MIST

Magnetosphere, Ionosphere and Solar-Terrestrial

Latest news

Announcement of New MIST Councillors.

We are very pleased to announce the following members of the community have been elected unopposed to MIST Council:

  • Rosie Johnson (Aberystwyth University), MIST Councillor
  • Matthew Brown (University of Birmingham), MIST Councillor
  • Chiara Lazzeri (MSSL, UCL), Student Representative

Rosie, Matthew, and Chiara will begin their terms in July. This will coincide with Jasmine Kaur Sandhu, Beatriz Sanchez-Cano, and Sophie Maguire outgoing as Councillors.

The current composition of Council can be found on our website, and this will be amended in July to reflect this announcement (https://www.mist.ac.uk/community/mist-council).

Nominations are open for MIST Council

We are very pleased to open nominations for MIST Council. There are three positions available (detailed below), and elected candidates would join Georgios Nicolaou, Andy Smith, Maria-Theresia Walach, and Emma Woodfield on Council. The nomination deadline is Friday 31 May.

Council positions open for nomination

2 x MIST Councillor - a three year term (2024 - 2027). Everyone is eligible.

MIST Student Representative - a one year term (2024 - 2025). Only PhD students are eligible. See below for further details.

About being on MIST Council

If you would like to find out more about being on Council and what it can involve, please feel free to email any of us (email contacts below) with any of your informal enquiries! You can also find out more about MIST activities at mist.ac.uk. Two of our outgoing councillors, Beatriz and Sophie, have summarised their experiences being on MIST Council below.

Beatriz Sanchez-Cano (MIST Councillor):

"Being part of the MIST council for the last 3 years has been a great experience personally and professionally, in which I had the opportunity to know better our community and gain a larger perspective of the matters that are important for the MIST science progress in the UK. During this time, I’ve participated in a number of activities and discussions, such as organising the monthly MIST seminars, Autumn MIST meetings, writing A&G articles, and more importantly, being there to support and advise our colleagues in cases of need together with the wonderful council members. MIST is a vibrant and growing community, and the council is a faithful reflection of it."

Sophie Maguire (MIST Student Representative):

"Being the student representative for MIST council has been an amazing experience. I have been part of organizing conferences, chairing sessions, and writing grant applications based on the feedback MIST has received. From a wider perspective, MIST has helped to grow and support my professional networks which in turn, directly benefits my PhD work as well. I would encourage any PhD student to apply for the role of MIST Student Representative and I would be happy to answer any questions or queries you have about the role."

How to nominate

If you would like to stand for election or you are nominating someone else (with their agreement!) please email This email address is being protected from spambots. You need JavaScript enabled to view it. by Friday 31 May. If there is a surplus of nominations for a role, then an online vote will be carried out with the community. Please include the following details in the nomination:

  1. Name
  2. Position (Councillor/Student Rep.)
  3. Nomination Statement (150 words max including a bit about the nominee and focusing on your reasons for nominating. This will be circulated to the community in the event of a vote.)

MIST Council details

  • Sophie Maguire, University of Birmingham, Earth's ionosphere - This email address is being protected from spambots. You need JavaScript enabled to view it. 
  • Georgios Nicolaou, MSSL, solar wind plasma - This email address is being protected from spambots. You need JavaScript enabled to view it. 
  • Beatriz Sanchez-Cano, University of Leicester, Mars plasma - This email address is being protected from spambots. You need JavaScript enabled to view it.
  • Jasmine Kaur Sandhu, University of Leicester, Earth’s inner magnetosphere - This email address is being protected from spambots. You need JavaScript enabled to view it.
  • Andy Smith, Northumbria University, Space Weather - This email address is being protected from spambots. You need JavaScript enabled to view it. 
  • Maria-Theresia Walach, Lancaster University, Earth’s ionosphere - This email address is being protected from spambots. You need JavaScript enabled to view it. 
  • Emma Woodfield, British Antarctic Survey, radiation belts - This email address is being protected from spambots. You need JavaScript enabled to view it. 
  • MIST Council email - This email address is being protected from spambots. You need JavaScript enabled to view it. 

Winners of Rishbeth Prizes 2023

We are pleased to announce that following Spring MIST 2023 the Rishbeth Prizes this year are awarded to Sophie Maguire (University of Birmingham) and Rachel Black (University of Exeter).

Sophie wins the prize for the best MIST student talk which was entitled “Large-scale plasma structures and scintillation in the high-latitude ionosphere”. Rachel wins the best MIST poster prize, for a poster entitled “Investigating different methods of chorus wave identification within the radiation belts”. Congratulations to both Sophie and Rachel!

As prize winners, Sophie and Rachel will be invited to write articles for Astronomy & Geophysics, which we look forward to reading.

MIST Council extends their thanks to the University of Birmingham for hosting the Spring MIST meeting 2023, and to the Royal Astronomical Society for their generous and continued support of the Rishbeth Prizes.

Nominations for MIST Council

We are pleased to open nominations for MIST Council. There are two positions available (detailed below), and elected candidates would join Beatriz Sanchez-Cano, Jasmine Kaur Sandhu, Andy Smith, Maria-Theresia Walach, and Emma Woodfield on Council. The nomination deadline is Friday 26 May.

Council positions open for nomination

  • MIST Councillor - a three year term (2023 - 2026). Everyone is eligible.
  • MIST Student Representative - a one year term (2023 - 2024). Only PhD students are eligible. See below for further details.

About being on MIST Council


If you would like to find out more about being on Council and what it can involve, please feel free to email any of us (email contacts below) with any of your informal enquiries! You can also find out more about MIST activities at mist.ac.uk.

Rosie Hodnett (current MIST Student Representative) has summarised their experience on MIST Council below:
"I have really enjoyed being the PhD representative on the MIST council and would like to encourage other PhD students to nominate themselves for the position. Some of the activities that I have been involved in include leading the organisation of Autumn MIST, leading the online seminar series and I have had the opportunity to chair sessions at conferences. These are examples of what you could expect to take part in whilst being on MIST council, but the council will welcome any other ideas you have. If anyone has any questions, please email me at This email address is being protected from spambots. You need JavaScript enabled to view it..”

How to nominate

If you would like to stand for election or you are nominating someone else (with their agreement!) please email This email address is being protected from spambots. You need JavaScript enabled to view it. by Friday 26 May. If there is a surplus of nominations for a role, then an online vote will be carried out with the community. Please include the following details in the nomination:
  • Name
  • Position (Councillor/Student Rep.)
  • Nomination Statement (150 words max including a bit about the nominee and your reasons for nominating. This will be circulated to the community in the event of a vote.)
 
MIST Council contact details

Rosie Hodnett - This email address is being protected from spambots. You need JavaScript enabled to view it.
Mathew Owens - This email address is being protected from spambots. You need JavaScript enabled to view it.
Beatriz Sanchez-Cano - This email address is being protected from spambots. You need JavaScript enabled to view it.
Jasmine Kaur Sandhu - This email address is being protected from spambots. You need JavaScript enabled to view it.
Andy Smith - This email address is being protected from spambots. You need JavaScript enabled to view it.
Maria-Theresia Walach - This email address is being protected from spambots. You need JavaScript enabled to view it.
Emma Woodfield - This email address is being protected from spambots. You need JavaScript enabled to view it.
MIST Council email - This email address is being protected from spambots. You need JavaScript enabled to view it.

RAS Awards

The Royal Astronomical Society announced their award recipients last week, and MIST Council would like to congratulate all that received an award. In particular, we would like to highlight the following members of the MIST Community, whose work has been recognised:
  • Professor Nick Achilleos (University College London) - Chapman Medal
  • Dr Oliver Allanson (University of Birmingham) - Fowler Award
  • Dr Ravindra Desai (University of Warwick) - Winton Award & RAS Higher Education Award
  • Professor Marina Galand (Imperial College London) - James Dungey Lecture

Nuggets of MIST science, summarising recent papers from the UK MIST community in a bitesize format.

If you would like to submit a nugget, please fill in the following form: https://forms.gle/Pn3mL73kHLn4VEZ66 and we will arrange a slot for you in the schedule. Nuggets should be 100–300 words long and include a figure/animation. Please get in touch!
If you have any issues with the form, please contact This email address is being protected from spambots. You need JavaScript enabled to view it.. 

Temporal variability of quasi-linear pitch-angle diffusion

By Clare Watt (Northumbria University)

Our work here combines observations and ensemble numerical simulations to study the effect of temporal variability in radiation belt physics. Kinetic wave-particle interactions in Earth’s outer radiation belt are an effective way to energize and scatter high-energy electrons. A Fokker-Planck equation is often used to model the wave-particle interactions, and we studied the way it responds to the temporal variation of the quasi-linear diffusion coefficient in the case of pitch-angle diffusion due to plasmaspheric hiss. We used stochastic parameterisation [Berner et al., 2017] to describe the temporal evolution of hiss diffusion coefficients in ensemble numerical experiments, guided throughout by observations of wave activity and plasma parameters from the NASA Van Allen Probes. Ensemble solutions of the Fokker-Planck equation depend significantly on the timescale of variation, varied here between minutes and hours. We analysed timescales over which it is useful to construct diffusion coefficients and conclude that there is a useful maximum averaging timescale that should be used to construct a diffusion coefficient from observations. This timescale is likely less than the orbital period of most inner magnetospheric missions. Although arithmetic averaging of inputs to diffusion coefficients is not recommended [Watt et al., 2019], arithmetic drift-averaging of the diffusion coefficients themselves can be appropriate in some cases. We found that in some locations, rare but large values of the diffusion coefficient occur during periods of relatively low number density. Ensemble solutions are sensitive to the presence of these rare values, supporting the need for accurate cold plasma density models in radiation belt descriptions.

Figure 1: Ensemble results for numerical diffusion experiments using Dαα(L* = 3). Each panel shows a column-normalised probability distribution function for the phase space density f just outside the loss-cone αLC for (A) Δt = 2 min, (B) Δt = 10 min, (C) Δt = 30 min, (D) Δt = 2 h, (E) Δt = 4 h, and (F) Δt = 6 h. Note that each histogram is displayed using the same vertical binning, giving the histograms a pixelated appearance.

 

References:

Berner, J., et al. (2017) Stochastic parameterization: towards a new view of weather and climate models. Bulletin of the American Meteorological Society, 98 (3). pp. 565-588. ISSN 1520-0477 doi: https://doi.org/10.1175/BAMS-D-15-00268.1

Watt, C. E. J., Allison, H. J., Meredith, N. P., Thompson, R. L., Bentley, S. N., Rae, I. J., et al. (2019). Variability of quasilinear diffusion coefficients for plasmaspheric hiss. J. Geophys. Res. Space Phys. 124, 8488–8506. doi:10.1029/2018ja026401

 

Associated Paper:

Watt, C. E. J., Allison, H. J., Bentley, S. N., Thompson, R. L., Rae, I. J., Allanson, O., … Killey, S. (2022). Temporal variability of quasi-linear pitch-angle diffusion. Frontiers in Astronomy and Space Sciences. https://www.frontiersin.org/articles/10.3389/fspas.2022.1004634

Filling in the gaps in the UK magnetic field coverage

Ciaran Beggan (British Geological Survey)

Monitoring the ground magnetic field variation during space weather events, such as geomagnetic storms, is important for understanding and modelling their potentially hazardous effects on power, rail, and pipeline systems. The UK has three geomagnetic observatories in Lerwick, Eskdalemuir and Hartland. These form an approximately north-south line in latitude but have little variation in longitude. To expand the coverage in the east-west directions, as part of the SWIMMR N4 project, the British Geological Survey geomagnetism team have installed three new variometer stations in Northern Ireland, Leicestershire, and Sussex (Figure 1, left). These systems consist of a three-axis vector fluxgate magnetometer, a digitiser/logger computer and a 4G modem to transmit near-real-time data. The systems use batteries and a solar panel for independent power supply (Figure 1, centre).

Two systems were installed in fields in rural areas, at Florence Court (FLO) National Trust and near Market Harborough (LEI) while the third is located at the Space Geodesy Facility in Herstmonceux (HTX). The magnetic data quality is good and suitable for space weather monitoring purposes. The three new variometers fill in the ‘gaps’ between the BGS and other INTERMAGNET observatories reducing the inter-site distance to less than 400 km (Figure 1, right), thus improving the overall coverage.

The variometers will run for two years initially as part of the SAGE project to enhance geoelectric field modelling capabilities in the UK.

Three panelled figure showing a map of the UK with the observatories highlighted; a photograph of the variometer showing a grey box next to a hedge and a solar panel; and the distances highlighted between the variometers on a map.
Figure 1: (left) Location of the new variometers (red triangles) and existing INTERMAGNET observatories (blue squares); (centre) Installation of the LEI variometer, with solar panel, electronics & batteries in the housing and the buried magnetometer; (right) distances between magnetometers: green dots are the new SAGE variometers, blue are existing stations.

The Harmonic Frequency Separation of Ionospheric Alfvén Resonances at Eskdalemuir

Rosie Hodnett (University of Leicester)

Ionospheric Alfvén resonances (IAR) occur when Alfvén waves are partially reflected at boundaries in the ionosphere where there are large changes in plasma mass density. These boundaries are the bottom of the ionosphere and above the F-Region peak. This sets up a resonance (Belyaev et al., 1990).

IAR have been observed in the induction coil magnetometer data at Eskdalemuir Geophysical Observatory, which is a British Geological Survey site (Beggan & Musur, 2018).

We have modelled the harmonic frequency separation (Δf) of the IAR, by modelling the Alfvén velocity and calculating the time taken for the wave to travel up and down the IAR cavity. We used the International Reference Ionosphere to model the plasma mass density and the International Geomagnetic Reference Field to model the magnetic field strength.

To find the average Δf from the data, we used machine learning to identify the IAR harmonics in spectrograms, and then automatically extracted the frequencies. We used a u-net (Ronneberger et al., 2015) which was developed by Marangio et al. (2020) to detect the IAR.

Figure a) shows the spectrogram for 05/03/2013 – 06/03/2013. The IAR harmonics are visible as bright fringes. The red line lowest in frequency is the average Δf extracted from the data, with subsequent red lines being 2 x Δf, 3 x Δf and 4 x Δf. These are plotted so we can see the Δf following the trends of the harmonics. The lowest white line is the modelled Δf, with higher white lines being higher orders. Generally, the model agrees fairly well with the data. Here, both the data and the model show Δf increasing from dusk to midnight. The data diverges from the model later on, indicating that the model does not accurately capture the ionosphere at this time.

Figure (b) shows the modelled Δf in green, Δf from the data in red and the absolute difference between them in blue, for March 2013. Overall, the data and the model agree well. On 21/03/2013, there is a greater difference between the model and data than other days. Examples like this will be investigated further.

We are now performing further analysis of the 9 year dataset, including a comparison of the data and model to foF2, sunspot number, Sym-H and Kp.

Figure showing two panels. The first panel shows a black and white spectrogram with horizontal features highlighted (IAR harmonics) and the second panel shows the IAR Harmonic frequency separation at Eskdalemuir for March 2013.
Figure a) Spectrogram of data from noon to noon on 05/03/2013 – 06/03/2013. IAR harmonics are visible as bright horizontal fringes, from around 19:00 – 02:00. The red line shows Δf extracted from the data and the white line shows the modelled Δf. b) Model Δf (green), data Δf (red) and absolute difference between model and data plotted for March 2013.

References:

Beggan, C. D., & Musur, M. (2018). Observation of Ionospheric Alfvén Resonances at 1-30 Hz and their Superposition with the Schumann Resonances. Journal of Geophysical Research: Space Physics, 123 (5), 4202–4214. doi: 10.1029/2018ja025264

Belyaev, P., Polyakov, S., Rapoport, V., & Trakhtengerts, V. (1990). The Ionospheric Alfvén Resonator. Journal of Atmospheric and Terrestrial Physics, 52 (9), 781–788. doi: 10.1016/0021-9169(90)90010-k

Marangio, P., Christodoulou, V., Filgueira, R., Rogers, H. F., & Beggan, C. D. (2020). Automatic Detection of Ionospheric Alfvén Resonances in Magnetic Spectrograms using U-Net. Computers amp; Geosciences, 145 , 104598. doi:10.1016/j.cageo.2020.104598

Ronneberger, O., Fischer, P., & Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation. Lecture Notes in Computer Science, 234–241. doi:10.1007/978-3-319-24574-4 287

Acknowledgements:

BGS: www.geomag.bgs.ac.uk/operations/eskdale.html

IRI: www.irimodel.org

IGRF: https://www.ngdc.noaa.gov/IAGA/vmod/igrf.html

 

 

Jupiter’s X-Ray and UV Dark Polar Region

By Daisy May and Ben Sipos (St Gilgen’s School)

Jupiter produces powerful ultraviolet (UV) and X-ray aurorae at the planet’s poles. The emissions take on a variety of dynamic structures, particularly in the swirl and active regions (Figure 1). However, the dark polar region (DPR) consistently demonstrates a lack of auroral emissions. 14 simultaneous Chandra X-ray Observatory and Hubble Space Telescope observations of Jupiter’s Northern aurorae (between 2016 and 2019) revealed that no statistically significant X-ray signature is detectable within the DPR. 

There were two potential non-DPR sources that might have contributed DPR photons, that needed to be considered.  The first source was scattered solar photons. By shifting a region the same shape and size as the observed DPR across non-auroral longitudes of the planet, and scaling the photon counts to the duration of the HST observation, we determined the expected number of scattered photons in the DPR for each observation (0.3 to 1.4 counts depending on the DPR size, distance to Jupiter, and solar activity).

The second source was emissions perceived to have come from within the DPR due to the spatial uncertainty of the X-ray Observatory. To determine the count of such photons, we simulated where photons that were produced from the active and swirl regions would have been detected when passed through the spatial uncertainties applied by the X-ray observatory. After 100,000 simulations for each observation, we determined the count of such falsely detected photons, and found that there is no statistically significant X-ray detection from the DPR for these 14 observations.

The lack of x-rays implies low levels of precipitation by solar wind and energetic magnetospheric ions in the DPR. Therefore, the observations are consistent with the DPR being associated with either:  Jupiter’s open field line region and/or the DPR containing different potential drops or an absence of the strong downward currents and/or wave-particle interactions present across the rest of the polar aurorae.

This research project was undertaken with the Orbyts programme which partners scientists with schools to support school student involvement in research and to improve inclusivity in science. This nugget was written by two school students who produced a significant proportion of the work in the associated paper.

Figure 1: Overlaid simultaneous UV (blue-white-red color map) and X-ray photon (white dots) longitude-latitude maps of Jupiter's North Pole, from the Hubble Space Telescope (HST) and Chandra X-ray Observatory High Resolution Camera (CXO-HRC). Dates and times of the observations (UT) are at the top of each panel. Only UV and X-ray emissions produced during this time window are shown. Jupiter’s main emission is labelled by white arrows, the dark polar region (DPR) is shown in yellow, the Swirl region is shown in pink and the Active Regions (sometimes split into a noon and dusk active region) are shown in Green. The boundary between the active region and swirl region (here labelled with a white “B”) sometimes includes an arc of UV and X-ray emission, as is the case for the two different observations shown in the top two panels here. The other panels highlight three different UV aurora families, as indicated by the white label in the lower left corner of each (Grodent et al. 2018). The white shape overlaid onto each map is consistent across each, and highlights the changing spatial distribution of X-rays for each. For each panel, the location and extent of the DPR are indicated with yellow arrows, showcasing its changing extent from observation-to-observation.

 

References: Grodent, D., Bonfond, B., Yao, Z., Gérard, J.-C., Radioti, A., Dumont, M., et al. (2018). Jupiter’s aurora observed with HST during Juno orbits 3 to 7. Journal of Geophysical Research: Space Physics, 123(5), 3299– 3319. 

Associated Paper: Dunn, W.R., Weigt, D.M., Grodent, D., Yao, Z.H., May, D., Feigelman, K., Sipos, B., Fleming, D., McEntee, S., Bonfond, B. and Gladstone, G.R., 2022. Jupiter’s X‐ray and UV Dark Polar Region. Geophysical Research Letters, p.e2021GL097390.

Data Assimilation and the Solar Wind

By Harriet Turner (University of Reading)

Data assimilation (DA) combines model output and observations to form an optimal estimation of reality. It has led to large improvements in terrestrial weather prediction, reducing the “butterfly effect”, by which small errors in the initial conditions can grow non-linearly and lead to large errors in the subsequent forecast.

DA has been used in three main areas for space weather forecasting: the ionosphere, the photosphere, and, more recently, the solar wind. The first attempts at using DA for solar wind forecasting has shown promise, with a reduction in forecast error (Lang, 2021).

I have been using the Burger Radius Variational Data Assimilation (BRaVDA) scheme (Lang, 2019). This uses output from a coronal model with a computationally efficient solar wind model (HUX; Riley and Lionello, 2011) to map information from in-situ observations at Earth’s orbital radius (215 solar radii), back to the HUX inner boundary at 30 solar radii. The inner boundary conditions are then updated, given the information from the in-situ observations. This update is then run forward in time, again using HUX, to produce a reconstruction of the solar wind. This can then be used for forecasting.   

We have three sources of observations: STEREO-A, STEREO-B, and the OMNI dataset for near-Earth space. For the purposes of my work, I am using a simple corotation to produce a forecast. We can compare this forecast against observations from the three sources to assess its performance. Recently, I have been looking at testing the performance of BRaVDA with real time data. Previous experiments have used cleaned-up, science-level data, but real time data would need to be used for an operational DA scheme. Initial results show that using the real time data does not worsen the forecasts significantly and is still an improvement from a 27-day persistence forecast, as shown in Figure 1, which is promising for future implementation of solar wind DA.

 Three panels of plots showing the mean absolute error for the science data, the real time data and the 27-day persistence. The first panel shows the data at Earth, where the errors are smallest for a short lead time. The second panel shows the data at Stereo-A, followed by the third panel showing the data at Stereo-B. The real-time data has slightly higher mean absolute errors. In all three panels the mean absolute error increases for longer lead times.

Figure 1: Mean absolute error (MAE) of solar wind forecasts as a function of forecast lead time, for the case where OMNI, STEREO-A and STEREO-B observations are assimilated together. The black line shows the forecast where the science-level data was used and the red line when real time data was used. The dashed grey line shows the average 27-day persistence MAE for the specific spacecraft. The left-hand panel shows the forecast at Earth, the middle panel shows the forecast at STEREO-A and the right-hand panel shows the forecast at STEREO-B. This covers the period from 01/04/2012 to 01/10/2013.

 

References:

Lang, M., & Owens, M. J. (2019). A Variational Approach to Data Assimilation in the Solar Wind. Space Weather, 17(1), 59 – 83. Doi: 10.1029/2018SW001857.

Lang, M., Witherington, J., Owens, M. J., & Turner, H. (2021). Improving solar wind forecasting using data assimilation. Space Weather, 1 – 23.

Riley, P., & Lionello, R. (2011). Mapping Solar Wind Streams from the Sun to 1 AU: A Comparison of Techniques. Solar Physics, 270(2), 575 – 592. Doi: 10.1007/s11207-001-9766-x.