio of peak intensities from the different energy channels remains almost constant as the position of the spacecraft changes. The phenomenon implies that in many gradual events, energetic particles observed at different locations are mainly composed of solar components that undergo perpendicular diffusion in both the vicinity of the Sun and the interplanetary space, and that perpendicular diffusion is the main factor enabling energetic particles to be observed in regions without magnetic connection to the solar source region.

Multiple neural network architectures, with different structural composition and complexity, are implemented in this study with the aim of providing multi-hour-ahead warnings of severe geomagnetic disturbances, based on in situ measurements of the solar wind plasma and magnetic field acquired at the Lagrangian point L1. First, a statistical analysis of the interplanetary data was performed to point out which are the most relevant parameters to be provided as input to the neural networks, and a preprocessing of the data set was implemented to face its heavy imbalance (the Earth’s magnetosphere is in fact mostly at rest). Then, neural networks were tested to evaluate their performance. It turned out that, in a binary classification problem, recurrent approaches are best at predicting critical events both 1 and 8 hr in advance, achieving a balanced accuracy of 94% and 70%, respectively. Finally, in an attempt at multistep prediction of the criticality of future geomagnetic events from 1–8 hr ahead, more complex neural networks, built by merging the different types of basic convolutional and recurrent architectures, have been shown to outperform single-step and state-of-the-art approaches with a balanced accuracy of at least 70%. Interestingly, the accuracy peaks at 4 hr, corresponding to the waiting time between the detection of solar drivers at L1 and the onset of the geomagnetic storm (as previously obtained by statistical investigations), suggesting that on average this is the time the Earth’s magnetosphere takes to react to the solar event.

Extreme solar storms, high-altitude electromagnetic pulses, and coordinated cyber attacks could disrupt regional/global electricity. Since electricity basically drives industry, industrial civilization could collapse without it. This could cause anthropological civilization (cities) to collapse, from which humanity might not recover, having long-term consequences. Previous work analyzed technical solutions to save nearly everyone despite industrial loss globally, including transition to animals powering farming and transportation. The present work estimates cost-effectiveness for the long-term future with a Monte Carlo (probabilistic) model. Model 1, partly based on a poll of Effective Altruism conference participants, finds a confidence that industrial loss preparation is more cost-effective than artificial general intelligence safety of ~ 88% and ~ 99+% for the 30 millionth dollar spent on industrial loss interventions and the margin now, respectively. Model 2 populated by one of the authors produces ~ 50% and ~ 99% confidence, respectively. These confidences are likely to be reduced by model and theory uncertainty, but the conclusion of industrial loss interventions being more cost-effective was robust to changing the most important 4–7 variables simultaneously to their pessimistic ends. Both cause areas save expected lives cheaply in the present generation and funding to preparation for industrial loss is particularly urgent. [ABSTRACT FROM AUTHOR]

Under nominal solar wind conditions, a tenuous wake forms downstream of the lunar nightside. However, the lunar plasma environment undergoes a transformation as the Moon passes through the Earth's magnetotail, with hot subsonic plasma causing the wake structure to disappear. We investigate the lunar wake response during a passing coronal mass ejection (CME) on March 8, 2012 while crossing the Earth's magnetotail using both a magnetohydrodynamic (MHD) model of the terrestrial magnetosphere and a three‐dimensional hybrid plasma model of the lunar wake. The CME arrives at 1 AU around 10:30 UT and its impact is first detected inside the geomagnetic tail after 11:10 UT by the Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon's Interaction with the Sun (THEMIS‐ARTEMIS) satellites in lunar orbit. A global magnetospheric MHD simulation using Wind data for upstream conditions with the OpenGGCM model reveals the magnetosheath compression to the lunar position from 11:20–12:00 UT, accompanied by multiple flux rope or plasmoid‐like features developing and propagating tailward. MHD results support plasma changes observed by the THEMIS‐ARTEMIS satellites. Lunar‐scale simulations using the Amitis hybrid code show a short and misaligned plasma wake during the Moon's brief entry into the magnetosheath at 11:20 UT, with plasma expansion into the void being aided by the higher plasma temperatures. Sharply accelerated flow speed and a compressed magnetic field lead to an enhanced electric field in the lunar wake capable of generating sudden changes to the nightside near‐surface electric potential.Key Points: Passing coronal mass ejection (CME) during a Full Moon distorts the magnetopause and magnetosheath, resulting in the Moon's removal from the geomagnetic tailCME arrival results in the redevelopment of a short optically misaligned lunar plasma wakeEvent conditions are favorable for the development of flux‐rope like plasmoids in the magnetotail capable of being detected at the Moon [ABSTRACT FROM AUTHOR]

We present a solar‐centric approach to estimating the probability of extreme coronal mass ejections (CME) using the Solar and Heliospheric Observatory (SOHO)/Large Angle and Spectrometric Coronagraph Experiment (LASCO) CME Catalog observations updated through May 2018 and an updated list of near‐Earth interplanetary coronal mass ejections (ICME). We examine robust statistical approaches to the estimation of extreme events. We then assume a variety of time‐independent distributions fitting, and then comparing, the different probability distributions to the relevant regions of the cumulative distributions of the observed CME speeds. Using these results, we then obtain the probability that the velocity of a CME exceeds a particular threshold by extrapolation. We conclude that about 1.72% of the CMEs recorded with SOHO LASCO arrive at the Earth over the time both data sets overlap (November 1996 to September 2017). Then, assuming that 1.72% of all CMEs pass the Earth, we can obtain a first‐order estimate of the probability of an extreme space weather event on Earth. To estimate the probability over the next decade of a CME, we fit a Poisson distribution to the complementary cumulative distribution function. We inferred a decadal probability of between 0.01 and 0.09 for an event of at least the size of the large 2012 event, and a probability between 0.0002 and 0.016 for the size of the 1859 Carrington event. [ABSTRACT FROM AUTHOR]

Few studies have collected and analyzed the astronomical events recorded in Arabic literature. In this paper, we present some additional events reported in four Arabic historical sources that could be classified as an aurora. These observations occurred from 9th to 20th century and cover a large geographic area: North Africa, Arabian-Peninsula and Middle-East. Some of them were observed at very low geomagnetic latitude, such as the event seen in Yemen in AD 1919 that can be considered as one of the lowest latitude auroras ever documented by Arabic scholars. In the same Yemenite source, the author describes a twilight phenomenon of 1883 October 03–November 01 which can be considered as an atmospheric-optical phenomenon arising from the major explosive eruptions of Krakatoa in 1883 August 26–27. We also noticed that one of the events which was seen for 7 days coincide probably with the prolonged manifestation of auroras of 1870 September 24–25. Including published records, we compiled a so far most complete catalog of potential auroral candidates in the Arabic sources. This data set can be used in order to study the solar activity variations and magnetic storms in the historical past. One of the interesting auroras was seen in Mecca (∼ 17 ∘ MLAT) in 1872 February 04. This event is further evidence for the equatorward extension of auroral display and the planetary consequences of the great geomagnetic storm of 1872. Finally, it should be underlined that no aurora observations were recorded during the Maunder minimum (MM). [ABSTRACT FROM AUTHOR]

Modern civilization relies on a complex, globally interconnected industrial agriculture system to produce food. Its unprecedented yields hinge on external inputs like machinery, fertilizers, and pesticides, rendering it vulnerable to disruptions in production and international trade. Such a disruption could be caused by large-scale damage to the electrical grid. Solar storms, nuclear detonations in the upper atmosphere, pandemics, or cyber-attacks, could cause this severe damage to electrical infrastructure. To assess the impact of such a global catastrophic infrastructure loss on major food crops (corn, rice, soybean, wheat), we employ a generalized linear model. The predictions show a crop-specific yield reduction between 15% and 37% in phase 1, the year after the catastrophe, assuming rationed use of fertilizers, pesticides, and fuel stocks. In phase 2, when all stocks are depleted, yields decrease by 35%-48%. Soybean is less affected in phase 1, while all crops experience strong declines in phase 2. Europe, North and South America, and parts of India, China, and Indonesia face major yield reductions, potentially up to 75%, while most African countries are less affected. These findings underscore the necessity for preparation by highlighting the vulnerability of the food system., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors. Global Challenges published by Wiley‐VCH GmbH.)

Transmission system operators are responsible for security and reliability of their grid. An important topic is the analysis of possible risks for the transmission system network.The paper presents actual results about geomagnetically induced currents (GIC) in the Austrian transmission system. Because of problems with unexpected noise at some transformers, investigations were started, which gave an indication that DC could be the source of this noise. Due to the particular geological structure of the country, the influence of GIC in Austria is higher than for the most other countries in Central Europe. A simulation model to compute GIC was set up and compared to the measured DC transformer neutral current. The comparison of the simulated and measured currents shows a good correlation. High geomagnetic disturbances, which lead to high currents according the simulation model, can be confirmed by the measurement. Differences between measurement and simulation can be seen in the region of "fast" fluctuation within seconds. By detailed analysis of the times of occurrence it was shown, that currents from underground railway, which are operating with DC, flow through the transmission grid, too. [ABSTRACT FROM AUTHOR]

A number of catastrophes could block the sun, including asteroid/comet impact, super volcanic eruption, and nuclear war with the burning of cities (nuclear winter). The problem of feeding 7 billion people would arise (the food problem is more severe than other problems associated with these catastrophes). Previous work has shown this is possible converting stored biomass to food if industry is present. A number of risks could destroy electricity globally, including a series of high-altitude electromagnetic pulses (HEMPs) caused by nuclear weapons, an extreme solar storm, and a super computer virus. Since industry depends on electricity, it is likely there would be a collapse of the functioning of industry and machines. Additional previous work has shown that it is technically feasible to feed everyone given the loss of industry without the loss of the sun. It is possible that one of these sun-blocking scenarios could occur near in time to one of these industry-disabling scenarios. This study analyzes food sources in these combined catastrophe scenarios. Food sources include extracting edible calories from killed leaves, growing mushrooms on leaves and dead trees, and feeding the residue to cellulose-digesting animals such as cattle and rabbits. Since the sun is unlikely to be completely blocked, fishing and growing ultraviolet (UV) and cold-tolerant crops in the tropics could be possible. The results of this study show these solutions could enable the feeding of everyone given minimal preparation, and this preparation should be a high priority now. [ABSTRACT FROM AUTHOR]

The article examines the problem of saturation and failure of power transformers under geomagnetically induced currents and currents of the E3 component of high-altitude nuclear explosions. It also describes a special protective relay reacting on DC component in the transformer neutral current.

Telesat Canada is a satellite communications firm, founded in 1969, that provides global broadcast and broadband services. Its fleet of satellites includes the geostationary Anik line. On January 20, 1994, a major solar storm knocked out communications on two Anik satellites. Anik E1 was recovered through a backup system within hours. However, Anik E2 was non-operational until June 1994, when engineers used an innovative ground fix to regain control. [ABSTRACT FROM AUTHOR]

Positioning using a satellite requires defining the instantaneous positions of navigation satellites. The established positions are predicted and transmitted to the users applying satellites, and, however become degraded with accuracy in cases solar events divert the satellites from their path. Meanwhile, getting satellite coordinates with reference to the made predictions involves computing effort. The question addressed in this paper is whether orbit disturbances can be detected by examining these predictions so that computing coordinates are avoided. The paper argues that detection is possible but requires further experiments on confirmation due to the fact there have been relatively few solar storms in recent years while collecting data on satellite tracking. also, the paper also suggests that detection by examining orbital parameters is of a limited practical value when compared with the ease of interpreting satellite coordinates measured in meters. Santrauka Padėtį nustatant globaline padėties nustatymo sistema turi būti žinomos akimirkinės dirbtinių Žemės palydovų padėtys orbitoje, tačiau dėl Saulės reiškinių įtakos dirbtiniai Žemės palydovai nukrypsta nuo jų judėjimo kelio. Išanalizavus teigiama, kad tiriant pasirinktuoju metodu galima nustatyti dirbtinių Žemės palydovų nukrypimus nuo įprastinės orbitos bei numatyti prognozes. Šiems teiginiams patvirtinti būtini tolesni eksperimentai. Резюме Для того, чтобы было известно мгновенное положение искусственных спутников Земли на орбите, требуется определение позиции с помощью системы глобального позиционирования. Однако точность позиций спутников на орбите уменьшается из-за событий на Солнце, вследствие чего искусственные спутники Земли отклоняются от пути их движения. В статье рассматривается вопрос, можно ли обнаружить погрешности на орбите искусственных спутников Земли и предвидеть прогнозы на основании выбранного метода. Утверждается, что изменения обнаружить можно, однако для подтверждения этого требуются дальнейшие эксперименты. Reikšminiai žodžiai: GPS palydovas, Keplerio orbita, navigacinis pranešimas, Saulės aktyvumas, Saulės audra, erdvės oro sąlygos Ключевые слова: искусственный спутник, орбита Кеплера, навигационное сообщение, активность Солнца, солнечная буря, условия воздушного пространства

With the approaching of the 24th solar cycle peak year (2012-2014), the impacts of super solar storms on the geospace environment have drawn attentions. Based on the geomagnetic field observations during Carrington event in 1859, we estimate the interplanetary solar wind conditions at that time, and investigate the response of the magnetosphere-ionosphere system to this extreme solar wind conditions using global 3D MHD simulations. The main findings include: 1) The day-side magnetopause and bow shock are compressed to 4.3 and 6.0 Re (Earth radius), and their flanks are also strongly compressed. The magnetopause shifts inside the geosynchronous orbit, exposing geosynchronous satellites in the solar wind in the magnetosheath. 2) During the storm, the region-1 current increases by about 60 times, and the cross polar potential drop increases by about 80 times; the reconnection voltage is about 5 to 6 times larger than the average storms, which means a larger amount of the solar wind energy enters the magnetosphere, resulting in strong space weather phenomena. [ABSTRACT FROM AUTHOR]

Abstract: Information and communication technologies (ICTs) devices operate within the atmosphere around the earth as part of their global network. They are therefore subjected to all the natural activities that take place in this global space. Solar storm activities continue to increase in intensity and NASA has issued a warning that a powerful solar storm may hit the earth sometime in 2012. This has the potential to lead to ICTs devices not functioning at all if this happens. In this paper a worst case scenario of this storm, if it was to happen, is discussed with its pros and cons. [Copyright &y& Elsevier]

Positioning using a satellite requires defining the instantaneous positions of navigation satellites. The established positions are predicted and transmitted to the users applying satellites, and, however become degraded with accuracy in cases solar events divert the satellites from their path. Meanwhile, getting satellite coordinates with reference to the made predictions involves computing effort. The question addressed in this paper is whether orbit disturbances can be detected by examining these predictions so that computing coordinates are avoided. The paper argues that detection is possible but requires further experiments on confirmation due to the fact there have been relatively few solar storms in recent years while collecting data on satellite tracking. Also, the paper also suggests that detection by examining orbital parameters is of a limited practical value when compared with the ease of interpreting satellite coordinates measured in meters. [ABSTRACT FROM AUTHOR]

Aiming at two intense shock events on October 28 and 29, 2003, this paper presents a two-step method, which combines synoptic analysis of space weather — “observing” and quantitative prediction — “palpating”, and then uses it to test predictions. In the first step of “observing”, on the basis of observations of the solar source surface magnetic field, interplanetary scintillation (IPS) and ACE spacecraft, we find that the propagation of the shocks is asymmetric relative to the normal direction of their solar sources, and the Earth is located near the direction of the fastest speed and the greatest energy of the shocks. As the two fast ejection shock events, the fast explosion of coronal mass of the extremely high temperature, the strong magnetic field, and the high speed background solar wind are also helpful to their rapid propagation. In the second step of “palpating”, we adopt a new membership function of the fast shock events for the ISF method. The predicted results show that for the onset time of the geomagnetic disturbance, the relative errors between the observational and the predicted results are 1.8% and 6.7%; and for the magnetic disturbance magnitude, the relative errors are 4.1% and 3.1%, respectively. Furthermore, the comparison among the predicted results of our two-step method with those of five other prevailing methods shows that the two-step method is advantageous. The results tell us that understanding the physical features of shock propagation thoroughly is of great importance in improving the prediction precision. [ABSTRACT FROM AUTHOR]

Abstract: The Sun goes through cycles of high and low activity that repeats approximately every 11 years. The solar activity is correlated to the number of dark spots on the Sun which are sources of sudden, sporadic eruptions, releasing energetic particles into space. This can directly affect the ionosphere and radio communications around the Earth. A spectacular and unusually high sunspot activity occurred during October and November 2003, commonly referred to as the Halloween Storms. The increased radiation exposure at aircraft altitudes during such an event is of major concern to international aviation organizations, airlines, governmental authorities and aircraft crew as well as flight passengers. Here, we report radiation exposure measurements made by ARC Seibersdorf research (ARCS) onboard commercial aircraft using a tissue equivalent proportional counter (TEPC). A unique set of long-term measurements was collected before, during and after the storm at flight altitudes. The results of these investigations give an understanding of the combined effects of magnetic field disturbances and solar particle fluence due to a solar storm, showing a 70% variation in the radiation exposure at typical flight altitudes. Whilst several predictive codes exist the radiation exposure to aircrew during a solar storm is difficult to predict by calculation models. These calculation models are still struggling with the high uncertainty of spectral input data provided by satellites during a solar storm. A reliable dose assessment concept to assess the radiation exposure to aircrew caused by a solar storm using a network of dosimeter instruments on-board several aircraft can be achieved. Such a proposal has been already introduced by experts of the European Radiation Dosimetry Group (EURADOS). [Copyright &y& Elsevier]