ALBERT

Beschreibung: Abstract An analysis of the counter‐electrojet occurrence (CEJ) during 2008–2014 is presented for the African and American sectors based on local daytime (0700–1700 LT) observations from the Communications and Navigation Outage Forecasting System (C/NOFS) vertical ion plasma drift (equivalent to vertical E×B at an altitude of about 400 km) and ground‐based magnetometers. Using quiet time (Kp≤ 3) data, differences and/or similarities between the two data sets with reference to local time and seasonal dependence are established. For the first time, it is shown that C/NOFS satellite data are consistent with magnetometer observations in identifying CEJ occurrences during all seasons. However, C/NOFS satellite data show higher CEJ occurrence rate for almost all seasons. With respect to local time, C/NOFS satellite observes more CEJ events than magnetometer observations by average of about 20% and 40% over the American and African sectors, respectively, despite both data sets showing similar trends in CEJ identification. Therefore, when a space weather event occurs, it is important to first establish the original variability nature and/or magnitude of the eastward electric field in equatorial regions before attributing the resulting changes to solar wind‐magnetosphere and ionosphere coupling processes since CEJ events can be present even during quiet conditions.

Beschreibung: Abstract High‐speed solar wind streams that originate from coronal holes play an important role in space weather disturbances, especially during the declining phase of the solar cycle. Space weather forecasters attempt to find good coronal hole indices that can be used to predict high‐speed streams days in advance. Several indices related to the coronal hole area, brightness, or magnetic field expansion factor have been reported in the literature. Empirical solar wind forecast models have been developed and used in operational service by several organizations by constructing prediction functions that relate the coronal hole index to the solar wind speed. In this paper, we present a new empirical modeling method and test its validity by comparing it with a previously reported method when applied to different coronal hole indices. In total, six empirical models are tested for a long period of time (2011–2018), with a 27‐day persistence model as a comparison benchmark. The results show that while all these empirical models can capture the temporal patterns of the solar wind observations well, the new modeling method and utilization of a composite coronal hole index PCH as an input parameter indeed improves the forecast accuracy. The high‐speed streams can be predicted approximately 3 days in advance, with a probability of detection of 0.78, a positive predictive value of 0.73, and a threat score of 0.61. The uncertainty of the high‐speed stream arrival time is approximately 1 day and the uncertainty of the peak speed is approximately 80 km/s.

Beschreibung: Abstract We describe a metric that has been repeatedly applied to assess the performance of models aimed at predicting geomagnetically induced currents from Space Weather events. The used parameterization, based on the well‐known root‐mean‐square error between model and observations, is simple and intuitive. Its use is exemplified, and its advantages and disadvantages are discussed, as well as its relationship with the widely extended correlation coefficient, r. Although the use of r alone is inappropriate for purposes of evaluating the agreement between model and observations, its use is recommended to complement the described performance parameter.

Beschreibung: Abstract Coronal Mass Ejections (CMEs) cause the largest geomagnetic disturbances at Earth which impact satellites, wired communication systems and power grids. The CME Analysis Tool (CAT) is used to determine a CME's initial longitude, latitude, angular width and radial speed from coronagraph images. These are the initial conditions for the Wang‐Sheeley‐Arge (WSA) Enlil solar wind model, along with the ambient solar wind properties derived from magnetograms. However, the coronagraph imagery is limited by field of view. We have incorporated heliospheric imagery (HI) from the Solar Terrestrial Relations Observatory (STEREO) into CAT to create the CME Analysis Tool with Heliospheric Imagery (CAT‐HI). These HI images have a larger field of view, allowing tracking of CMEs to greater distances from the Sun. We have compared the performances of CAT and CAT‐HI by examining the expected arrival times of CMEs at the L1 Lagrange point and found them to be consistent. However, CAT‐HI is advantageous because it could be used to prune ensemble forecasts and issue routine updates for CME arrival time forecasts. Finally, we discuss CAT‐HI in the context of an operational mission at the L4 or L5 Lagrange points.

Beschreibung: Abstract Mass density variations can deviate from the expected behaviour caused by temperature due to changes in the composition. Such deviations can be especially significant during solar minimum conditions. Model‐data differences are typically resolved through temperature corrections while overlooking the role of errors in lower boundary composition. In this work, we use a data‐driven methodology to simultaneously estimate thermosphere composition and temperature contributions to model‐data differences. The methodology uses modal decomposition to extract high‐dimensional, reduced order basis functions for the covariance of the neutral thermospheric species and temperature. The extracted basis functions are combined with CHAMP and GRACE mass density measurements using a non‐linear least squares solver. We demonstrate the methodology using the Naval Research Laboratory's empirical MSIS (Mass Spectrometer and Incoherent Scatter) model to derive high‐dimensional basis functions. We characterize and quantify the contribution of temperature and lower boundary effects with oxygen and helium since the two species have a direct impact on drag and orbit prediction through gas‐surface interactions and mass density. We analyze the month of December in 2008, based on the work of Thayer et al. [2012], and estimate that lower boundary composition errors contribute approximately 50% of the model‐data differences.

Beschreibung: Abstract Eruptive events on the Sun have an impact on the immediate surroundings of the Earth. Through induction of electric currents, they also affect Earth‐bound structures such as the electric power transmission networks. Inspired by recent studies we investigate the correlation between the disturbances recorded in 12 years in the maintenance logs of the Czech electric‐power distributors with the geomagnetic activity represented by the K index. We find that in case of the datasets recording the disturbances on power lines at the high and very high voltage levels and disturbances on electrical substations, there is a statistically significant increase of anomaly rates in the periods of tens of days around maxima of geomagnetic activity compared to the adjacent minima of activity. There are hints that the disturbances are more pronounced shortly after the maxima than shortly before the maxima of activity Our results provide indirect evidence that the geomagnetically induced currents may affect the occurrence rate of anomalies registered on power‐grid equipment even in the mid‐latitude country in the middle of Europe. A follow‐up study that includes the modelling of geomagnetically induced currents is needed to confirm our findings.

Beschreibung: Abstract The Sun was remarkably active during the first week of September 2017 producing numerous solar flares, solar radiation storms and coronal mass ejections (CME). This activity caused disruption to terrestrial high frequency (HF, 3‐30 MHz) radio communication channels including observations with the SuperDARN HF radars. In this paper, we analyze the response of SuperDARN ground‐scatter observations and decreases in background sky noise level in response to multiple solar flares occurring in quick succession and co‐occurring with solar energetic protons and auroral activity. We estimate the attenuation in HF signal strength using an approach similar to riometry and find that the radars exhibit a nonlinear response to compound solar flare events. Additionally, we find the three different space weather drivers have varying degrees of influence on the HF signal properties at different latitudes. Our study demonstrates that in addition to monitoring high latitude convection, SuperDARN observations can be used to study the spatiotemporal evolution of disruption to HF communication during extreme space weather conditions.

Beschreibung: Abstract In this paper we present several methods to identify precursors that show great promise for early predictions of solar flare events. A data pre‐processing pipeline is built to extract useful data from multiple sources, Geostationary Operational Environmental Satellites (GOES) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI), to prepare inputs for machine learning algorithms. Two classification models are presented: classification of flares from quiet times for active regions and classification of strong versus weak flare events. We adopt deep learning algorithms to capture both spatial and temporal information from HMI magnetogram data. Effective feature extraction and feature selection with raw magnetogram data using deep learning and statistical algorithms enable us to train classification models to achieve almost as good performance as using active region parameters provided in HMI/Space‐Weather HMI‐Active Region Patch (SHARP) data files. Case studies show a significant increase in the prediction score around 20 hours before strong solar flare events.

Beschreibung: Abstract The total electron content (TEC) recorded at two middle‐latitude stations (Mohe and Beijing), and four low‐latitude stations (Xiamen, Guangzhou, Nanning, and Kunming) in the China sector are analyzed to study the response of the ionosphere during the sudden stratospheric warming (SSW) event in February 2018. The TEC and deviation of TEC (ΔTEC) present remarkable perturbation after the reversal of the zonal wind during the SSW period. The ΔTEC presents enhancement during the daytime and decreases after sunset, especially around the temperature peak. Results of wavelet power spectra analysis show that the ΔTEC shows intensive semidiurnal and diurnal oscillations during the SSW period. The percentage of dTEC exhibits moderate correlation with solar geophysical drivers (such as solar wind speed, F10.7, and Ap index) during the period of 11–26 February at low‐latitude stations. The significant correlation between equatorial electrojet and the percentage of dTEC monitored at low latitude indicates that the equatorial electrojet plays a key role in the anomaly perturbation and periodic oscillation of TEC, while it has a weak correlation at middle latitude.

Beschreibung: No abstract is available for this article.

Beschreibung: Abstract This paper describes a new neural network‐based approach to estimate ionospheric critical plasma frequencies (f0F2) from Global Navigation Satellite Systems (GNSS)‐vertical total electron content (TEC) measurements. The motivation for this work is to provide a method that is realistic and accurate for using GNSS receivers (which are far more commonly available than ionosondes) to acquire f0F2 data. Neural networks were employed to train vertical TEC and corresponding f0F2 observations respectively obtained from closely located GNSS receivers and ionosondes in various parts of the globe. Available data from 52 pairs of ionosonde‐GNSS receiver stations for the 17‐year period from 2000 to 2016 were used. Results from this work indicate that the relationship between f0F2 and TEC is mostly affected by the seasons, followed by the level of solar activity, and then the local time. Geomagnetic activity was the least significant of the factors investigated. The relationship between f0F2 and TEC was also shown to exhibit spatial variation; the variation is less conspicuous for closely located stations. The results also show that there is a good correlation between the f0F2 and TEC parameters. The f0F2/TEC ratio was generally observed to be lower during enhanced ionospheric ionizations in the day time and higher during reduced ionospheric ionizations in the nights and early mornings. The analysis of errors shows that the model developed in this work (known as the NNT2F2 model) can be used to estimate the f0F2 from GNSS‐TEC measurements with accuracies of less than 1 MHz. The new approach described in this paper to obtain f0F2 based on GNSS‐TEC data represents an important contribution in space weather prediction.

Beschreibung: Abstract The potential field source surface (PFSS) model is widely used to derive the magnetic field of the solar corona. The only free parameter in the PFSS model is the radius of the so‐called source surface, where magnetic field lines are forced to open. The radius of this surface is typically set to 2.5 solar radii in research and operational PFSS numerical models. Here, using Global Oscillation Network Group (GONG) synoptic maps of the photospheric field, solutions of the PFSS model for various heights of the source surface are investigated for 2006–2018. In particular, numerically derived open solar magnetic flux and coronal holes are examined. Solutions of the PFSS model based on GONG synoptic maps are particularly important since they are often used to drive operational space weather forecast models. Comparisons between observations and numerical results in this paper suggest that the radius of the source surface is significantly lower than 2.5 solar radii during the active phase of solar cycle 24. The fact that the source surface location depends on the solar activity suggests that relations which associate solar wind properties with the coronal magnetic field in the PFSS‐based solar wind modes should be revisited. Furthermore, although the correction of the polar magnetic field is part of GONG synoptic map production pipeline, the results suggest that better treatment of polar fields is needed to cover observational gaps. The issue with the polar fields in GONG maps is particularly pronounced in recent years.

Beschreibung: Abstract The Kp index is a measure of the mid‐latitude global geomagnetic activity and represents short‐term magnetic variations driven by solar wind plasma and IMF. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere and the radiation belts. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast Kp, based their inferences on the recent history of Kp and on solar wind measurements at L1. In this study, we systematically test how different machine learning techniques perform on the task of nowcasting and forecasting Kp for prediction horizons of up to 12 hours. Additionally, we investigate different methods of machine learning and information theory for selecting the optimal inputs to a predictive model. We illustrate how these methods can be applied to select the most important inputs to a predictive model of Kp and to significantly reduce input dimensionality. We compare our best performing models based on a reduced set of optimal inputs with the existing models of Kp, using different test intervals and show how this selection can affect model performance.

Beschreibung: Abstract On 13 March 1989, the largest magnetic storm of the last century caused widespread effects on power systems including a blackout of the Hydro‐Québec system. Since then this event has become the archetypal disturbance for examining the geomagnetic hazard to power systems. However, even 30 years on from 1989, the story of exactly what happened in March 1989 is far from complete. This paper reexamines the information available about the March 1989 event and uses this to construct a timeline and description of the space weather phenomena and how they caused the power system effects. The evidence shows that the disturbance was caused by two coronal mass ejections (CMEs): the first associated with a X4.5 flare on 10 March and the second linked to a M7.3 flare on 12 March. The arrival of the interplanetary CME shock fronts caused storm sudden commencements at 01.27 and 07.43 UT on 13 March. The transit time and speed of the first (second) interplanetary CME shock are 54.5 hr (31.5 hr) and 760 km/s (1,320 km/s). Empirical relations are used to estimate solar wind speed and southward interplanetary magnetic field, Bs, and give values of v = 980 km/s, Bs = 40 to 60 nT at the peak of the storm. Key findings are that the second storm sudden commencement occurred at the same time as the substorm that impacted the Hydro‐Québec system and indicates that external triggering of the substorm may have contributed to a faster substorm onset than might otherwise have occurred. This caused the production of larger geomagnetically induced currents that caused the Hydro‐Québec blackout. The March 1989 storm had the largest recorded value of the Dst index representing the size of the magnetic storm main phase, but the Hydro‐Québec blackout occurred early in the storm when the Dst value was less disturbed. Only later in the storm did Dst reach its peak value. At this time an expansion of the auroral oval brought disturbances to lower latitudes where they caused power system problems in the United States, United Kingdom, and Sweden.

Beschreibung: Abstract The OMNI database is formed by propagating the solar wind measured at around Lagrange point L1, whose result may differ from the actual solar wind in the vicinity of the bow shock nose. To test the quality of the OMNI database we cross‐correlate the 2‐hr intervals of 1‐min interplanetary magnetic field (IMF) data provided mostly by ACE and WIND spacecraft with Geotail measurements in front of the bow shock (10409 cases in 1997‐2016). We used two metrics: Pearson correlation coefficient (CC) and prediction efficiency (PE). Confirming previous studies, we found that the prediction quality of actual IMF degrades continuously with increasing distance of OMNI spacecraft from the Sun‐Earth line, with the amounts of poor and good predictions become nearly equal for RYZ ≥ 65 RE (they constitute ~12% of the entire data base). In roughly 20% of the analyzed data, low CC and PE values were the consequence of low IMF variability (a low signal to noise ratio). The remaining data set include 42% of very good data (CC ≥ 0.8), 33% of relatively good data (0.5 ≤ CC 〈 0.8 and PE ≥ 0), 10% of data having correct variability but wrong absolute values (0.5 ≤ CC 〈 0.8 and PE 〈 0), and 15% of poor data (CC 〈 0.5). We also discovered that the OMNI data are generally of a good quality when the PC index of geomagnetic activity correlates well with the solar wind‐magnetosphere coupling factor suggested by Kan and Lee (1979).

Beschreibung: Abstract We develop and test an empirical model predicting ground‐based observations of ultra‐low frequency (ULF, 1‐20 mHz) wave power across a range of frequencies, latitudes and magnetic local time sectors. This is parameterized by instantaneous solar wind speed vsw, variance in proton number density var(Np) and interplanetary southward magnetic field Bz. A probabilistic model of ULF wave power will allow us to address uncertainty in radial diffusion coefficients and therefore improve diffusion modeling of radial transport in Earth's outer radiation belt. Our model can be used in two ways to reproduce wave power; by sampling from conditional probability distribution functions or by using the mean (expectation) values. We derive a method for testing the quality of the parameterization and test the ability of the model to reproduce ULF wave power time series. Sampling is a better method for reproducing power over an extended time period as it retains the same overall distribution while mean values are better for predicting the power in a time series. The model predicts each hour in a time series better than the assumption that power persists from the preceding hour. Finally, we review other sources of diffusion coefficient uncertainty. Although this wave model is designed principally for the goal of improved radial diffusion coefficients to include in outer radiation belt diffusion based modeling, we anticipate that our model can also be used to investigate the occurrence of ULF waves throughout the magnetosphere and hence the physics of ULF wave generation and propagation.

Beschreibung: Abstract Peer review remains one of the most important service activities for scientists. Through the time‐consuming process of peer review, community volunteers set the bar for the quality of science that is shared with each other and with the world. Attentive, patient, and critical review is required to maintain rigorous and accurate scientific reporting. Reviewers donate their time and effort with little incentive outside of the knowledge that they are contributing to sustain scientific rigor. Space Weather is fortunate to be able to continually rely on our reviewers to maintain a journal that receives and publishes high‐quality, high‐impact articles. We recognize the time, effort, and dedication each review requires. For this, we extend a heartfelt thank you to all of our 2018 reviewers. We sincerely appreciate your choice to respond positively to our review requests. Last year, Space Weather received 785 peer reviews from 354 individuals. The reviewers who contributed three or more reviews are recognized in italics below. Thank you all for your contributions in 2018.

Beschreibung: Abstract Routine in‐situ solar wind observations from L5, located 60° behind Earth in its orbit, would provide a valuable input to space‐weather forecasting. One way to ulitise such observations is to assume that the solar wind is in perfect steady state over the 4.5 days it takes the Sun to rotate 60° and thus near‐Earth solar wind in 4.5‐days time would be identical to that at L5 today. This corotation approximation is most valid at solar minimum when the solar wind is slowly evolving. Using STEREO data, it has been possible to test L5‐corotation forecasting for a few months at solar minimum, but the various contributions to forecast error cannot be disentangled. This study uses 40+ years of magnetogram‐constrained solar wind simulations to isolate the effect of latitudinal offset between L5 and Earth due to the inclination of the ecliptic plane to the solar rotational equator. Latitudinal offset error is found to be largest at solar minimum, due to the latitudinal ordering of solar wind structure. It is also a strong function of time of year; maximum at the solstices and very low at equinoxes. At solstice, the latitudinal offset alone means L5‐corotation forecasting is expected to be less accurate than numerical solar wind models, even before accounting for time‐dependent solar wind structures. Thus, a combination of L5‐corotation and numerical solar wind modelling may provide the best forecast. These results also highlight that three‐dimensional solar wind structure must be accounted for when performing solar wind data assimilation.

Beschreibung: Abstract We re‐construct the timeline of the extreme space weather event of May 1921, reviewing a wealth of reports from scientific literature, databases, newspaper reports, and reports by historians and astronomers. A series of coronal mass ejections (CMEs) bombarded Earth between 13 and 16 May, as shown by a series of sudden commencements observed across the global network of magnetometers. These CMEs produced three major periods of geomagnetic activity. The first period followed the arrival of two CMEs on 13 May. These may have cleared much density from the inner heliosphere, enabling a subsequent CME to travel quickly to Earth and cause intense activity. Continuing moderate magnetic activity following the first period may also have preconditioned the magnetosphere so it responded strongly to that later CME. This arrived late on 14 May, driving a short period of very intense activity early on 15 May, including technological impacts indicative of strong geoelectric fields. Another CME arrived early on 16 May, driving intense activity similar to that on 13 May. We show how these impacts fit with scientific observations to give a timeline that can be used in worst case studies/benchmarks. We also show that some impacts were probably coincidental with the storm, but due to more prosaic faults. This sequence of preconditioning, intense geoelectric fields and their impacts, plus coincidental faults, makes the 1921 event an excellent basis for building space weather scenarios. Such scenarios are vital scientific input to the development and implementation of policies for mitigation of severe space weather.

Beschreibung: Abstract We report updated measurements of the integral fluxes of energetic protons, helium ions, and heavier ions as measured by the Cosmic Ray Telescope for the Effects of Radiation (CRaTER). CRaTER is a particle telescope that has been operating aboard the Lunar Reconnaissance Orbiter since 2009. In an earlier report, we presented the methodology used to extract linear energy transfer (LET) spectra, and integral fluxes for particles with sufficient energies to fully penetrate the telescope. Results were presented for the time span from late 2009 through the end of calendar year 2014, a period that encompassed the rise of solar activity from deep solar minimum to the weak maximum of Cycle 24. Here, we update the results with data obtained from that point in time through the end of 2018, in the declining phase of Cycle 24. Fluxes obtained in the most recent data are approaching the peak levels observed in late 2009 and early 2010. The results can be used as input to models of solar modulation of Galactic Cosmic Rays, and are also relevant to human exploration of deep space.

Beschreibung: Abstract Features and peculiarities of the cosmic ray intensity (CRI) and the geomagnetic activity, along with several solar plasma and interplanetary magnetic field during the period 4‐10 September 2017 are studied. The period was characterized by strong solar activity: several solar flares occurred, several halo Coronal Mass Ejections (CMEs) were ejected in space. In the near‐Earth interplanetary space, the CMEs driving shock(s) and sheath(s) were identified. At the Earth, strong Forbush decreases (FD) in CRI and geomagnetic storms (GS) were observed. Several large solar flares, one of them of very high X‐ray importance (X 9.3) and three halo CMEs were detected in the solar atmosphere. Two shock‐associated Interplanetary Coronal Mass Ejections were observed during that interval in near‐Earth space; the latter and faster one arrived even as the ejecta of earlier one was still crossing. Variations in interplanetary plasma and field parameters during, before and after the FD and GS that occurred during the considered period were examined. A detailed time‐lagged correlation analysis using data at three different temporal resolutions (hourly, 5‐min and 1‐min) was also performed. Cross‐correlations of time series of CRI with geomagnetic activity during the period 4 – 10 September 2017 are computed. This cross‐correlation analysis between CRI variability (defined as the difference of the CRI count rate between the current and the previous time step) and the Dst indicates a delay of Dst by 3‐4 hours.

Beschreibung: Abstract Current algorithms for the real‐time prediction of the Kp index use a combination of models empirically driven by solar wind measurements at the L1 Lagrange point and historical values of the index. In this study, we explore the limitations of this approach, examining the forecast for short and long lead times using measurements at L1 and Kp time series as input to artificial neural networks. We explore the relative efficiency of the solar wind‐based predictions, predictions based on recurrence, and based on persistence. Our modeling results show that for short‐term forecasts of approximately half a day, the addition of the historical values of Kp to the measured solar wind values provides a barely noticeable improvement. For a longer‐term forecast of more than two days, predictions can be made using recurrence only, while solar wind measurements provide very little improvement for a forecast with long horizon times. We also examine predictions for disturbed and quiet geomagnetic activity conditions. Our results show that the paucity of historical measurements of the solar wind for high Kp results in a lower accuracy of predictions during disturbed conditions. Rebalancing of input data can help tailor the predictions for more disturbed conditions.

Beschreibung: Abstract Analysis is made of low‐latitude ground‐based magnetometer data recording the magnetic superstorm of May 1921. By inference, the storm was driven by a series of interplanetary coronal mass ejections, one of which produced a maximum pressure on the magnetopause of ~64.5 nPa, sufficient to compress the subsolar magnetopause radius to ~5.3 Earth radii. Over the course of the storm, low‐latitude geomagnetic disturbance exhibited extreme local‐time (longitude) asymmetry that can be attributed to substorm disturbance extending to low latitudes. The storm attained an estimated maximum ‐Dst on May 15 of 907 nT ±132 nT, an intensity comparable to that of the Carrington event of 1859. The May 1921 storm interfered with and damaged telephone and telegraph systems associated with railroad systems in New York City and State. These effects were due to a combination of three factors: the localized details of geomagnetic vector disturbance, the geographic expression of the Earth's surface impedance tensor, and the configurations and physical parameters of the electrical networks of the day.

Beschreibung: No abstract is available for this article.

Beschreibung: Abstract Introduction of new navigation signals L2C (1227.60 MHz) and L5 (1176.45 MHz) to the existing GPS (Global Positioning System) spectrum, under the modernization program of GPS offers the improvement of position accuracy. The present study aims to understand the relative robustness of the L2C and L5 signals compared to legacy L1 C/A signal during periods of scintillations in terms of durations of cycle slips encountered from an anomaly crest location, Calcutta (22.58°N, 88.38°E geographic; magnetic dip 32°N). The data analyzed in this study were recorded during the vernal equinox of 2014 (February–April), a period of high solar activity of cycle 24. Results obtained from the comparative analyses, which are perhaps one of the first from the Indian longitude sector, indicate GPS L5 to be more robust than L1 C/A and L2C in terms of occurrence and duration of cycle slips under adverse ionospheric conditions. Furthermore, loss‐of‐lock events of duration greater than 6 s are found to be more frequent for S4 ≥ 0.6. It is found that frequency sensitivity of the GPS spectrum, in terms of occurrence of cycle slips and loss of locks are in conformity with earlier results from the equatorial region but are different from the high latitudes with respect to local time of occurrence and geomagnetic activity.

Beschreibung: Abstract Between 7‐8 September 2017, Earth experienced extreme space weather events. We have combined measurements made by the IMAGE magnetometer array, ionospheric equivalent currents, GIC recordings in the Finnish natural gas pipeline, and multiple ground conductivity models to study the Fennoscandia ground effects. This unique analysis has revealed multiple interesting physical and technical insights. We show that although the 7‐8 September event was significant by global indices (Dst~150 nT), it produced an unexpectedly large peak GIC. It is intriguing that our peak GIC did not occur during the intervals of largest geomagnetic depressions, nor was there any clear upstream trigger. Another important insight into this event is that unusually large and rare GIC amplitudes (〉10 A) occurred in multiple MLT sectors and could be associated with westward and eastward electrojets. We were also successfully able to model the geoelectric field and GIC using multiple models, thus providing a further important validation of these models for an extreme event. A key result from our multiple conductivity model comparison was the good agreement between the temporal features of 1D and 3D model results. This provides an important justification for past and future uses of 1D models at Mäntsälä which is highly relevant to additional uses of this dataset. Although the temporal agreement (after scaling) was good, we found a large (factor of 4) difference in the amplitudes between local and global ground models due to the difference in model conductivities. Thus, going forward, obtaining accurate ground conductivity values are key for GIC modeling.

Beschreibung: Abstract We present three solar wind shock events that all occurred at times when Advanced Composition Explorer was near L1 and WIND was in front of the bow shock. We use a 1.5‐D MHD (magnetohydrodynamic) numerical model and the well known MVAB‐0 time‐shifting algorithm to propagate these events from Advanced Composition Explorer to the location of WIND. The results of these two methods are compared to WIND observations. We find that the 1.5‐D numerical model reproduces some important features in the WIND data that are not reflected in the time‐shifted results. We believe that 1.5‐D numerical simulations could supplement traditional time‐shifting methods in some circumstances for time‐shifting solar wind data to the bow shock.

Beschreibung: Abstract During the intense solar radio bursts on 6 September 2017, Global Navigation Satellite Systems (GNSS) signal interferences were observed at ground stations in the European longitude sector from 20°N to 70°N for all GNSS satellites in view including GPS, GLONASS, and Galileo. The solar radio noise reduced the signal‐to‐noise ratio with clear frequency dependence. The impact of the radio burst has been found at L2 and L5 frequencies, but not at L1 frequency. The ground observation of the solar radio spectrum between 1.0 and 2.0 GHz corresponds well to such frequency dependence. The maximum signal‐to‐noise ratio reduction of ‐10 dB was found when the solar radio flux was pulsating around 2,000 solar flux unit level. Precise point positioning results show that accuracy is reduced with stronger deviation for dual‐frequency solutions than for single‐frequency solutions based on L1 signal only. The positioning error refers rather to the solar extreme ultraviolet flare than to solar radio interferences. The results presented here are a clear indication of frequency‐dependent GNSS performance degradation during strong space weather events.

Beschreibung: Abstract We used data for eight magnetospheric spacecraft providing magnetic observations in various magnetospheric domains during a six‐day time period, including the June 2015 storm, and a five‐day period including the March 2015 storm. For these time intervals, containing different solar wind regimes and different activity levels, we used three types of metrics to compare predictions of all existing types of magnetospheric magnetic field models, including empirical models (TA15, TS05, and T96), a data‐adapted model (AM03), and a global magnetohydrodynamic model (Space Weather Modeling Framework/Block Adaptive Tree Solar Wind–Roe–Upwind Scheme coupled with Rice Convection Model). In total, the models are ranked in the order: AM03, TS05, TA15, Space Weather Modeling Framework, and T96. The regional scores may differ from the average ones (in particular, better scores are obtained at GEO, compared to the inner magnetosphere) and also the model effectiveness varies with activity conditions (for example, TA15 outperforms other models in quiet conditions, but TS05 leads during active times). Quite unexpectedly, although run at modest resolution, the community available global magnetohydrodynamic model closely approached the best scores of empirical statistical models during the moderate/high disturbed periods in the June event, suggesting that this kind of modeling may now compete with other type models. We also carried out the field line mapping from fixed points in the equatorial magnetosphere to the ionosphere, using different models to examine the storm time foot point excursions (which may be as large as ~10° CGLat during storm time sudden commencements) and their uncertainties, quantified by the difference between the model predictions.

Beschreibung: Abstract In this study, Global Ionosphere Specification (GIS) based on Gauss‐Markov Kalman filter assimilation of slant total electron content observed from ground‐based global positioning system receivers and space‐based radio occultation instrumentations is applied to investigate the ionospheric day‐to‐day tidal variability during the 2009 stratospheric sudden warming (SSW) period. Including the improved daily three‐dimensional global electron density distribution from GIS enables us to retrieve the daily solar tidal solution by using least squares tidal analysis. We find prominent reductions followed by enhancements in the amplitude of the solar semidiurnal migrating tide (SW2) after the peak warming, with recurrent phase variations occurring at low magnetic latitudes over a period of about 15 days. This is close to the beating period (15.13 day) between SW2 and lunar semidiurnal (M2), thus suggesting the existence of strong M2, and our results demonstrate that the intensification of M2 exists only during the SSW period. Additionally, M2 acts as the key contributor to make the semidiurnal ionospheric perturbations shift toward later local times. Our tidal analyses of daily GIS thus provide evidence for the combined impact of amplitudes and phases of the SW2 and M2 in producing semidiurnal variations in ionosphere during the 2009 SSW.

Beschreibung: Abstract In this study, the CHAMP (Challenging Minisatellite Payload satellite) and GRACE (Gravity Recovery and Climate Experiment satellite) observations and the simulations from the National Center for Atmospheric Research Thermosphere Ionosphere Electrodynamics General Circulation Model are used to investigate the impact of local time of satellite sampling on the dynamic modeling of the thermosphere. Thermosphere Ionosphere Electrodynamics General Circulation Mode simulations are sampled along the satellite orbits to obtain the synthetic observations and to reconstruct the global thermosphere. By comparing with the simulated “true” base, the relative deviations of the dynamic reconstructions are further characterized as a function of the local time of satellite sampling. It is found that the relative deviations would become relatively large when the satellite crosses the dawn‐dusk local time sectors. Our further investigation indicates that this spatial–temporal dependence would be greatly reduced, as the data from one more satellite are blended. The CHAMP and GRACE observations are also utilized to assess this local time dependence of the thermospheric forecasting.

Beschreibung: Abstract Surface charging by keV (kiloelectron Volt) electrons can pose a serious risk for satellites. There is a need for physical models with the correct and validated dynamical behavior. The 18.5‐month (2013–2015) output from the continuous operation online in real time as a nowcast of the Inner Magnetosphere Particle Transport and Acceleration Model (IMPTAM) is compared to the GOES 13 MAGnetospheric Electron Detector (MAGED) data for 40, 75, and 150 keV energies. The observed and modeled electron fluxes were organized by Magnetic Local Time (MLT) and IMPTAM driving parameters; the observed Interplanetary Magnetic Field (IMF) BZ, BY, and |B|; the solar wind speed VSW; the dynamic pressure PSW; and Kp and SYM‐H indices. The peaks for modeled fluxes are shifted toward midnight, but the ratio between the observed and modeled fluxes at around 06 MLT is close to 1. All the statistical patterns exhibit very similar features with the largest differences of about 1 order of magnitude at 18–24 MLT. Based on binary event analysis, 20–78% of threshold crossings are reproduced, but Heidke skill scores are low. The modeled fluxes are off by a factor of 2 in terms of the median symmetric accuracy. The direction of the error varies with energy: overprediction by 50% for 40 keV, overprediction by 2 for 75 keV, and underprediction by 18% for 150 keV. The revealed discrepancies are due to the boundary conditions developed for ions but used for electrons, absence of substorm effects, representations of electric and magnetic fields which can result in not enough adiabatic acceleration, and simple models for electron lifetimes.

Beschreibung: Abstract Space weather manifests in power networks as quasi‐DC currents flowing in and out of the power system through the grounded neutrals of high‐voltage transformers, referred to as geomagnetically induced currents. This paper presents a comparison of modeled geomagnetically induced currents, determined using geoelectric fields derived from four different impedance models employing different conductivity structures, with geomagnetically induced current measurements from within the power system of the eastern states of Australia. The four different impedance models are a uniform conductivity model (UC), one‐dimensional n‐layered conductivity models (NU and NW), and a three‐dimensional conductivity model of the Australian region (3DM) from which magnetotelluric impedance tensors are calculated. The modeled 3DM tensors show good agreement with measured magnetotelluric tensors obtained from recently released data from the Australian Lithospheric Architecture Magnetotelluric Project. The four different impedance models are applied to a network model for four geomagnetic storms of solar cycle 24 and compared with observations from up to eight different locations within the network. The models are assessed using several statistical performance parameters. For correlation values greater than 0.8 and amplitude scale factors less than 2, the 3DM model performs better than the simpler conductivity models. When considering the model performance parameter, P, the highest individual P value was for the 3DM model. The implications of the results are discussed in terms of the underlying geological structures and the power network electrical parameters.

Beschreibung: Abstract We review, summarize, and comment on the 2019 National Space Weather Strategy and Action Plan.

Beschreibung: Abstract Eric H. Strach (1914‐2011) studied medicine at University of Prague and graduated in 1938. Strach dedicated a great part of his life to astronomy becoming a consistent and meticulous observer. He joined the Liverpool Astronomical Association and British Astronomical Association during the 1960s and obtained two recognitions as proof of his great work in solar physics: the BAA's Merlin Medal and Gift in 1999 and Walter Goodacre Medal and Gift, 10 years later. Strach recorded four decades (1969‐2008) of systematic solar records in his observation notebooks although he started his observations from the late 1950s. In this work, we document the valuable effort made by Strach in getting four decades of solar records and the importance of this kind of long observation series for studies of space weather and climate. We present the sunspot group number series according to Strach's data and a long observation series of prominences recorded by Strach.

Beschreibung: Abstract An existing empirical model of the electron fluxes at geosynchronous orbit is extended radially outward in the equatorial plane to ~6–20 Earth radii (RE) using observations from the Research with Adaptive Particle Imaging Detectors (RAPID) instrument on the Cluster spacecraft. The new model provides electron flux predictions in the energy range ~45 eV to ~325 keV, as a function of local time and radial distance from the Earth, with geomagnetic activity parameterized by the Kp index. The model outputs include the mean and median electron fluxes along with the standard deviation and the 5th, 25th, 75th, and 95th percentiles for the given input conditions. The flux outputs from the model are tested against in‐sample observations from Cluster/RAPID and out‐of‐sample observations from Time History of Events and Macroscale Interactions during Substorms (THEMIS)/Solid State Telescope with good prediction efficiency during quiet and active intervals, as quantified by standard methods. This new model is intended to supplement current predictive capabilities in the magnetosphere for spacecraft operations, as well as providing the necessary boundary and/or input conditions for computational/physical models of the magnetospheric system when the necessary in situ observations are unavailable. While the new model can certainly not reproduce the rapid small‐scale fluctuations inherent in spacecraft observations, it does provide a coarse capability to predict the flux of electrons close to the equatorial plane, based on radial distance, energy, local time, and geomagnetic activity, in regions where no in situ assets are available.

Beschreibung: Abstract Solar energetic protons (SEPs) can cause radiation damage to satellites. The Space Environment Prediction Center of China defines the start of a SEP event as the time when three consecutive instances of the 5‐min‐averaged integral flux of 〉10 MeV protons equal or exceed the 10 proton flux unit threshold. In this study, we analyzed the 5‐min‐averaged soft X‐ray flux and the differential and integral proton flux obtained by the Geostationary Operational Environmental Satellites for the period from January 1990 to September 2017 and developed SEP prediction models and their products. The statistical models take one or two data products and the given thresholds as the predictor and predict whether a SEP event will occur or not in the next 24 hr. The quality of the forecast models was measured by comparing the model results against certain verification metrics. Our model taking the products of 5‐min‐averaged integral flux of 〉10 MeV protons and long wavelength of soft X‐ray flux as predictors can provide a probability of detection of 0.80 (152/190), a false alarm ratio of 0.26 (53/205), and an average warning time of 2.6 hr for the correctly predicted events. In addition, the model can provide a critical success index of 0.63, a Gilbert skill score of 0.62, and a Heidke skill score of 0.76.

Beschreibung: No abstract is available for this article.

Beschreibung: Abstract The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework leverages existing Community Coordinated Modeling Center services: Run‐on‐Request postprocessing tools that generate model time series outputs and the new Community Coordinated Modeling Center Metadata Registry that describes simulation runs using Space Physics Archive Search and Extract metadata. The new CAMEL visualization tool compares the modeled time series with observational data and computes a suite of skill scores such as Prediction Efficiency, Root‐Mean‐Square Error, and Symmetric Signed Percentage Bias. Model‐data pairs used for skill calculations are obtained considering a user‐selected maximum difference between the time of observation and the nearest model output. The system renders available data for all locations and time periods selected using interactive visualizations that allow the user to zoom, pan, and pick data values along traces. Skill scores are reported for each selected event or aggregated over all events for all participating model runs. Separately, scores are reported for all locations (satellites or stations) and for each location individually. We are building on past experiences with model‐data comparisons of magnetosphere and ionosphere model outputs from GEM2008, GEM‐CEDAR Electrodynamics Thermosphere Ionosphere, and the SWPC Operational Space Weather Model challenges. The CAMEL visualization tool is demonstrated using three validation studies: (a) Wang‐Sheeley‐Arge heliosphere simulations compared against OMNI solar wind data, (b) ground magnetic perturbations from several magnetosphere and ionosphere electrodynamics models as observed by magnetometers, and (c) electron fluxes from several ring current simulations compared to Radiation Belt Storm Probes Helium Oxygen Proton Electron instrument measurements, integrated over different energy ranges.

Beschreibung: Abstract We present evidence that variability in the STEREO‐A Heliospheric Imager (HI) data is correlated with in situ solar wind speed estimates from WIND, STEREO‐A, and STEREO‐B. For 2008–2012, we compute the variability in HI differenced images in a plane‐of‐sky shell between 20 to 22.5 solar radii and, for a range of position angles, compare daily means of HI variability and in situ solar wind speed estimates. We show that the HI variability data and in situ solar wind speeds have similar temporal autocorrelation functions. Carrington rotation periodicities are well documented for in situ solar wind speeds, but, to our knowledge, this is the first time they have been presented in statistics computed from HI images. In situ solar wind speeds from STEREO‐A, STEREO‐B, and WIND are all are correlated with the HI variability, with a lag that varies in a manner consistent with the longitudinal separation of the in situ monitor and the HI instrument. Unlike many approaches to processing HI observations, our method requires no manual feature tracking; it is automated, is quick to compute, and does not suffer the subjective biases associated with manual classifications. These results suggest we could possibly estimate solar wind speeds in the low heliosphere directly from HI observations. This motivates further investigation, as this could be a significant asset to the space weather forecasting community; it might provide an independent observational constraint on heliospheric solar wind forecasts, through, for example, data assimilation. Finally, these results are another argument for the potential utility of including a HI on an operational space weather mission.

Beschreibung: Abstract We analyse the response of different ionospheric equivalent current modes to variations in the interplanetary magnetic field (IMF) components By and Bz. Each mode comprises a fixed spatial pattern whose amplitude varies in time, identified by a month‐by‐month empirical orthogonal function separation of surface measured magnetic field variance. Here we focus on four sets of modes that have been previously identified as DPY, DP2, NBZ and DP1. We derive the cross‐correlation function of each mode set with either IMF By or Bz for lags ranging from ‐10 to +600 mins with respect to the IMF state at the bow shock nose. For all four sets of modes, the average correlation can be reproduced by a sum of up to three linear responses to the IMF component, each centered on a different lag. These are interpreted as the statistical ionospheric responses to magnetopause merging (15‐20 mins lag) and magnetotail reconnection (60 mins lag), and to IMF persistence. Of the mode sets, NBZ and DPY are the most predictable from a given IMF component, with DP1 (the substorm component) the least predictable. The proportion of mode variability explained by the IMF increases for the longer lags, thought to indicate conductivity feedbacks from substorms. In summary, we confirm the postulated physical basis of these modes and quantify their multiple reconfiguration timescales.

Beschreibung: Abstract Taking advantage of the public Global Navigational Satellite Systems (GNSS) infrastructure in South America, an operational monitoring system for the total electron content (TEC) in the ionosphere has been developed. It incorporates data in near real time, from more than 90 GNSS satellites tracked by more than 200 ground stations. In turn, the system produces every 15 min a snapshot, that is a map, of the current state of the regional ionosphere, which is immediately available online. These maps could be employed, for example, to augment positioning with single‐frequency GNSS receivers. They could also be combined with similar products in order to obtain weighted and reliable regional TEC maps, even in near real time. Most importantly, these products could be employed as data input in space environment forecasting and nowcasting models, given their very short latency of just a few minutes. In order to assess the response of the whole system to severe geomagnetic disturbances, the performance of the whole monitoring system during an actual geomagnetic storm has been investigated. The results suggest that the near‐real‐time system should be quite capable to monitor the regional TEC at a high temporal rate even under such conditions.

Beschreibung: Abstract We report an extreme erosion of the plasmasphere arising from the September 2017 storm. The cold electron density is identified from the upper limit frequency of upper hybrid resonance waves observed by the Plasma Wave Experiment instrument onboard the Exploration of energization and Radiation in Geospace/Arase satellite. The electron density profiles reveal that the plasmasphere was severely eroded during the recovery phase of the storm and the plasmapause was located at L = 1.6–1.7 at 23 UT 8 September 2017. This is the first report of deep erosion of the plasmasphere (LPP 〈 2) with the in situ observation of the electron density. The degree of the severity is much more than what is expected from the relatively moderate value of the SYM‐H minimum (−146 nT). We attempt to find a possible explanation for the observed severe depletion by using both observational evidence and numerical simulations. Our results suggest that the middle latitude electric field had penetrated from the high‐latitude storm time convection for several hours. Such an unusually long‐lasting penetration event can cause this observed degree of severity.

Beschreibung: Abstract At geosynchronous Earth orbit, the radiation belt/ring current electron fluxes with energies up to several hundred kiloelectron volts can vary widely in magnetic local time (MLT). This study aims to develop Nonlinear AutoRegressive eXogenous models using system science techniques, which account for the spatial variation in MLT. This is difficult for system science techniques, since there is sparse data availability of the electron fluxes at different MLT. To solve this problem, the data are binned from Geostationary Operational Environmental Satellites (GOES) 13, 14, and 15 by MLT, and a separate Nonlinear AutoRegressive eXogenous model is deduced for each bin using solar wind variables as the inputs to the model. These models are then conjugated into one spatiotemporal forecast. The model performance statistics for each model varies in MLT with a prediction efficiency between 47% and 75% and a correlation coefficient between 51.3% and 78.9% for the period from 1 March 2013 to 31 December 2017.

Beschreibung: Abstract An analysis of noise attenuation during 80 solar flares between 2013 and 2017 was carried out at frequencies 8–20 MHz using 34 Super Dual Auroral Radar Network radars and the EKB ISTP SB RAS radar. The attenuation was determined on the basis of noise measurements performed by the radars during the intervals between transmitting periods. The location of the primary contributing ground sources of noise was found by consideration of the propagation paths of radar backscatter from the ground. The elevation angle for the ground echoes was determined through a new empirical model. It was used to determine the paths of the noise and the location of its source. The method was particularly well suited for daytime situations, which had to be limited for the most part to only two crossings through the D region. Knowing the radio path was used to determine an equivalent vertical propagation attenuation factor. The change in the noise during solar flares was correlated with solar radiation lines measured by GOES/XRS, GOES/EUVS, SDO/AIA, SDO/EVE, SOHO/SEM, and PROBA2/LYRA instruments. Radiation in the 1 to 8 Å and near 100 Å are shown to be primarily responsible for the increase in the radionoise absorption, and by inference, for an increase in the D and E region density. The data are also shown to be consistent with a radar frequency dependence having a power law with an exponent of −1.6. This study shows that a new data set can be made available to study D and E regions.

Beschreibung: Abstract We investigate how statistical properties of the rate of change R of the surface horizontal magnetic field in the United Kingdom differ during substorm expansion and recovery phases compared with other times. R is calculated from 1‐min magnetic field data from three INTERMAGNET observatories—Lerwick, Eskdalemuir, and Hartland and between 1996 and 2014—nearly two solar cycles. Substorm expansion and recovery phases are identified from the SuperMAG Lower index using the Substorm Onsets and Phases from Indices of the Electrojet method. The probability distribution of R is decomposed into categories of whether during substorm expansion and recovery phases, in enhanced convection intervals, or at other times. From this, we find that 54–56% of all extreme R values (defined as above the 99.97th percentile) occur during substorm expansion or recovery phases. By similarly decomposing the magnetic local time variation of the occurrence of large R values (〉99th percentile), we deduce that 21–25% of large R during substorm expansion and recovery phases are attributable to the Disturbance Polar (DP)1 magnetic perturbation caused by the substorm current wedge. This corresponds to 10–14% of all large R in the entire data set. These results, together with asymptotic trends in occurrence probabilities, may indicate the two‐cell DP2 magnetic perturbation caused by magnetospheric convection as the dominant source of hazardous R 〉 600 nT/min that is potentially damaging to the U.K. National Grid. Thus, further research is needed to understand and model DP2, its mesoscale turbulent structure, and substorm feedbacks in order that GIC impact on the National Grid may be better understood and predicted.

Beschreibung: Abstract Historically, gathering data on atmospheric radiation levels during solar particle events has been difficult, as there is little or no time warning of events. Being able to accurately quantify radiation levels within the atmosphere during solar events is of significance to the aviation industry, as described in the International Civil Aviation Organization's (ICAO) Space Weather manual. Particularly during a large ground‐level enhancement (GLE) where the ionizing dose to passengers and crew can exceed the recommended general public annual dose limits, set by the International Commission for Radiological Protection (Barlett, Beck, Bilski, Bottollier‐Depois, & Lindborg, 2004, https://doi.org/10.1093/rpd/nch232), in a single flight. The Smart Atmospheric Ionizing RAdiation (SAIRA) Monitoring Network is a new system of handheld radiation detectors that can be carried on aircraft to monitor and record atmospheric radiation levels. The system operates via citizen science volunteers, who record radiation data as they travel for normal purposes. Over 30 flights have been conducted with volunteers to demonstrate that a citizen science network is possible. Volunteers have used a new Android application to record and upload data to a central server to form a database of flight measurements. The demonstration has shown that there is a willingness in public volunteers to use radiation detectors and engage in science outreach. A fully developed system will ideally provide the capability to quantify radiation levels during a solar particle event or ground‐level enhancement and the data can be used by relevant organizations to minimize potential risks.

Beschreibung: Abstract We present the observational and modeling study focused on the major factors determining the spatio‐temporal structure of the high‐latitude ionospheric plasma density enhancement – the tongue of ionization (TOI) structure – during the 2015 St. Patrick's Day geomagnetic storm. We use the Global Self‐consistent Model of the Thermosphere, Ionosphere, Protonosphere (GSM TIP model) to reproduce the plasma density distribution, and the results are compared with the observational data as deduced from the ground‐based GPS TEC and in situ plasma probe measurements at different altitudes. Both the simulation and observation results show that a large‐scale TOI‐like structure of enhanced plasma density extends from the dayside mid‐latitude region towards the central polar cap along the anti‐sunward cross‐polar convection flow. We reveal an important role of the clockwise convection cells rotation for the modification of TOI structure. According to model results during the storm main phase, the neutral thermospheric composition, particularly the “tongue” in n(N2) modifies the spatial structure of TOI in such a way that: (1) the near‐pole region of enhanced plasma density is shifted to the dusk side; (2) at F region heights, the TOI is split into the dusk and dawn branches. The signature of TOI in the topside ionosphere considerably differs from that in the F region because of a lesser influence of the neutral composition changes at higher altitudes. Model results revealed that at plasmaspheric heights, the TOI structure appears in both the dawn and dusk convection cells.

Beschreibung: Abstract In this paper, a procedure for updating the International Reference Ionosphere (IRI) model by means of assimilated vertical total electron content (vTEC) measurements from a Global Navigational Satellite Systems (GNSS) receiver network is presented. This procedure stands as an additional implementation of the IRI UPdate (IRI UP) method which is based on the assimilation of ionosonde derived F2 layer ionospheric characteristics. According to this, a mathematical procedure for obtaining foF2 and M(3000)F2 values from vTEC measurements is here proposed. Mathematical relationships between F2 layer characteristics and vTEC values have been derived using South‐African co‐located ionosonde and GNSS stations. The same procedure can however be applied successfully in each region where such data are available. The goodness of the proposed IRI UP method, based on assimilated vTEC values, has been tested for several quiet and disturbed days in 2017 and 2018. IRI UP exhibits better performances than IRI for foF2, for most of the analyzed cases. Slight improvements are achieved in modeling hmF2 only for very disturbed periods in 2017. Due to the very good coverage of the terrestrial surface that GNSS receivers have achieved in recent years, we suggest that the method proposed here can be a good implementation of the IRI model for Space Weather nowcasting purposes, at least for foF2.

Beschreibung: Abstract For the purpose of building a regional (bound 20°‐60° N in latitude and 110°‐160° E in longitude) ionospheric now‐cast model, we investigated the performance of IDA4D (Ionospheric Data Assimilation Four‐Dimension) technique considering IRI (International Reference Ionosphere) model as the background. The data utilized in assimilation were slant total electron content (STEC) from twenty‐seven ground GPS (Global Positioning System) receiver stations, and NmF2 (ionospheric F2 peak density) from five ionosondes and COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) Data Analysis Archive Center. The period analyzed covered both geomagnetic quiet and disturbed days (15‐18 March, 2015). Assimilations were run under the following data combinations (cases): (1) GPS‐STEC's only; (2) GPS‐STEC's and NmF2's from five ionosondes; (3) only NmF2's from five ionosondes; and (4) GPS‐STEC's and NmF2's from both five ionosondes and COSMIC. Results showed that under case 1 the root‐mean‐square error (RMSE) in STEC reduced by 44% over the background IRI values, and on averaged over all ionosonde stations in the analysis RMSE values of foF2 (F2‐layer critical frequency) reduced by 21%. Furthermore, foF2 RMSE values under case 2 were 36% smaller than those under case 1. Under case 4, IDA4D performance improved even further in areas not covered by GPS and ionosonde measurements. Therefore, IDA4D is a potential candidate for regional ionosphere modeling that exhibits improved performance with assimilation of different data types.

Beschreibung: Abstract During the recovery of a magnetic storm, the relativistic electrons at MeV energy from the outer radiation belt will be enhanced at the geosynchronous orbit. In particular, the 〉2 MeV electrons could penetrate the surface of satellites and accumulate inside. After a long period, such an electron flux effect could cause satellites to be unable to function properly or to fail completely. Unlike previous prediction models of relativistic electrons focusing mainly on forecasting the daily value, we have developed an hourly prediction model to learn more detailed changes. In addition, due to external forcing by the solar wind, relativistic electron flux changes rapidly and is very non‐stationary during magnetic storms. We use the method of Empirical Mode Decomposition to reduce these effects. The result shows that the average prediction efficiency of hourly predictions of relativistic electrons from 2001 to 2006 is approximately 0.73. Moreover, we use this method to forecast daily fluence to validate Empirical Mode Decomposition. The prediction efficiency of daily fluence from 2001 to 2006 is 0.80, and for the period in which the relativistic electrons change particularly rapidly during 2001‐2004, the prediction efficiency is 0.79. Meanwhile, we compare with the prediction values without using Empirical Mode Decomposition. The result shows a great improvement using this method. Furthermore, it shows the non‐stationary nature of the electron flux time series has a great impact on the prediction of relativistic electrons.

Beschreibung: Abstract We present a statistical study of interplanetary conditions and geospace response to 89 coronal mass ejection (CME)‐driven sheaths observed during Solar Cycles 23 and 24. We investigate in particular the dependencies on the driver properties and variations across the sheath. We find that the ejecta speed principally controls the sheath geoeffectiveness and shows the highest correlations with sheath parameters, in particular in the region closest to the shock. Sheaths of fast ejecta have on average high solar wind speeds, magnetic (B)‐field magnitudes, and fluctuations and they generate efficiently strong out‐of‐ecliptic fields. Slow‐ejecta sheaths are considerably slower, have weaker fields and field fluctuations and therefore they cause primarily moderate geospace activity. Sheaths of weak and strong B‐field ejecta have distinct properties but differences in their geoeffectiveness are less drastic. Sheaths of fast and strong ejecta push the subsolar magnetopause significantly earthward, often even beyond geostationary orbit. Slow‐ejecta sheaths also compress the magnetopause significantly due to their large densities that likely result of their relatively long propagation times and source near the streamer belt. We find the regions near the shock and ejecta leading edge to be the most geoeffective parts of the sheath. These regions are also associated with the largest B‐field magnitudes, out‐of‐ecliptic fields, and field fluctuations as well as largest speeds and densities. The variations, however, depend on driver properties. Forecasting sheath properties is challenging due to their variable nature, but the dependence on ejecta properties determined in this work could help to estimate sheath geoeffectiveness through remote‐sensing CME observations.

Beschreibung: Abstract The Community Coordinated Modeling Center (CCMC) has been leading community‐wide space science and space weather model validation projects for many years. These efforts have been broadened and extended via the newly‐launched International Forum for Space Weather Modeling Capabilities Assessment (https://ccmc.gsfc.nasa.gov/assessment/). Its objective is to track space weather models’ progress and performance over time, a capability that is critically needed in space weather operations and different user communities in general. The Space Radiation and Plasma Effects Working Team of the aforementioned International Forum works on one of the many focused evaluation topics and deals with five different subtopics (https://ccmc.gsfc.nasa.gov/assessment/topics/radiation‐all.php) and varieties of particle populations: Surface Charging from 10s eV to 40 keV electrons, Internal Charging due to energetic electrons from hundreds keV to several MeVs. Single Event Effects from Solar Energetic Particles (SEPs) and Galactic Cosmic Rays (GCRs) (several MeV to TeVs), Total Dose due to accumulation of doses from electrons (〉100 KeV) and protons (〉 1 MeV) in a broad energy range, and Radiation Effects from SEPs and GCRs at aviation altitudes. A unique aspect of the Space Radiation and Plasma Effects focus area is that it bridges the space environments, engineering and user communities. The intent of the paper is to provide an overview of the current status and to suggest a guide for how to best validate space environment models for operational/engineering use, which includes selection of essential space environment and effect quantities and appropriate metrics.

Beschreibung: Abstract The space environment near Earth is constantly subjected to changes in the solar wind flow generated at the Sun. Examples of this variability are the occurrence of powerful solar disturbances, such as coronal mass ejections (CMEs). The impact of CMEs on the Earth's magnetosphere perturbs the geomagnetic field causing the occurrence of geomagnetic storms. Such extremely variable geomagnetic fields trigger geomagnetic effects measurable not only in the geospace but also in the ionosphere, upper atmosphere, and on the ground. For example, during extreme events, rapidly changing geomagnetic fields generate intense geomagnetically induced currents (GICs). In recent years, GIC impact on the power networks at middle and low latitudes has attracted attention due to the expansion of large‐scale power networks into these regions. This paper presents a new model, called MA.I.GIC. (Magnetosphere ‐ Ionosphere ‐ Ground Induced Current), to derive the geoelectric field used to determine the magnitude of GICs. In addition, we discuss the results of the MA.I.GIC. model applied to the September 2017 Geomagnetic Storm with particular focus on the two sudden impulses occurring on September 6 and 7, 2017, and the two main phases on September 7 and 8, 2017.

Beschreibung: Abstract Geomagnetic field variations recorded by fluxgate magnetometers are used to evaluate geomagnetically induced currents (GICs) under the equatorial electrojet (EEJ) and South Atlantic Magnetic Anomaly (SAMA) during two geomagnetic storms in March and June 2015. Geomagnetic stations with information about the underground electrical conductivity structure and that can be approximated by unidimensional (1‐D) models for calculation of the geoelectric field are selected. GICs levels are estimated using a realistic local power grid model located in the central region of Brazil, artificially moved to the sites where the geomagnetic measurements are available. GIC magnitudes are not large during the storms, and a maximum amplitude of 3.8 A was estimated at an equatorial station positioned over high resistivity underground during the main phase of the June storm. Effects of the ionospheric currents over the measurement sites and of the conductivity distribution beneath these sites are also evaluated. It is observed that both (EEJ) and (SAMA) increase the GICs amplitudes, with the greatest effects associated with daytime (EEJ) currents. A cutoff frequency was identified for both the (EEJ) and (SAMA) so that signals with frequencies lower than 2 mHz (periods longer than 500 s) are not amplified by the ionospheric currents. In relation to the underlying conductivity structure, GIC magnitude is affected by variation of the surface impedance and the sampling rate of the geomagnetic field. In our case, differences in amplitude of the surface impedance at the Nyquist frequency control the relative effects of the ground conductance between the stations.

Beschreibung: Abstract An accurate understanding of space weather socioeconomic impact is fundamental to the development of appropriate operational services, forecasting capabilities, and mitigation strategies. One way to approach this problem is by developing physics‐based models and frameworks that can lead to a bottom‐up estimate of risk and likely impact. Here we describe the development of a new framework to assess the economic impact of space weather on power distribution networks and the supply of electricity. In particular, we focus on the phenomenon of the geomagnetic substorm, which is relatively localized in time and space, and occurs multiple times with varying severity during a geomagnetic storm. The framework uses the AE index to characterize substorm severity, and the impact of the substorm is modulated by the resilience of the power grid and the nature of available forecast. Possible scenarios for substorm sequences during a 1‐in‐10‐, a 1‐in‐30‐, and a 1‐in‐100‐year geomagnetic storm events are generated based on the 2003, 1989, and 1859 geomagnetic storms. Economic impact, including international spill over, can then be calculated using standard techniques, based on the duration and the geographical footprint of the power outage. Illustrative calculations are made for the European sector, for a variety of forecast and resilience scenarios. However, currently available data are highly regionally inhomogeneous, frustrating attempts to define an overall global economic impact at the present time.

Beschreibung: Abstract Magnetic storms are the most prominent global manifestations of out‐of‐equilibrium magnetospheric dynamics. Investigating the dynamical complexity exhibited by geomagnetic observables can provide valuable insights into relevant physical processes as well as temporal scales associated with this phenomenon. In this work, we utilize several innovative data analysis techniques enabling a quantitative nonlinear analysis of the nonstationary behavior of the disturbance storm time (Dst) index together with some of the main drivers of its temporal variability, the VBSouth electric field component, the vertical component of the interplanetary magnetic field, Bz, and the dynamic pressure of the solar wind, Pdyn. Using recurrence quantification analysis and recurrence network analysis, we obtain several complementary complexity measures that serve as markers of different physical processes underlying quiet and storm time magnetospheric dynamics. Our approach discriminates the magnetospheric activity in response to external (solar wind) forcing from primarily internal variability and highlights the case‐specific nature of interdependencies between the Dst index and its potential drivers that need to be accounted for in future improved space weather forecasting models.

Beschreibung: Abstract This work designs a new model called PreMevE to predict storm‐time distributions of relativistic electrons within Earth's outer radiation belt. This model takes advantage of the cross‐energy, ‐L‐shell, and –pitch‐angle coherence associated with wave‐electron resonant interactions, ingests observations from belt boundaries—mainly by NOAA POES in low‐Earth‐orbits (LEOs), and provides high‐fidelity nowcast (multiple‐hour prediction) and forecast (〉 ~1 day) of MeV electron fluxes over L‐shells between 2.8‐7 through linear prediction filters. PreMevE can not only reliably anticipate incoming enhancements of MeV electrons during storms with at least 1‐day forewarning time, but also accurately specify the evolving event‐specific electron spatial distributions afterwards. The performance of PreMevE is assessed against long‐term in situ data from one Van Allen Probe and a LANL geosynchronous satellite. This new model enhances our preparedness for severe MeV electron events in the future, and further adds new science utility to existing and next‐generation LEO space infrastructure.

Beschreibung: Abstract Spacecraft surface charging during geomagnetically disturbed times is one of the most important causes of satellite anomalies. Predicting the surface charging environment is one prevalent task of the geospace environment models. Therefore, the Geospace Environment Modeling (GEM) Focus Group “Inner Magnetosphere Cross‐energy/Population Interactions” initiated a community‐wide challenge study to assess the capability of several inner magnetosphere ring current models in determining surface charging environment for the Van Allen Probes orbits during the 17 March 2013 storm event. The integrated electron flux between 10 and 50 keV is used as the metrics. Various skill scores are applied to quantitatively measure the modeling performance against observations. Results indicate that no model consistently perform the best in all of the skill scores or for both satellites. We find that from these simulations the ring current model with observational flux boundary condition and Weimer electric potential driver generally reproduces the most realistic flux level around the spacecraft. A simple and weaker Volland‐Stern electric field is not capable of effectively transporting the same plasma at the boundary toward the Earth. On the other hand, if the ring current model solves the electric field self‐consistently and obtains similar strength and pattern in the equatorial plane as the Weimer model, the boundary condition plays another crucial role in determining the electron flux level in the inner region. When the boundary flux spectra based on magnetohydrodynamics (MHD) model/empirical model deviate from the shape or magnitude of the observed distribution function, the simulation produces poor skill scores along Van Allen Probes orbits.

Beschreibung: Abstract An interval of exceptional solar activity was registered in early September 2017, late in the decay phase of solar cycle 24, involving the complex Active Region 12673 as it rotated across the western hemisphere with respect to Earth. A large number of eruptions occurred between 4–10 September, including four associated with X‐class flares. The X9.3 flare on 6 September and the X8.2 flare on 10 September are currently the two largest during cycle 24. Both were accompanied by fast coronal mass ejections and gave rise to solar energetic particle (SEP) events measured by near‐Earth spacecraft. In particular, the partially‐occulted solar event on 10 September triggered a ground level enhancement (GLE), the second GLE of cycle 24. A further, much less energetic SEP event was recorded on 4 September. In this work we analyze observations by the Advanced Composition Explorer (ACE) and the Geostationary Operational Environmental Satellites (GOES), estimating the SEP event‐integrated spectra above 300 keV and carrying out a detailed study of the spectral shape temporal evolution. Derived spectra are characterized by a low‐energy break at few/tens of MeV; the 10 September event spectrum, extending up to ∼1 GeV, exhibits an additional rollover at several hundred MeV. We discuss the spectral interpretation in the scenario of shock acceleration and in terms of other important external influences related to interplanetary transport and magnetic connectivity, taking advantage of multi‐point observations from the Solar Terrestrial Relations Observatory (STEREO). Spectral results are also compared with those obtained for the 17 May 2012 GLE event.

Beschreibung: Abstract Postsunset midlatitude traveling ionospheric disturbances (TIDs) and equatorial plasma bubbles (EPBs) were simultaneously observed over American sector during the geomagnetic storm on 8 September 2017. The characteristics of TIDs are analyzed by using a combination of the Millstone Hill incoherent scatter radar data and 2‐D detrended total electron content (TEC) from ground‐based Global Navigation Satellite System receivers. The main results associated with EPBs are as follows: (1) stream‐like structures of TEC depletion occurred simultaneously at geomagnetically conjugate points, (2) poleward extension of the TEC irregularities/depletions along the magnetic field lines, (3) severe equatorial and midlatitude electron density (Ne) bite outs observed by Defense Meteorological Satellite Program and Swarm satellites, and (4) enhancements of ionosphere F layer virtual height and vertical drifts observed by equatorial ionosondes near the EPBs initiation region. The stream‐like TEC depletions reached 46° magnetic latitudes that map to an apex altitude of 6,800 km over the magnetic equator using International Geomagnetic Reference Field. The formation of this extended density depletion structure is suggested to be due to the merging between the altitudinal/latitudinal extension of EPBs driven by strong prompt penetration electric field and midlatitude TIDs. Moreover, the poleward portion of the depletion/irregularity drifted westward and reached the equatorward boundary of the ionospheric main trough. This westward drift occurred at the same time as the sudden expansion of the convection pattern and could be attributed to the strong returning westward flow near the subauroral polarization stream region. Other possible mechanisms for the westward tilt are also discussed.

Beschreibung: Abstract We study how the probability distribution functions of power input to the magnetosphere Pα and of the geomagnetic ap and Dst indices vary with averaging timescale, τ, between 3 hr and 1 year. From this we develop and present algorithms to empirically model the distributions for a given τ and a given annual mean value. We show that lognormal distributions work well for ap, but because of the spread of Dst for low activity conditions, the optimum formulation for Dst leads to distributions better described by something like the Weibull formulation. Annual means can be estimated using telescope observations of sunspots and modeling, and so this allows the distributions to be estimated at any given τ between 3 hr and 1 year for any of the past 400 years, which is another important step toward a useful space weather climatology. The algorithms apply to the core of the distributions and can be used to predict the occurrence rate of large events (in the top 5% of activity levels): they may contain some, albeit limited, information relevant to characterizing the much rarer superstorm events with extreme value statistics. The algorithm for the Dst index is the more complex one because, unlike ap, Dst can take on either sign and future improvements to it are suggested.

Beschreibung: Abstract The article “The Global Oscillation Network Group (GONG) Facility ‐ An Example of Research to Operations in Space Weather” by Frank Hill (https://doi.org/10.1029/2018SW002001) narrates how an instrument built for answering questions of basic research is playing a greater role in the field of space weather. In the past 25 years, the project has successfully produced fundamental results that have helped to fine‐tune stellar structure models and have resolved several outstanding problems in stellar physics. It is also important to know the background coronal and solar wind environment in order to understand and adequately predict the transient events as this is the environment through which they propagate. The GONG magnetograms are useful as boundary conditions to construct the large‐scale magnetic field structure of the heliosphere and at times to detect the change in longitudinal field due to the solar flares. In order to advance the Space Weather prediction tools, it is necessary to study the magnetic and thermodynamic properties of the source regions of the transient events. The rich information contained in the polarized spectra originating at these locations that is currently measured by the "Synoptic Optical Long‐term Investigations of the Sun" (SOLIS) instrument are most appropriate for this purpose. Although, GONG magnetograms have been, and continue to be, useful in understanding some aspects of Space Weather, there remains a need for new solar observing capabilities aimed at better understanding the "Transient Sun". In this commentary, we describe the need for a GONG upgrade that will fully serve the Space Weather Community.

Beschreibung: Abstract Geoelectric fields at the Earth's surface caused by geomagnetic storms have the potential to disrupt and damage ground‐based infrastructure such as electrical power distribution networks, pipelines, and railways. Here we model geoelectric fields in Ireland and the UK during both quiet and active time intervals of geomagnetic conditions using measurements from magnetic observatories and electromagnetic tensor relationships. The analysis focused on (1) defining periods of the magnetic field variations that are largely affected by the geomagnetic storms, between 30 and 30,000 s; (2) constraining the electromagnetic tensor relationships that defines the Earth's response to magnetic field variations; (3) implementing and validating two approaches for modeling geoelectric fields based on measurements from magnetic observatories and local and interstation electromagnetic transfer functions; and (4) estimating uncertainties when modeling geoelectric fields. The use of interstation tensor relationships allowed us to differentiate between regional and local geomagnetic sources. We found coherence values of 0.5–0.95, signal‐to‐noise ratio of 1–15 dB, normalized root‐mean‐square values of 0.8–3.4, and root‐mean‐square values of 0.7–84 mV/km. Within these ranges of values, sites in close proximity (〈100 km) to a magnetic observatory and not affected by local storms will provide the most accurate results, while sites located at further distances and affected by spatially localized features of the storm will be less accurate. These methods enable us to more accurately model geomagnetically induced currents, and their associated uncertainties, in the British and Irish power networks.

Beschreibung: Abstract A new, rapid, nonassimilative technique is demonstrated for forecasting the ionosphere's vertical total electron content (TEC) on time scales longer than 1 day. The approach uses a statistical model constructed by regressing solar extreme ultraviolet irradiance and seasonal, diurnal, and geomagnetic predictors at multiple lags against the 2‐hourly International Global Navigation Satellite Systems Service observations, with a formulation that accounts for solar modulation of the seasonal oscillations and solar and seasonal modulation of the diurnal oscillations. Solar irradiance inputs to the statistical model are forecast at successive 2‐hr intervals from 1999 to 2015 using an autoregressive model of irradiance variations during the prior 100 days. As the forecast time increment increases from 1 to 10 days, the average over the globe of the mean absolute error of TEC observations and the forecasts increases from 2.5 to 3.2 TECU (total electron content unit, 1 TECU = 1016 el/m2); the root‐mean‐square error increases from 3.7 to 4.8 TECU. Averaged over the equatorial ionization anomaly region (30°S–30°N) the mean absolute error of the forecasts increases from 3.2 to 4.3 TECU and the root‐mean‐square error increases from 4.6 to 6.4 TECU. The skill of the TEC forecasts at time increments of 3, 5, and 8 days ahead exceeds persistence by 9%, 13%, and 15% and climatology by 9%, 12%, and 10%, respectively. Forecast skill is higher in April than in July. Long‐range, multiyear forecasts from 2018 to 2030 are demonstrated based on current expectations that solar activity in cycle 25 will be comparable to that in cycle 24.

Beschreibung: Abstract As part of its International Capabilities Assessment effort, the Community Coordinated Modeling Center initiated several working teams, one of which is focused on the validation of models and methods for determining auroral electrodynamic parameters, including particle precipitation, conductivities, electric fields, neutral density and winds, currents, Joule heating, auroral boundaries, and ion outflow. Auroral electrodynamic properties are needed as input to space weather models, to test and validate the accuracy of physical models, and to provide needed information for space weather customers and researchers. The working team developed a process for validating auroral electrodynamic quantities that begins with the selection of a set of events, followed by construction of ground truth databases using all available data and assimilative data analysis techniques. Using optimized, predefined metrics, the ground truth data for selected events can be used to assess model performance and improvement over time. The availability of global observations and sophisticated data assimilation techniques provides the means to create accurate ground truth databases routinely and accurately.

Beschreibung: Abstract Most of the methods that produce space weather forecasts are based on deterministic models. In order to generate a probabilistic forecast, a model needs to be run several times sampling the input parameter space, in order to generate an ensemble from which the distribution of outputs can be inferred. However, ensemble simulations are costly and often preclude the possibility of real‐time forecasting. We introduce a simple and robust method to generate uncertainties from deterministic models, that does not require ensemble simulations. The method is based on the simple consideration that a probabilistic forecast needs to be both accurate and well‐calibrated (reliable). We argue that these two requirements are equally important, and we introduce the Accuracy‐Reliability cost function that quantitatively measures the trade‐off between accuracy and reliability. We then define the optimal uncertainties as the standard deviation of the Gaussian distribution that minimizes the cost function. We demonstrate that this simple strategy, implemented here by means of a regularized deep neural network, produces accurate and well‐calibrated forecasts, showing examples both on synthetic and real‐world space weather data.

Beschreibung: Abstract A series of coronal mass ejections (CMEs) erupted from the same active region between 4–6 September 2017. Later, on 6–9 September, two interplanetary (IP) shocks reached L1, creating a complex and geoeffective plasma structure. To understand the processes leading up to the formation of the two shocks, we model the CMEs with the Wang‐Sheeley‐Arge (WSA)‐ENLIL+Cone model. The first two CMEs merged already in the solar corona driving the first IP shock. In IP space, another fast CME presumably interacted with the flank of the preceding CMEs and caused the second shock detected in situ. By introducing a customized density enhancement factor (dcld) in the WSA‐ENLIL+Cone model based on coronagraph image observations, the predicted arrival time of the first IP shock was drastically improved. When the dcld factor was tested on a well‐defined single CME event from 12 July 2012 the shock arrival time saw similar improvement. These results suggest that the proposed approach may be an alternative to improve the forecast for fast and simple CMEs. Further, the slowly decelerating kilometric type II radio burst confirms that the properties of the background solar wind have been preconditioned by the passage of the first IP shock. This likely caused the last CME to experience insignificant deceleration and led to the early arrival of the second IP shock. This result emphasizes the need to take preconditioning of the IP medium into account when making forecasts of CMEs erupting in quick succession.

Beschreibung: Abstract Coronal Mass Ejections (CMEs) are the key drivers of strong to extreme space weather storms at the Earth that can have drastic consequences for technological systems in space and on ground. The ability of a CME to drive geomagnetic disturbances depends crucially on the magnetic structure of the embedded flux rope, which is thus essential to predict. The current capabilities in forecasting in advance (at least half‐a‐day before) the geoeffectiveness of a given CME is however severely hampered by the lack of remote‐sensing measurements of the magnetic field in the corona and adequate tools to predict how CMEs deform, rotate and deflect during their travel through the coronal and interplanetary space as they interact with the ambient solar wind and other CMEs. These problems can lead not only to over‐ or underestimation of the severity of a storm, but also to forecasting “misses" and “false alarms" that are particularly difficult for the end‐users. In this paper, we discuss the current status and future challenges and prospects related to forecasting of the magnetic structure and orientation of CMEs. We focus both on observational and modeling (first‐principle and semi‐empirical) based approaches, and discuss the space‐ and ground‐based observations that would be the most optimal for making accurate space weather predictions. We also cover the gaps in our current understanding related to the formation and eruption of the CME flux rope and physical processes that govern its evolution in the variable ambient solar wind background that complicate the forecasting. Plain‐language summary: Coronal Mass Ejections (CMEs) are gigantic magnetized plasma clouds that are frequently expelled from the Sun. Practically all strong and extreme space weather disturbances in the near‐Earth space environment are caused by CMEs that propagate in a few days from the Sun to the Earth. Space weather disturbances are related to various harmful effects to modern technology both in space and on ground which can lead to substantial economic losses. Forecasting the CME properties at least half a day before their impact on Earth is thus essential for our society. Our ability to provide accurate predictions of space weather consequences of CMEs is however currently quite modest. The key challenges are related to observational and modeling limitations, and complex evolution CMEs may experience as they propagate from Sun to Earth. This paper discusses the current status and future prospect in forecasting key CME properties using both observations and simulations.

Beschreibung: Abstract Accurate determination of thermospheric neutral density holds crucial importance for satellite drag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and three physics‐based models of the ionosphere‐thermosphere are compared with the neutral densities along the Challenging Micro‐Satellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias), (2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set of metrics for the neutral density.

Beschreibung: Abstract In deep space, personnel and equipment are exposed to the space radiation environment in the form of energetic particles, specifically Galactic Cosmic Rays and sporadic Solar Energetic Particle events. Radiation fields resulting from these particles are modified by shielding, but most radiation measurements in deep space have been made with detectors that were unshielded or very lightly shielded. In contrast, the space radiation environment on the International Space Station (ISS) is more complicated, with time‐dependent modification of the incident flux by the geomagnetic field and complex bulk shielding distributions; measured particle spectra inside the ISS are affected by both types of shielding. The geomagnetic field is also responsible for the existence of the South Atlantic Anomaly, a region of trapped energetic protons and electrons, and hence enhanced radiation dose, through which the ISS travels several times per day on average. Here, our primary aim is to compare charged particle spectra at high linear energy transfer (LET) obtained by the ALTEA (Anomalous Long‐Term Effects in Astronauts) instrument on ISS during high‐latitude portions of the orbit to data acquired at the same time by the Cosmic Ray Telescope for the Effects of Radiation and Radiation Assessment Detector instruments, both in deep space. The hypothesis being tested is that these spectra are the same, modulo shielding differences, since the effects of the geomagnetic field are expected to be minimal at high latitudes.

Beschreibung: Abstract Precision and safety of life applications of Global Navigation Satellite Systems require key information on space weather conditions in particular on the perturbation degree of the ionosphere. Such systems are particularly vulnerable against severe spatial gradients and rapid changes of the total electron content (TEC) measured along different satellite‐receiver links. To estimate spatial gradients and rapid temporal variations of ionospheric TEC, two approaches are discussed. The Gradient Ionosphere indeX (GIX) and the Sudden Ionospheric Disturbance indeX are able to estimate the perturbation degree of the ionosphere instantaneously without taking into account previous measurements. The capabilities and accuracy of the index approaches are demonstrated by simulations using a 3‐D electron density model of the ionosphere and plasmasphere in conjunction with realistic Global Navigation Satellite Signal constellations. Real data tests confirm the applicability of GIX and the related standard deviation GIX Sigma to monitor spatial gradients. Sudden Ionospheric Disturbance indeX is able to monitor rapid temporal variations of TEC as exemplified by using Global Navigation Satellite Signal measurements carried out during solar flare events. Both approaches could identify enhanced space weather impacts on precise point positioning and the European Geostationary Navigation Overlay Service. More comprehensive studies analyzing ionospheric storms in close dialogue with potential customers are needed to fully utilize the potential of these approaches to serve as objective ionospheric indices for scaling horizontal TEC gradients and rapid TEC variations in space weather services.

Beschreibung: Abstract Metrics are an objective, quantitative assessment of forecast (or model) agreement with observations. They are essential for assessing forecast accuracy and reliability and consequently act as a diagnostic for forecast development. Partly as a result of limited spatial sampling of observations, much of space‐weather forecasting is focused on the time domain rather than inherent spatial variability. Thus, metrics are primarily point‐by‐point approaches, in which observed conditions at time t are compared directly (and only) with the forecast conditions at time t. Such metrics are undoubtedly useful. But in lacking an explicit consideration of timing uncertainties, they have limitations as diagnostic tools and can, under certain conditions, be misleading. Using a near‐Earth solar wind speed forecast as an illustrative example, this study briefly reviews the most commonly used point‐by‐point metrics and advocates for complementary time window approaches. In particular, a scale‐selective approach, originally developed in numerical weather prediction for validation of spatially patchy rainfall forecasts, is adapted to the time domain for space‐weather purposes. This simple approach readily determines the time scales over which a forecast is and is not valuable, allowing the results of point‐by‐point metrics to be put in greater context.

Beschreibung: Abstract Magnetospheric substorms represent key explosive processes in the interaction of the Earth's magnetosphere with the solar wind, and their understanding and modeling are critical for space weather forecasting. During substorms, the magnetic field on the nightside is first stretched in the antisunward direction and then it rapidly contracts earthward bringing hot plasmas from the distant space regions into the inner magnetosphere, where they contribute to geomagnetic storms and Joule dissipation in the polar ionosphere, causing impressive splashes of aurora. Here we show for the first time that mining millions of spaceborne magnetometer data records from multiple missions allows one to reconstruct the global 3‐D picture of these stretching and dipolarization processes. Stretching results in the formation of a thin (less than the Earth's radius) and strong current sheet, which is diverted into the ionosphere during dipolarization. In the meantime, the dipolarization signal propagates further into the inner magnetosphere resulting in the accumulation of a longer lived current there, giving rise to a protogeomagnetic storm. The global 3‐D structure of the corresponding substorm currents including the substorm current wedge is reconstructed from data.

Beschreibung: Abstract Severe geomagnetic storms caused by the solar wind disturbances have harmful influences on the operation of modern equipment and systems. The modeling and forecasting of AE index are extremely useful to understand the geomagnetic substorms. This study presents a novel cloud‐nonlinear autoregressive with exogenous input (NARX) model to predict AE index 1 hr ahead. The cloud‐NARX model provides AE index forecasting results, with a correlation coefficient of 0.87 on the data of whole year 2015. The benchmarks on the data of the two interested periods of 17–21 March 2015 and 22–26 June 2015 are presented. The presented model uses uncertainty “cloud” model and cloud transformation to quantify the uncertainty throughout the structure detection, parameter estimation, and model prediction. The new predicted band can be generated to forecast AE index with confidence interval. The proposed method provides a new way to evaluate the model based on uncertainty analysis, revealing the reliability of model, and visualize the bias of model prediction.

Beschreibung: Abstract Accurate forecasting of the arrival time and subsequent geomagnetic impacts of coronal mass ejections (CMEs) at Earth is an important objective for space weather forecasting agencies. Recently, the CME Arrival and Impact working team has made significant progress toward defining community‐agreed metrics and validation methods to assess the current state of CME modeling capabilities. This will allow the community to quantify our current capabilities and track progress in models over time. First, it is crucial that the community focuses on the collection of the necessary metadata for transparency and reproducibility of results. Concerning CME arrival and impact we have identified six different metadata types: 3‐D CME measurement, model description, model input, CME (non)arrival observation, model output data, and metrics and validation methods. Second, the working team has also identified a validation time period, where all events within the following two periods will be considered: 1 January 2011 to 31 December 2012 and January 2015 to 31 December 2015. Those two periods amount to a total of about 100 hit events at Earth and a large amount of misses. Considering a time period will remove any bias in selecting events and the event set will represent a sample set that will not be biased by user selection. Lastly, we have defined the basic metrics and skill scores that the CME Arrival and Impact working team will focus on.

Beschreibung: Abstract A new, rapid, nonassimilative technique is demonstrated for forecasting the ionosphere's vertical total electron content (TEC) on time scales longer than 1 day. The approach uses a statistical model constructed by regressing solar extreme ultraviolet irradiance and seasonal, diurnal, and geomagnetic predictors at multiple lags against the 2‐hourly International Global Navigation Satellite Systems Service observations, with a formulation that accounts for solar modulation of the seasonal oscillations and solar and seasonal modulation of the diurnal oscillations. Solar irradiance inputs to the statistical model are forecast at successive 2‐hr intervals from 1999 to 2015 using an autoregressive model of irradiance variations during the prior 100 days. As the forecast time increment increases from 1 to 10 days, the average over the globe of the mean absolute error of TEC observations and the forecasts increases from 2.5 to 3.2 TECU (total electron content unit, 1 TECU = 1016 el/m2); the root‐mean‐square error increases from 3.7 to 4.8 TECU. Averaged over the equatorial ionization anomaly region (30°S–30°N) the mean absolute error of the forecasts increases from 3.2 to 4.3 TECU and the root‐mean‐square error increases from 4.6 to 6.4 TECU. The skill of the TEC forecasts at time increments of 3, 5, and 8 days ahead exceeds persistence by 9%, 13%, and 15% and climatology by 9%, 12%, and 10%, respectively. Forecast skill is higher in April than in July. Long‐range, multiyear forecasts from 2018 to 2030 are demonstrated based on current expectations that solar activity in cycle 25 will be comparable to that in cycle 24.

Beschreibung: Abstract High‐intensity long‐duration continuous auroral electrojet activities (HILDCAAs) are recognized as the continuous (duration 〉2 days) auroral electrojet activities (AE 〉 1,000 nT) caused by interplanetary Alfvén waves driving magnetic reconnection at the Earth's magnetopause. This paper focuses on the study of geoeffectiveness of HILDCAA on the basis of associated geomagnetically induced currents (GICs) and pipe‐to‐soil voltage (PSV) observed in an underground pipeline at Finnish Natural Gas Station, Mäntsälä. In this study, 113 HILDCAAs with different interplanetary sources (72 corotating interaction region‐storm preceded, 29 interplanetary coronal mass ejection‐storm preceded, and 12 nonstorm) have been selected and their possible contributions in underground pipeline corrosion have been quantitatively compared by assessing GIC/PSV profiles for each of these events. In addition, the spectral characteristics of GIC during these events have been studied using continuous wavelet transforms. The Morlet wavelet has been applied to 10‐s modeled GIC data corresponding to each event to explore the main band structures and the periodicities found in GIC spectrum. GIC/PSV modeling is based on plane wave method and distributed source transmission line analogy between pipelines and electric circuits. HILDCAAs are found to drive a small‐amplitude, but continuous, fluctuation in GIC throughout the event duration of several days. This makes the cumulative effect of HILDCAAs in pipeline corrosion noteworthy. The spectral analysis shows that GIC possesses both short‐term, as well as continuous, power distribution with different periodicities. CIR‐preceded HILDCAAs are found to be more geoeffective while taking associated GIC and PSV into account. Possible physical explanations supporting the results have been presented.

Beschreibung: Abstract Coronal mass ejections (CMEs) are intense solar explosive eruptions. CMEs are highly important players in solar‐terrestrial relationships, and they have important consequences for major geomagnetic storms and energetic particle events. It has been unclear how CMEs evolve when they propagate in the heliosphere. Here we report an interplanetary CME consisting of multiple magnetic flux ropes measured by WIND on 25–26 March 1998. These magnetic flux ropes were merging with each other. The observations indicate that internal interactions (reconnections) within multiflux rope CME can coalesce into large‐scale ropes, which may improve our understanding of the interplanetary evolution of CMEs. In addition, we speculated that the reported rope‐rope interactions may also exist between successive rope‐like CMEs and are important for the space weather forecasting.

Beschreibung: Abstract The Cluster mission, launched in 2000, has produced a large database of electron flux intensity measurements in the Earth's magnetosphere by the Research with Adaptive Particle Imaging Detector (RAPID)/ Imaging Electron Spectrometer (IES) instrument. However, due to background contamination of the data with high‐energy electrons (〈400 keV) and inner‐zone protons (230‐630 keV) in the radiation belts and ring current, the data have been rarely used for inner‐magnetospheric science. The current paper presents two algorithms for background correction. The first algorithm is based on the empirical contamination percentages by both protons and electrons. The second algorithm uses simultaneous proton observations. The efficiencies of these algorithms are demonstrated by comparison of the corrected Cluster/RAPID/IES data with Van Allen Probes/Magnetic Electron Ion Spectrometer (MagEIS) measurements for 2012‐2015. Both techniques improved the IES electron data in the radiation belts and ring current, as the yearly averaged flux intensities of the two missions show the ratio of measurements close to 1. We demonstrate a scientific application of the corrected IES electron data analyzing its evolution during solar cycle. Spin‐averaged yearly mean IES electron intensities in the outer belt for energies 40‐400 keV at L‐shells between 4 and 6 showed high positive correlation with AE index and solar wind dynamic pressure during 2001‐ 2016. The relationship between solar wind dynamic pressure and IES electron measurements in the outer radiation belt was derived as a uniform linear‐logarithmic equation.

Beschreibung: Abstract The numerous recent breakthroughs in machine learning make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand Challenge review paper is focused on the present and future role of machine learning in Space Weather. The purpose is twofold. On one hand, we will discuss previous works that use machine learning for Space Weather forecasting, focusing in particular on the few areas that have seen most activity: the forecasting of geomagnetic indices, of relativistic electrons at geosynchronous orbits, of solar flares occurrence, of coronal mass ejection propagation time, and of solar wind speed. On the other hand, this paper serves as a gentle introduction to the field of machine learning tailored to the Space Weather community and as a pointer to a number of open challenges that we believe the community should undertake in the next decade. The recurring themes throughout the review are the need to shift our forecasting paradigm to a probabilistic approach focused on the reliable assessment of uncertainties, and the combination of physics‐based and machine learning approaches, known as gray‐box.

Beschreibung: Abstract Coupled Sun‐to‐Earth models represent a key part of the future development of space weather forecasting. With respect to predicting the state of the thermosphere and ionosphere, there has been a recent paradigm shift; it is now clear that any self‐respecting model of this region needs to include some representation of forcing from the lower atmosphere, as well as solar and geomagnetic forcing. Here we assess existing modeling capability and set out a roadmap for the important next steps needed to ensure further advances. These steps include a model verification strategy, analysis of the impact of non‐hydrostatic dynamical cores, and a cost‐benefit analysis of model chemistry for weather and climate applications.

Beschreibung: Abstract The Carrington event is considered to be one of the most extreme space weather events in observational history within a series of magnetic storms caused by extreme interplanetary coronal mass ejections (ICMEs) from a large and complex active region (AR) emerged on the solar disk. In this article, we study the temporal and spatial evolutions of the source sunspot active region and visual aurorae, and compare this storm with other extreme space weather events on the basis of their spatial evolution. Sunspot drawings by Schwabe, Secchi, and Carrington describe the position and morphology of the source AR at that time. Visual auroral reports from the Russian Empire, Iberia, Ireland, Oceania, and Japan fill the spatial gap of auroral visibility and revise the time series of auroral visibility in mid to low magnetic latitudes (MLATs). The reconstructed time series is compared with magnetic measurements and shows the correspondence between low to mid latitude aurorae and the phase of magnetic storms. The spatial evolution of the auroral oval is compared with those of other extreme space weather events in 1872, 1909, 1921, and 1989 as well as their storm intensity, and contextualizes the Carrington event, as one of the most extreme space weather events, but likely not unique.

Beschreibung: Abstract In this work, we use observations by the Solar Back scatter Ultraviolet Sounder (SBUS) and Space Environment Monitor (SEM) on FengYun‐3 to analyze the polar ozone depletion during the solar proton events (SPEs), which occurred in early March 2012. The ozone distributions changed evidently with the increasing energetic proton flux (the particle energy is over 100 MeV) at the approximate altitude of 30 km. From the ozone profile relative changes, the short‐term impacts of SPEs can be distinguished from the long‐term effects of ozone season variations after the SPEs take place and cause about 4%‐17% of the short‐term polar ozone decreases at the different levels in the upper stratosphere of both hemispheres. In the upper stratosphere, the SPE‐related polar ozone depletion is more significant and continuous in the Northern Hemisphere but shows the short‐term effects in the Southern Hemisphere during the March SPEs. The ozone depletion responses to the first SPE on March 7 are more pronounced in this altitude region than the second one on March 13 in both hemispheres due to the “harder” particle energy spectrum.

Beschreibung: Abstract The particle simulations of the inner magnetosphere require time‐dependent boundary condition for the particle flux set in the transition region between dipolar and tail‐like configurations. Usually, the flux is reconstructed from particle density and temperature predicted by empirical models or magnetohydrodynamic (MHD) simulations. However, this method requires assumptions about the energy spectra to be made. This uncertainty adds to the inaccuracy of the empirical models or MHD predictions. We use electron flux measurements in the nightside at r=6—11 RE in the 1—300 keV energy range to estimate the potential accuracy of the electron flux reconstruction from the macroscopic plasma parameter models. We use kappa and Maxwellian distribution functions as well as two population approximations to describe the electron spectra. It is found that this method works reasonably well in the thermal energy range (1—10 keV). However, the average difference between measured and predicted fluxes becomes as large as one order of magnitude at energies ≥ 40 keV. The optimal value of the kappa parameter is found to be between 3 and 4 but it depends strongly on MLT and radial distance. We conclude that the development of the flux‐based models (model of differential flux at several reference energies) instead of density and temperature models can be considered as a promising direction.

Beschreibung: Abstract The recent introduction of all‐electric propulsion on geosynchronous satellites enables lower‐cost access to space by replacing chemical propellant. However, the time period required to initially raise the satellite to geostationary orbit (GEO) is around 200 days. During this time the satellite can be exposed to dynamic increases in trapped flux which are challenging to model. To understand the potential penalty of this new technique in terms of radiation exposure, the influence of several key parameters on solar cell degradation during the electric orbit raising period has been investigated. This is achieved by calculating the accumulation of non‐ionising dose through time for a range of approaches. We demonstrate the changes in degradation caused by launching during a long‐lived (100s of days) enhancement in MeV trapped proton flux for three different electric orbit raising scenarios and three different thicknesses of coverglass. Results show that launching in an active environment can increase solar cell degradation due to trapped protons by ~5% before start of service compared with a quiet environment. The crucial energy range for such enhancements in proton flux is 3‐10MeV (depending on shielding). Further changes of a few percent can occur between different trajectories, or when a 50μm change in coverglass thickness is applied.

Beschreibung: Abstract Interplanetary scintillation (IPS) manifests itself as a variation in the radio signal received from a distant, compact radio source on the sky. The intensity fluctuations of the radio waves are caused by density inhomogeneities in the outflowing solar plasma across the heliosphere. IPS allows us to infer solar wind speed and density variations along the line of sight (LOS). There are two types of techniques in the literature to infer solar wind speed using IPS data sets: single‐site analysis (SSA), where the power spectra from single time series' are analysed to obtain solar wind parameters; and multi‐site analysis, where the cross‐correlation function (CCF) of data from two or more widely‐separated sites is used. The selection of the analysis technique depends on the number of sites available to each IPS system. In order to combine and complement solar wind speed determinations from different instruments, it is important to validate results and methodologies of the two techniques. In this paper, we analysed previously well‐studied European Incoherent SCATter (EISCAT) and Multi‐Element Radio‐Linked Interferometer Network (MERLIN) observations of IPS with well‐known results from the CCF methodology. We applied the SSA technique to each of the individual EISCAT and MERLIN IPS power spectra. This work shows the capabilities of the SSA to describe complex events and seeks to obtain improved parameter fits using the SSA methodology.

Beschreibung: Abstract The capability to forecast conditions in the mesosphere and lower thermosphere is investigated based on 30‐day hindcast experiments that were initialized bimonthly during 2009 and 2010. The hindcasts were performed using the Whole Atmosphere Community Climate Model with thermosphere‐ionosphere eXtension (WACCMX) with data assimilation provided by the Data Assimilation Research Testbed (DART) ensemble Kalman filter. Analysis of the WACCMX+DART hindcasts reveals several important features that are relevant to forecasting the middle atmosphere. The results show a clear dependence on spatial scale, with the slowest error growth occurring in the zonal mean and the fastest error growth occurring for small‐scale waves. The error growth rate is also found to be significantly greater in the upper mesosphere and lower thermosphere compared to in the upper stratosphere to lower mesosphere, suggesting that the forecast skill decreases with increasing altitude. The results demonstrate that the errors in the lower thermosphere reach saturation, on average, in less than 5 days, at least with the current version of WACCMX+DART. A seasonal dependency to the error growth is found at high latitudes in the Northern and Southern Hemispheres but not in the tropics or global average. We additionally investigate the error growth rates for migrating and nonmigrating atmospheric tides and find that the errors saturate after ∼5 days for tides in the lower thermosphere. The results provide an initial assessment of the error growth rates in the mesosphere and lower thermosphere and are relevant for understanding how whole atmosphere models can potentially improve space weather forecasting.

Beschreibung: Abstract We present high‐latitude field‐aligned current (FAC) response to nearly frontal shocks (NFSs) and highly inclined shocks (HISs) through a superposed epoch analysis (SEA). The FACs are derived from magnetic perturbation data provided by the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) program. Forty‐nine events for each group are used for the SEA. The 25%, 50% and 75% quantiles of the FAC and total current distributions are studied. We found that NFSs are statistically stronger shocks in terms of solar wind parameters such as solar wind speed and interplanetary magnetic field (IMF). For the 50% quantiles, both groups of shocks produce rapid increases in total currents after shock arrival, but NFSs result in sharper increase in FACs and more intense FACs compared to HISs. At the 50% and 75% quantiles, NFSs trigger stronger auroral‐zone current disturbance for the first hour after shock arrival than do HISs. Spatially, the difference in FAC response is most notable in: 1) the dayside noon region; 2) the duskside Region 2 current system; and 3) the dawnside pre‐noon Region 1 current system. Our results are consistent with previous numerical simulations that showed more symmetric and stronger compression of the magnetosphere for high‐speed and nearly frontal shocks. We observationally confirm the role of shock impact angle in controlling the subsequent shock geoeffectiveness for fast shocks. We assert that determining the shock impact angle via an upstream solar wind model could provide useful insight in forecasting the geoeffectiveness of a shock prior to its arrival at the magnetopause.

Beschreibung: Abstract In this paper, we present evidence that geomagnetic activity has the potential to disrupt the electricity flows between Ontario, Canada and New York State, USA. This conclusion is based on a modeling framework that makes use of weather data, electricity load data, measures of transmission “network effects,” proxies for geomagnetically induced currents (GICs) and the expected level of power grid conditions. The model is estimated using hourly data throughout 1 May 2002 through 31 October 2003. The model is evaluated using out‐of‐sample hourly data over the period of 1 November to 9 December 2003. The out‐of‐sample predictions are more accurate when the forecasting equation reflects the estimated contribution of geomagnetic activity. The structural modeling results for the sample period indicate that the peak predicted effect of geomagnetic activity on the electricity flow was about 1,604 MWh in absolute value when the GIC proxy achieved a value of 363.2 nT/min. The analysis also indicates that the level of the geomagnetically induced electricity flow is highly dependent on ambient temperature and expected system conditions at the time of the geomagnetic storm. Moreover, geomagnetic activity is an important driver of the volatility in the electricity flows. The overall findings indicate that the scope of the challenge posed by space weather to the operations of the electric power system is likely understated.

Beschreibung: Space Weather, Volume 0, Issue ja, -Not available-.

Beschreibung: No abstract is available for this article

Beschreibung: Abstract Human radiation exposure from solar energetic particle (SEP) events during deep‐space exploration missions has a greater impact on mission planning and operations compared to spaceflight missions to low Earth orbit. Deep‐space SEP radiation exposure may require in‐flight preventative actions in order to reduce the radiation risks to as low as reasonably achievable, to limit the onset and severity of acute biological responses, and to ensure that astronaut permissible exposure limits are not exceeded. In this paper, radiation dose to the blood forming organs (BFO) of astronaut crew are calculated from a set of historical SEP events, using the design of the Orion Multi‐Purpose Crew Vehicle (MPCV). The BFO doses from the historical events are analyzed in several ways. The results show the range and upper limit of BFO doses expected in heavily shielded space vehicles such as the Orion MPCV, based on calculations from all the major SEP events encountered in the space age. The dose reduction properties of the MPCV storm‐shelter are characterized over the broad range of SEP events included in the historical database. Correlations are derived between the integral proton fluence and BFO dose in the vehicle, showing that integral fluence is a good proxy for predicting or forecasting vehicle BFO dose. The best correlation with MPCV BFO dose is from the 〉100 MeV integral fluence. These results will assist in the design of future space weather architectures by identifying models and measurements needed to expand and extend NASA's existing SEP radiation risk tools in the support and management of human space exploration missions.

Beschreibung: Abstract A common assumption used when estimating geomagnetically induced currents (GICs) in a power system given a time series of nearby direct measurements or indirect estimates of the horizontal geoelectric field components Ex(t) and Ey(t) on Earth's surface is that the system is resistive. That is, the approximation GIC(t) = aoEx(t) + boEy(t) (Model 1) is used, where ao and bo are frequency‐independent power system coefficients. A first test of this assumption is made using GIC measurements in a 187 kV transformer connected to a ~100 km power line in Memanbetsu, Japan and geoelectric field measurements made at the Memanbetsu Magnetic Observatory ~9 km away. A second model (Model 2) is obtained using a frequency domain generalization of Model 1: GIC(ω) = a(ω)Ex(ω)+b(ω)Ey(ω). The coefficients a(ω) and b(ω) are shown to be frequency‐dependent and this model provides significantly better estimates of the measured GIC than Model 1. Based on results using a simulated geoelectric field, it is suggested that the measurement‐derived frequency dependence of the system coefficients may be explained by spatial variations in the spectrum of the geoelectric field over the spatial extent of the power system. It is also shown that further improvements over Model 2 can be made using frequency‐dependent models with the geomagnetic field as an input.

Beschreibung: Abstract One of the major research areas in the space weather community is the ability to understand, characterize and model a time‐space variant ionosphere through which trans‐ionospheric signals propagate. In this paper a strong constraint four‐dimensional variational data assimilation (4D‐var) technique was used to more accurately estimate the South African regional ionosphere (bound latitude 20° S ‐ 35° S, longitude 20° E ‐ 40° E and altitude 100‐1336 km). The altitude was capped to the JASON‐1 satellite orbital altitude for the purpose of eliminating the plasmasphere contribution hence reducing the computation expense. Background densities were obtained from an empirical internationally recognized ionosphere model (IRI‐2016), and propagated in time using a Gauss‐Markov filter. Ingested data were STECs (slant total electron content) obtained from the South African GNSS (Global Navigation Satellite System) receiver network (TrigNet). The vertically integrated electron content was validated using GIMs (Global ionosphere Maps) and JASON‐3 data over the continent and ocean areas, respectively. Further, vertical profiles after assimilation were compared with data from a network of ground based regional ionosondes Hermanus (34.25° S, 19.13° E), Grahamstown (33.3° S, 26.5° E), Louisvale (21.2° S, 28.5° E) and Madimbo (22.4° S, 30.9° E). Results show that assimilation of STEC data has a profound improvement on the estimation of both the horizontal and vertical structure during quiet and storm periods. Accuracy of the horizontal structure decreases from the continent towards the ocean area where GPS receivers are less abundant. Superiority of assimilating STEC is best pronounced during day time especially when estimating maximum electron density of the F2 layer (NmF2), with a 60% RMSE improvement over the background values.

Beschreibung: No abstract is available for this article

Beschreibung: Abstract We investigate satellite orbital drag effects at low‐Earth orbit (LEO) associated with thermosphere heating during magnetic storms caused by coronal mass ejections. CHAllenge Mini‐satellite Payload (CHAMP) and Gravity Recovery And Climate Experiment (GRACE) neutral density data are used to compute orbital drag. Storm‐to‐quiet density comparisons are performed with background densities obtained by the Jacchia‐Bowman 2008 (JB2008) empirical model. Our storms are grouped in different categories regarding their intensities as indicated by minimum values of the SYM‐H index. We then perform superposed epoch analyses with storm main phase onset as zero epoch time. In general, we find that orbital drag effects are larger for CHAMP (lower altitudes) in comparison to GRACE (higher altitudes). Results show that storm‐time drag effects manifest first at high latitudes, but for extreme storms particularly observed by GRACE stronger orbital drag effects occur during early main phase at low/equatorial latitudes, probably due to heating propagation from high latitudes. We find that storm‐time orbital decay along the satellites' path generally increases with storm intensity, being stronger and faster for the most extreme events. For these events, orbital drag effects decrease faster probably due to elevated cooling effects caused by nitric oxide, which introduce modeled density uncertainties during storm recovery phase. Errors associated with total orbit decay introduced by JB2008 are generally the largest for the strongest storms, and increase during storm times, particular during recovery phases. We discuss the implication of these uncertainties for the prediction of collision between space objects at LEO during magnetic storms.

Beschreibung: Abstract The auroral substorm has been extensively studied over the last six decades. However, our understanding of its driving mechanisms is still limited and so is our ability to accurately forecast its onset. In this study, we present the first deep learning‐based approach to predict the onset of a magnetic substorm, defined as the signature of the auroral electrojets in ground magnetometer measurements. Specifically, we use a time history of solar wind speed (Vx), proton number density, and IMF components as inputs to forecast the occurrence probability of an onset over the next one hour. The model has been trained and tested on a dataset derived from the SuperMAG list of magnetic substorm onsets and can correctly identify substorms ∼75% of the time. In contrast, an earlier prediction algorithm correctly identifies ∼21% of the substorms in the same dataset. Our model's ability to forecast substorm onsets based on solar wind and IMF inputs prior to the actual onset time, and the trend observed in IMF Bz prior to onset together suggest a majority of the substorms may not be externally triggered by northward turnings of IMF. Furthermore, we find that IMF Bz and Vx have the most significant influence on model performance. Finally, principal component analysis shows a significant degree of overlap in the solar wind and IMF parameters prior to both substorm and non‐substorm intervals, suggesting that solar wind and IMF alone may not be sufficient to forecast all substorms, and preconditioning of the magnetotail may be an important factor.

Beschreibung: Abstract The Editor in Chief discusses the vitality of Space Weather Journal

Beschreibung: Abstract We propose a new method to derive the nightside thermsopheric density by extending GUVI dayside limb observations using empirical orthogonal function (EOF) analysis. First, we acquire the GUVI dayside total mass density during 2002‐2005 to construct a preliminary empirical model (EM). Simultaneously, we decompose the background thermospheric density from US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended (NRLMSISE‐00) model into different empirical orthogonal functions (EOFs). The decomposed EOFs are then used to fit the continuous density from EM, to develop a new nightside extended model (NEM). The preliminary EM and developed NEM are further evaluated with CHAMP satellite observations. Higher correlation coefficients and smaller relative standard errors (RSE) between CHAMP observations and the NEM results are obtained than those between CHAMP observations and the EM results, and the NEM results are in good agreement with the CHAMP observations in time series during both daytime and nighttime, which all prove the NEM method is effective to the reproduction and extension of GUVI original dayside observations. Furthermore, the NEM reveals two typical seasonal variation features, the semiannual variation and equinoctial asymmetry of thermospheric density. The model provides an effective tool to derive the nightside thermospheric density and explore the thermospheric intrinsic structure, and needs the further development to achieve more widespread application of the thermosphere.