MIST

By Dale Weigt (University of Southampton)

Jupiter has dynamic auroral X-ray emissions, first observed over 40 years ago. A key characteristic of Jupiter’s aurora are “hot spots” of soft X-rays at the poles, which we observe from the Chandra X-ray Observatory (CXO) with high spatial resolution. These non-conjugate northern (Gladstone et al. 2002 + others) and southern auroral hot spots (Dunn et al. 2017 + others) are found in several observation campaigns to flare quasi-periodically. However, the driver of the X-rays (and hence their link to solar wind and magnetospheric conditions) is currently unknown.

In the Weigt at. (2020) case study, we analyse CXO data from 18^th June 2017 during a 10-hour observation where Juno was near its apojove position. An XMM-Newton observation overlapped the latter half of this observation (Wibisono et al. 2020). From the particle data, we find that Juno crossed the magnetopause several times preceding the Chandra observation. Using the closest crossing and amagnetopause model, we inferred a compressed magnetosphere during this interval. Using a numerical threshold to define spatial regions of concentrated photons, we find that the hot spot in the north appeared twice during the observation with a more extended morphology. Using Rayleigh testing, we find significant quasi-periodic oscillations (QPO) during both instances the hot spot was in view at ~ 37 min and 26 min respectively. The 26-min QPO was also observed by XMM-Newton and was found to remain for a further two Jupiter rotations. Using the Vogt et al. (2011, 2015) flux equivalence model, we map the origin of the QPOs and X-ray driver to be on the dayside-dusk magnetopause boundary, considering the caveats of the model. The timescales of the periods found suggest that the driver may be linked to magnetospheric processes producing ultra-low frequency waves (ULF).

Figure 1: (c) polar plot of Jupiter’s north pole showing the observed mapped and unmapped photons (black dots and orange triangles respectively)at the beginning of the observation interval. (d) The photons are mapped to their magnetospheric origins using the Vogt et al. (2011, 2015) model, where error bars show the estimated mapping errors. The red dashed line indicates the magnetopause boundary inferred from the Juno data during the Chandra observation. The location of Juno during this time is denoted by the yellow star. 

These results demonstrate the capabilities of CXO data in understanding the “hot spots” in Jupiter’s aurora, and can provide important contextual information to Juno observations. This study is also the first to find two significant QPOs in the northern hot spot over timescales less than a Jupiter rotation.

For more details, see the paper:

Weigt, D. M., Jackman, C. M., Dunn W. R., Gladstone G.R., Vogt M. F., Wibisono A. D., et al (2020). Chandra Observation of Jupiter’s X-rays Auroral Emission During Juno Apojove 2017 Journal of Geophysical Research: Planets, 125, e2019JE006262. https://doi.org/10.1029/2019JE006262 

By William Dunn (Mullard Space Science Laboratory, UCL; The Centre for Planetary Science at UCL/Birkbeck; Harvard‐Smithsonian Center for Astrophysics)

The solar minimum from 2007-2009 was the lowest and longest of the space age. In February 2007, the New Horizons spacecraft was approaching Jupiter measuring the conditions in the solar wind. At this time, a rich multi-instrument observing campaign was conducted, including X-ray, UV and Radio observations. In 2 accepted JGR: Space Physics papers we explore these campaigns, particularly focussing on the X-ray observations. 

The first paper concentrates on the X-ray emissions in the context of solar minimum. We explore the spectral and spatial morphologies of Jupiter’s X-rays using the Chandra and XMM-Newton (XMM) observatories. We show that the Jovian equatorial emission varies with solar cycle and may be utilised as a diagnostic of the disk-integrated solar spectrum at a given time. 

Figure showing variability in Jupiter’s X-ray aurora as recorded by Chandra ACIS during the 2007 campaign.  Each plot shows a projection on Jupiter's North pole of the X-ray aurora. The logarithmic color bar indicates the number of X-rays in bins of 3 degree by 3 degree of S3 latitude-longitude. Dashed grey lines of longitude radiate from the pole, increasing clockwise in increments of 30 degree from 0 degree at the top. Concentric grey circles outward from the pole represent lines of latitude in increments of 10 degree. Thin green contours with white text labels indicate the VIP4  [Connerney et al. 1998] model magnetic field strength in Gauss. Thick gold contours show the magnetic field ionospheric footprints of field lines intersecting the Jovigraphic equator at 5.9 R_J (Io's orbit), 15 R_J and 45 R_J [Grodent et al. 2008; Vogt et al. 2015] from equator to pole respectively.

The second paper compares the UV, Radio and X-ray auroral emissions in the context of the solar wind conditions, identifying shared behaviours between the emissions. Generally, we find that Jupiter’s X-ray aurora is best fit by ion lines from precipitating magnetospheric plasma, but during some magnetospheric expansions the spectrum is very different. At these times, the spectral models require the inclusion of a precipitating solar wind ion population, suggesting that additional solar wind ions gain access to the outer magnetosphere or directly to the pole during magnetospheric expansions. During these expansions we also observe a new type of X-ray aurora, which coexists with the other aurorae. We label this new aurora as ‘flickering X-ray aurora’ based on its temporal behaviour. 

The papers lay important groundwork in X-ray aurora spectral modelling and in attempting to understand the unification of the different multi-waveband auroral emissions and their relationship to solar wind conditions.

For more details see:

Dunn, W. R. et al. Jupiter’s X-rays 2007 Part 1: Jupiter’s X-ray Emission During Solar Minimum. J. Geophys. Res. Sp. Phys. https://doi.org/10.1029/2019JA027219

Dunn, W. R. et al. Jupiter’s X-ray Emission 2007 Part 2: Comparisons with UV and Radio Emissions and In-Situ Solar Wind Measurements. J. Geophys. Res. Sp. Phys. https://doi.org/10.1029/2019JA027222 

By Frances Staples (Mullard Space Science Laboratory, UCL)

Under steady-state solar wind conditions, the magnetopause location is described as a pressure balance between internal magnetic pressure of Earth’s magnetic field and the external dynamic pressure of the solar wind. Under extreme solar wind driving, such as high solar wind pressure or strong southward-directed interplanetary magnetic fields, this boundary is located much closer towards Earth. These compressions of the magnetopause can play a significant role in the depletion of magnetospheric plasma in the Van Allen Radiation Belts, via magnetopause shadowing. Statistical models of the magnetopause location are often used in investigations of radiation belt losses through the magnetopause. However, empirical models cannot capture the time varying nature of the magnetopause during such events, which are often associated with large step-changes in solar wind conditions.

We constructed a database of ~ 20,000 spacecraft crossings of the dayside magnetopause to assess the accuracy of the commonly used Shue et al. (1998) model. For the majority of our measurements, the Shue et al. (1998) model accurately represented the magnetopause location within an error of ± 1 R_E. However, when the magnetopause was compressed below 8 R_E, the model overestimated the radial distance of the magnetopause by more than 1 R_E on average. This result is demonstrated in the Figure as the data does not follow the blue line, which represents where the modelled location is equal to measured location, for magnetopause measurements below 10 R_E. 

Figure: The median magnetopause location, R_Mod, calculated for a given measurement of the magnetopause by a spacecraft, R_SC, is plotted by purple diamonds, and a best fit is shown by the purple line. The interquartile range of R_SC (where 75% of magnetopause measurements were taken) is shown by the shaded region.

Furthermore, during sudden storm commencements, where interplanetary shocks impact the magnetosphere, the modelled magnetopause was significantly displaced from the measured location. Magnetopause measurements were on average 6% closer to the radiation belts, with a maximum of 42%. We conclude that statistical magnetopause parameterizations may not be appropriate during dynamic compressions of the magnetosphere and could underestimate the role of magnetopause shadowing on radiation belt dynamics. Models should be supplemented by magnetopause observations wherever possible and we have provided a dataset of THEMIS magnetopause crossing to be used by the research community.

For more information, please see the paper;

Staples, F. A., Rae, I. J., Forsyth, C., Smith, A. R. A., Murphy, K. R., Raymer, K. M., et al (2020). Do statistical models capture the dynamics of the magnetopause during sudden magnetospheric compressions?. Journal of Geophysical Research: Space Physics, 125, e2019JA027289. https://doi.org/10.1029/2019JA027289 

The database of THEMIS and Geotail magnetopause crossings used in this study are openly available at https://doi.org/10.5281/zenodo.3700504 and https://doi.org/10.5281/zenodo.3719411 .

By Juliane Hübert (British Geological Survey, Edinburgh)

Large geomagnetic storms create time-varying magnetic fields, which induce secondary electric fields in the conductive Earth resulting in geomagnetically induced currents (GICs). The high voltage (HV) power transmission network is connected to the Earth at grounding points in substations. These offer a low-resistance path for GICs to flow into the power network, potentially causing the transformers to malfunction with extensive consequences for the national power supply. The UK government has listed severe space weather events as one of the highest priority natural hazard. Therefore, it is important to fully understand GICs to enable the mitigation of this hazard. It is possible to directly measure GICs at substations using Hall-effect probes, but due to cost and operational reasons, at present only four substations in the UK are monitored. Therefore we have developed a new instrument to measure GICs indirectly using two magnetometers, one placed under the HV line and another a few hundred metres away. By examining the differences between the magnetometers, we work out the additional current flowing in the HV line.

Figure 1: Recorded times series during the G3 geomagnetic storm on 25-26 August 2018. Panels a-d) Horizontal magnetic field components at DMM site Whiteadder (WHI), East Scotland. Panel e) Line GICs at WHI; Panel f) GIC data from a Hall probe at Torness substation.

In the study, we present the design and initial deployment of the first differential magnetometer method (DMM) systems in the UK and measurements from the first site installed at Whiteadder in eastern Scotland. At this site we have successfully detected geomagnetically induced currents in a 400 kV high voltage power network. The Figure compares line GIC data recorded at Whiteadder (panels a-e) to data from a Hall probe at the nearby substation at Torness (panel f) during the 26 August 2018 storm. The measured GICs from the line and the Hall probe show excellent temporal correlation, though with significant differences in amplitude, illustrating that line measurements with DMM and Hall probes at grounding points capture different but complementary views of GIC flow in a network. Using the latest model of the HV network and electric field variations estimated from a magnetotelluric survey, we show that the measured line and earthing GICs match the expected modelled values during the geomagnetic storm. This is the first study to validate such a complex network model using direct and indirect measurements of GICs.

The full article can be found here:

Hübert, J., Beggan, C. D., Richardson, G. S., Martyn, T., & Thomson, A. W. P. (2020). Differential Magnetometer Measurements of Geomagnetically Induced Currents in a Complex High Voltage Network. Space Weather, 18, https://doi.org/10.1029/2019SW002421