Generation of inverted heliospheric magnetic flux by coronal loop opening and slow solar wind release

In situ spacecraft observations provide much-needed constraints on theories of solar wind formation and release, particularly the highly variable slow solar wind, which dominates near-Earth space. Previous studies have shown an association between local inversions in the heliospheric magnetic field (HMF) and solar wind released from the vicinity of magnetically closed coronal structures. We here show that in situ properties of inverted HMF are consistent with the same hot coronal source regions as the slow solar wind. We propose that inverted HMF is produced by solar wind speed shear, which results from interchange reconnection between a coronal loop and open flux tube, and introduces a pattern of fast–slow–fast wind along a given HMF flux tube. This same loop-opening process is thought to be central to slow solar wind formation. The upcoming Parker Solar Probe and Solar Orbiter missions provide a unique opportunity to directly observe these processes and thus determine the origin of the slow solar wind

A homogeneous aa index: 1. secular variation

Originally complied for 1868-1967 and subsequently continued so that it now covers 150 years, the aa index has become a vital resource for studying space climate change. However, there have been debates about the inter-calibration of data from the different stations. In addition, the effects of secular change in the geomagnetic field have not previously been allowed for. As a result, the components of the “classical” aa index for the southern and northern hemispheres (aaS and aaN) have drifted apart. We here separately correct both aaS and aaN for both these effects using the same method as used to generate the classic aa values but allowing {\delta}, the minimum angular separation of each station from a nominal auroral oval, to vary as calculated using the IGRF-12 and gufm1 models of the intrinsic geomagnetic field. Our approach is to correct the quantized aK-values for each station, originally scaled on the assumption that {\delta} values are constant, with time-dependent scale factors that allow for the drift in {\delta}. This requires revisiting the intercalibration of successive stations used in making the aaS and aaN composites. These intercalibrations are defined using independent data and daily averages from 11 years before and after each station change and it is shown that they depend on the time of year. This procedure produces new homogenized hemispheric aa indices, aaHS and aaHN, which show centennial-scale changes that are in very close agreement. Calibration problems with the classic aa index are shown to have arisen from drifts in {\delta} combined with simpler corrections which gave an incorrect temporal variation and underestimate the rise in aa during the 20th century by about 15%

A homogeneous aa index: 2. hemispheric asymmetries and the equinoctial variation

Paper 1 [Lockwood et al., 2018] generated annual means of a new version of the aa geomagnetic activity index which includes corrections for secular drift in the geographic coordinates of the auroral oval, thereby resolving the difference between the centennial-scale change in the northern and southern hemisphere indices, aaN and aaS. However, other hemispheric asymmetries in the aa index remain: in particular, the distributions of 3-hourly aaN and aaS values are different and the correlation between them is not high on this timescale (r = 0.66). In the present paper, a location-dependant station sensitivity model is developed using the am index (derived from a much more extensive network of stations in both hemispheres) and used to reduce the difference between the hemispheric aa indices and improve their correlation (to r = 0.79) by generating corrected 3-hourly hemispheric indices, aaHN and aaHS, which also include the secular drift corrections detailed in Paper 1. These are combined into a new, “homogeneous” aa index, aaH. It is shown that aaH, unlike aa, reveals the “equinoctial”-like time-of-day/time-of-year pattern that is found for the am index

The value of CME arrival‐time forecasts for space weather mitigation

Severe geomagnetic storms are driven by the coronal mass ejections (CMEs). Consequently, there has been a great deal of focus on predicting if and when a CME will arrive in near‐Earth space. However, it is useful to step back and ask, “How value is this information, in isolation, useful for making decisions to mitigate against the adverse effects of space weather?” While all severe geomagnetic storms are triggered by CMEs, not all CMEs trigger severe storms. Thus even perfect knowledge of CME arrival time will provide `actionable' forecast information only in operational situations where false alarms can be tolerated. Of course, any CME transit model used to predict CME arrival time must also produce an estimate of CME speed at Earth. This can help discriminate between geoeffective and non‐geoeffective CMEs, reducing false alarms and expanding the range of operational scenarios under which a forecast provides value. Thus, from an end‐user perspective, CME arrival speed should form part of the standard metric by which CME transit models are evaluated. Looking to the future, even coarse information about the CME magnetic properties would likely provide even greater forecast value. These points are illustrated by a simple analysis of solar wind data

Inferring thermospheric composition from ionogram profiles: a calibration with the TIMED spacecraft

Measurements of thermospheric composition via ground-based instrumentation are challenging to make and so details about this important region of the upper atmosphere are currently sparse. We present a technique that deduces quantitative estimates of thermospheric composition from ionospheric data, for which there is a global network of stations. The visibility of the F1 peak in ionospheric soundings from ground-based instrumentation is a sensitive function of thermospheric composition. The ionospheric profile in the transition region between F1 and F2 peaks can be expressed by the G factor, a function of ion production rate and loss rates via ion-atom interchange reactions and dissociative recombination of molecular ions. This in turn can be expressed as the square of the ratio of ions lost via these processes. We compare estimates of the G factor obtained from ionograms recorded at Kwajalein (9° N, 167.2° E) for 25 times during which the TIMED spacecraft recorded approximately co-located measurements of the neutral thermosphere. We find a linear relationship between √G and the molecular: atomic composition ratio, with a gradient of 2.23 ± 0.17 and an offset of 1.66 ± 0.19. This relationship reveals the potential for using ground-based ionospheric measurements to infer quantitative variations in the composition of the neutral thermosphere. Such information can be used to investigate spatial and temporal variations in thermospheric composition which in turn has applications such as understanding the response of thermospheric composition to climate change and the efficacy of the upper atmosphere on satellite drag

Time-of-day/time-of-year response functions of planetary geomagnetic indices

Aims: To elucidate differences between commonly-used mid-latitude geomagnetic indices and study quantitatively the differences in their responses to solar forcing as a function of Universal Time (UT), time-of-year (F), and solar-terrestrial activity level. To identify the strengths, weaknesses and applicability of each index and investigate ways to correct for any weaknesses without damaging their strengths. Methods: We model how the location of a geomagnetic observatory influences its sensitivity to solar forcing. This modelling for a single station can then be applied to indices that employ analytic algorithms to combine data from different stations and thereby we derive the patterns of response of the indices as a function of UT, F and activity level. The model allows for effects of solar zenith angle on ionospheric conductivity and of the station’s proximity to the midnight-sector auroral oval: it employs coefficients that are derived iteratively by comparing data from the current aa index stations (Hartland and Canberra) to simultaneous values of the am index, constructed from chains of stations in both hemispheres. This is done separately for 8 overlapping bands of activity level, as quantified by the am index. Initial estimates were obtained by assuming the am response is independent of both F and UT and the coefficients so derived were then used to compute a corrected F-UT response pattern for am. This cycle was repeated until it resulted in changes in predicted values that were below the adopted uncertainty level (0.001%). The ideal response pattern of an index would be uniform and linear (i.e., independent of both UT and F and the same at all activity levels). We quantify the response uniformity using the percentage variation at any activity level, V = 100(S/), where S is the index’s sensitivity at that activity level and S is the standard deviation of S: both S and S were computed using the 8 UT ranges of the 3-hourly indices and 20 equal-width ranges of F. As an overall metric of index performance, we take an occurrence-weighted mean of V, Vav, over the 8 activity-level bins. This metric would ideally be zero and a large value shows that the index compilation is introducing large spurious UT and/or F variations into the data. We also study index performance by comparisons with the SME and SML indices, compiled from a very large number of stations, and with an optimum solar wind “coupling function”, derived from simultaneous interplanetary observations. Results: It is shown that a station’s response patterns depend strongly on the level of geomagnetic activity because at low activity levels the effect of solar zenith angle on ionospheric conductivity dominates over the effect of station proximity to the midnight-sector auroral oval, whereas the converse applies at high activity levels. The metric Vav for the two-station aa index is modelled to be 8.95%, whereas for the multi-station am index it is 0.65%. The ap (and hence Kp) index cannot be analyzed directly this way because its construction employs tabular conversions, but the very low Vav for am allows us to use / to evaluate the UT-F response patterns for ap. This yields Vav = 11.20% for ap. The same empirical test applied to the classical aa index and the new “homogenous” aa index, aaH (derived from aa using the station sensitivity model), yields Vav of, respectively, 10.62% (i.e., slightly higher than the modelled value) and 5.54%. The ap index value of Vav is shown to be high because it exaggerates the average semi-annual variation and has an annual variation giving a lower average response in northern hemisphere winter. It also contains a strong artefact UT variation. We derive an algorithm for correcting for this uneven response which gives a corrected ap value, apC, for which Vav is reduced to 1.78%. The unevenness of the ap response arises from the dominance of European stations in the network used and the fact that all data are referred to a European station (Niemegk). However, in other contexts, this is a strength of ap, because averaging similar data gives increased sensitivity and more accurate values on annual timescales, for which the UT-F response pattern is averaged out

Testing the current paradigm for space weather prediction with heliospheric imagers

Predictions of the arrival of four coronal mass ejections (CMEs) in geospace are produced through use of three CME geometric models combined with CME drag modeling, constraining these models with the available Coronagraph and Heliospheric Imager data. The efficacy of these predications is assessed by comparison with the Space Weather Prediction Center (SWPC) numerical MHD forecasts of these same events. It is found that such a prediction technique cannot outperform the standard SWPC forecast at a statistically meaningful level. We test the Harmonic Mean, Self-Similar Expansion, and Ellipse Evolution geometric models, and find that, for these events at least, the differences between the models are smaller than the observational errors. We present a new method of characterizing CME fronts in the Heliospheric Imager field of view, utilizing the analysis of citizen scientists working with the Solar Stormwatch project, and we demonstrate that this provides a more accurate representation of the CME front than is obtained by experts analyzing elongation time maps for the studied events. Comparison of the CME kinematics estimated independently from the STEREO-A and STEREO-B Heliospheric Imager data reveals inconsistencies that cannot be explained within the observational errors and model assumptions. We argue that these observations imply that the assumptions of the CME geometric models are routinely invalidated and question their utility in a space weather forecasting context. These results argue for the continuing development of more advanced techniques to better exploit the Heliospheric Imager observations for space weather forecasting

Using the ionospheric response to the solar eclipse on 20th March 2015 to detect spatial structure in the solar corona

Long-term variability has previously been observed in the relative magnitude of annual and semi-annual variations in the critical frequency (related to the peak electron concentration) of the ionospheric F2 layer (foF2). In this paper we investigate the global patterns in such variability by calculating the time varying power ratio of semi-annual to annual components seen in ionospheric foF2 data sequences from 77 ionospheric monitoring stations around the world. The temporal variation in power ratios observed at each station was then correlated with the same parameter calculated from similar epochs for the Slough/Chilton data set (for which there exists the longest continuous sequence of ionospheric data). This technique reveals strong regional variation in the data, which bears a striking similarity to the regional variation observed in long-term changes to the height of the ionospheric F2 layer. We argue that since both the height and peak density of the ionospheric F2 region are influenced by changes to thermospheric circulation and composition, the observed long-term and regional variability can be explained by such changes. In the absence of long-term measurements of thermospheric composition, detailed modelling work is required to investigate these processes

Solar Energetic-Particle Ground-Level Enhancements and the Solar Cycle

Severe geomagnetic storms appear to be ordered by the solar cycle in a number of ways. They occur more frequently close to solar maximum and the declining phase, are more common in larger solar cycles, and show different patterns of occurrence in odd- and even-numbered solar cycles. Our knowledge of the most extreme space-weather events, however, comes from spikes in cosmogenic-isotope (C-14, Be-10, and Cl-36) records that are attributed to significantly larger solar energetic-particle (SEP) events than have been observed during the space age. Despite both storms and SEPs being driven by solar-eruptive phenomena, the event-by-event correspondence between extreme storms and extreme SEPs is low. Thus, it should not be assumed a priori that the solar-cycle patterns found for storms also hold for SEPs and the cosmogenic-isotope events. In this study, we investigate the solar-cycle trends in the timing and magnitude of the 67 SEP ground-level enhancements (GLEs) recorded by neutron monitors since the mid-1950s. Using a number of models of GLE-occurrence probability, we show that GLEs are around a factor of four more likely around solar maximum than around solar minimum, and that they preferentially occur earlier in even-numbered solar cycles than in odd-numbered cycles. There are insufficient data to conclusively determine whether larger solar cycles produce more GLEs. Implications for putative space-weather events in the cosmogenic-isotope records are discussed. We find that GLEs tend to cluster within a few tens of days, likely due to particularly productive individual active regions, and with approximately 11-year separations, owing to the solar-cycle ordering. However, these timescales would not explain any cosmogenic-isotope spikes requiring multiple extreme SEP events over consecutive years.Peer reviewe

Tracking CMEs using data from the Solar Stormwatch project; observing deflections and other properties

With increasing technological dependence, society is becoming ever more affected by changes in the near-Earth space environment caused by space weather. The primary driver of these hazards are coronal mass ejections (CMEs). Solar Stormwatch is a citizen science project in which volunteers participated in several activities which characterised CMEs in the remote sensing images from the SECCHI instrument package on the twin STEREO spacecraft. Here, we analyse the results of the 'Track-it-back' activity, in which CMEs were tracked back through the COR2, COR1 and EUVI images. Analysis of the COR1, COR2 and EUVI data together allows CMEs to be studied consistently throughout the whole field-of-view spanned by these instruments (out to 15 solar radii). 4783 volunteers took part in this activity, creating a dataset containing 23,801 estimates of CME timing, location and size. We used this data to produce a catalogue of 41 CMEs, which is the first to consistently track CMEs through each of these instruments. We assess how the CME speeds, propagation directions and widths vary as the CMEs propagate through the fields of view of the different imagers. In particular, we compare the observed CME deflections between the COR1 and COR2 fields of view to the separation between the CME source region and the heliospheric current sheet (HCS), demonstrating that, in general, these CMEs appear to deflect towards the HCS, consistent with other modelling studies of CME propagation