Hello, I’m Luke and I work with Chris Scott (formerly Davis!) at the University of Reading as a postdoctoral research assistant. Recently I’ve been doing some work with the large amount of Trace-it data that has been generated over the last few years. We thought it was a good time to update everyone on the work we have been doing.

The short story is that we have turned the roughly 40000 time-elongation (t-e) profiles generated by Trace-it into a catalogue of CMEs seen by Heliospheric Imager (HI) instruments aboard STEREO-A (STA) and STEREO-B (STB). The Solar Stormwatch catalogue provides profiles of the CME fronts in the remarkable field-of-view (FOV) of the HI instruments. The HI FOV covers regions of the inner heliosphere not accessible to the coronagraph instruments that are more commonly used to build CME catalogues. Therefore the Solar Stormwatch catalogue should allow us to study the structure and dynamics of CME fronts in a way not previously possible using other presently available CME catalogues. This has been written up into a paper which is currently under review for publication in the journal Space Weather. So, first things first, thank you to everyone that has contributed to Solar Stormwatch. I think that we have produced a useful catalogue of CMEs, which will hopefully be of use to the wider space weather community – this wouldn’t have been possible without all of the contributors to Solar Stormwatch.

Let’s begin with a quick review of the raw data produced by Trace-it. Trace-it analysed J-maps made from HI1 and HI2 images, for both STA and STB, over 18 distinct position angles separated by 5 degrees, except for one position angle, which was centered on the ecliptic plane.

The J-maps covered a time span of January-2007 to February-2010. As of a few months ago, the Trace-it results consisted of database of 38171 t-e profiles, 22007 from STA and 16164 from STB, generated by 4599 Solar Stormwatch users.

If elongation angles and position angles are unfamiliar to anyone reading this, Figure 1 shows an image from HI1A, over which contours of constant position angle (in blue) and constant elongation angle (in red) have been overlaid, to make these coordinates clear.

Figure 1. An example of a differenced image from the HI1A camera, overlaid with contours of

constant PA (in blue) and constant elongation angle (in red). The elongation and PA contours

are in 5◦ increments. A CME is visible to the right of the image, between 5◦ and 10◦ elongation

and with maximum extent in PA between 65◦ and 135

To separate the t-e profiles into groups which represent individual CMEs we looked for periods when many t-e profiles were clustered in a short space of time. To do this, we counted how many t-e profiles began in a 7-hour window, for every hour covering the data set, and whenever the count of profiles was higher than a threshold of 22 counts we defined that as an event. This happens whenever lots of us have seen features over multiple position angles but at similar times. Figure 2 shows an example of this. Panel A) shows a STA J-map, at PA=110 degrees, overlaid with the t-e profiles generated by the Solar Stormwatchers as red dots, whilst the blue dots mark the earliest occurring point in each profile. In this instance, this position angle was tracked 11 times by 8 different Solar Stormwatchers. Panel B) shows the count of these profiles as a function of time, using the 7 hour sliding window. Note that this count is done over every position angle, whereas the J-map shows the t-e profiles at one position angle only. There is a well defined maximum in the count, which we use to define the onset of this event and identify the t-e profiles that describe it. The thresholds we picked are arbitrary but sensible, we could have used different ones and had similar results – for anyone interested in how we picked these numbers, we go into a bit more detail in the paper.

This gives us groups of t-e profiles for each CME – 113 from STA and 80 from STB. However, we had to do a bit of quality control, as it is not good enough just to have to t-e profiles that start at similar times – they could come from coincident but unrelated solar transients that are widely separated in position angle. So we used another set of rules to exclude any t-e profiles which look like they may belong to a different solar transient. This process is detailed more in the paper, but the result of it is that we have to discard 6 events that we are too unsure about, 3 each from STA and STB. This leaves us with 110 events from STA and 77 from STB.

At this point, we have defined sets of t-e profiles which we think robustly identify CMEs seen by the Solar Stormwatchers. The next step is to average these profiles along each position angle the event was observed. An example of this averaging is shown in Figure 3. The black dots show the t-e profiles generated by the Solar Stormwatchers for one event and along one PA, which includes 13 t-e profiles, generated by 9 different Solar Stormwatchers. The red-dots and red-lines show the average profile and the uncertainty in the average profile.

Figure 3. An example of an average t-e profile, for CME number 59 from STA, tracked along a PA of 110 degrees. The black dots show the individual t-e profiles and the red dots mark the consensus profile while the two red lines indicate the uncertainty in the mean time coordinates.

Now we can turn this around and overlay the average t-e profiles for each position angle back onto the original differenced images that made the J-maps they were tracked in. Figure 4 shows a movie of the evolution of an event through the HI1A field-of-view. The yellow lines mark the maximum extent of PAs that the J-maps used by Stormwatch cover, whilst the regions bounded in red mark the locations where the consensus profiles (like figure 3) suggest the CME front should be. The width of the bounded region arises from the uncertainty in the consensus profile at that position angle, so that wider regions mean we are less sure where the CME front is.

Figure 4. This movie shows a sequence of HI1A differenced images in which a CME can be seen to enter and propagate across the HI1A field-of-view. The yellow lines mark the outer limits of the position angles of the J-maps analysed by Trace-it. The red lines mark the location of the CME front, and are calculated from the averaged t-e profiles (see Figure 3) along each position angle the event was tracked.

We are in the process of making this CME catalogue available in an easily usable form so that the rest of the space weather community can get involved and hopefully start using it for some research. In November we will be taking this work to the European Space Weather Week conference in Belgium, to present this work to other researchers. In the meantime, we have some plans for some things we would like to do with the Solar Stormwatch catalogue, which we will update you with when there is more to say.

Thanks!

You may have noticed a bit of a splash in the press last Thursday, when I and my co-authors at the University of Reading had a study published showing that the solar wind appears to affect lightning rates over Europe. If you are interested, you can download the paper here;

Environmental Research Letters, Solar wind modulation of lightning;

or, if you don’t fancy wading through a scientific paper, you can see me trying to explain it without waving my arms around too much in a short video, here;

And, if neither of those approaches appeals, you can read on for a short summary of the work (I’m assuming you’re interested otherwise you wouldn’t have chosen to read this blog, right?).

It’s long been thought that cosmic rays (very energetic particles generated throughout the galaxy, accelerated on shock-fronts created by supernova explosions) could be responsible for causing electrically charged clouds to discharge to ground in the form of lightning. As the cosmic rays fall through the atmosphere, the argument goes, they ionise the air, free electrons get accelerated further by the electric field present in the cloud and a runaway breakdown of air results, ending in a lightning flash.

What does the Sun have to do with this? Well, the Sun is an active star with an eleven year solar cycle. The solar wind drags the solar magnetic field into space where it shields the Earth from some of the cosmic rays. When the Sun is active, the solar magnetic field around Earth is stronger and we see fewer cosmic rays reaching the ground. There is also evidence that there is less lighting at these times. So that’s the long-term view, but what happens over shorter timescales?

While you can use solar storms, or Coronal Mass Ejections (CMEs) as they are known, with their enhanced magnetic fields, to look for short-term enhancements of the interplanetary magnetic field, relatively few events travel Earthwards to make a statistical survey conclusive. Instead, we looked at fast solar wind streams. While these produce a smaller depletion in cosmic ray flux (around 1%) compared with CMEs (around 10%) they co-rotate with the Sun and so wash past Earth at regular intervals. We were expecting therefore to see a reduction in lighting but instead we saw that the lightning rates went up (there is a moral here; never try to anticipate the result of an experiment!). The answer, we think, lies with ‘solar energetic particles’ that are accelerated ahead of the solar wind stream, like surfers on a huge wave. While these do not reach the energies of cosmic rays, it is likely that they nevertheless are able to penetrate the Earth’s atmosphere to the height of thunder clouds where they presumably do a similar job to that thought to be done by cosmic rays in initiating lightning.

There’s loads more work to do in order to fully understand where these particles end up and how they influence lightning but if we can understand this effect, there is the tantalising possibility that we could use our observations of solar wind streams from space to forecast the severity of lightning events several weeks in advance. With around 24,000 lightning associated deaths occurring worldwide every year, anything we can do to predict the severity of lightning in advance has to be useful, doesn’t it?

While all this has been going on, we have been analysing the Stormwatch data too, and it’s been very informative. More on these results soon.

Thanks again for your enthusiasm and time, keep clicking! (don’t forget Trace It!)

Chris.

‘Here Comes The Sun’ is special one-off documentary for BBC 2 investigating the nature of the Sun during this period of heightened solar activity – the solar maximum. The presenters, Kate Humble and Helen Czerski, along with a team of experts will explore how the Sun works, how its secrets could power our future and what the current behaviour of the Sun means for us. One strand of the programme will focus on Space Weather Prediction: examining the fundamental mechanisms that cause solar storms, the impact they may have on the Earth’s infrastructure, and how scientists are working to predict this type of solar behaviour, which is why they are looking for your help…!

The team are coming to film at the Rutherford Appleton Laboratory (RAL), in Oxford, on the 28^th of February and 1^st March and are looking to recruit a group of around 20 UK-based Stormwatchers to come to RAL and be part of this programme! It is a wonderful opportunity to bring the Solar Stormwatch project into the public eye and illustrate the important job of every single Stormwatcher. It will be great fun and a good excuse to get together with other fellow Stormwatchers!

This is a great opportunity and we are hoping this exposure on a national level will encourage more people to get involved!!

If you are interested please do not hesitate to contact Fay Finlay for more information. Fay.Finlay@bbc.co.uk or 0141 422 6991.

Attention Stormwatchers!

Remember all that data analysis you’ve been doing for us? All those storms you’ve tracked in both archive and real time data have now been used to create an animation of what the Sun has been up to over the first three years of the STEREO mission. Over the summer, a student of mine, Amy Skelt, wrote a program to enable us to view your data analysis in a unique way. By taking all your CME tracking information and combining it with my analysis of smaller solar wind features, we can now create animations showing the activity of the solar wind throughout the first three years of the STEREO mission. Just in time for Christmas I’ve used Amy’s software to create a movie of the entire Stormwatch analysis so far. You can view the movie here;

It’s incredible! You can now see the constant stream of solar wind material as it erupts into space and even the spirals created as the various sources of solar wind rotate with the Sun. And when a solar storm erupts, you can see which planets are in the firing line!

We’ve had to make some assumptions about the rate at which the solar storms expand and so any differences between this movie and the real world will help us understand how realistic our assumptions are. Amy made the software very flexible so that you can view the solar system from a fixed point (as in the attached movie), from above or even from a moving object. You can even go for a ride on comet Encke and see how it fares as it rides the solar wind!

As usual, many, many thanks for your time and efforts so far. In the New Year my group and I at the University of Reading will be using your data analysis to investigate what we have learned so far about using STEREO HI data to make real-time forecasts. Working with the UK Met Office, we will ultimately be applying what we learn to improving the operational space weather forecasting model that they will be running. In the current climate, there is much talk of ‘impact’. I can confidently say that you are helping us with our impact. Both metaphorically and literally!

I hope that those of you that are about to celebrate Christmas have a wonderful holiday.

See you in the New Year for more Solar Storming!

Chris.

Finished working on automating the predictions from the clicks you give us on the incoming track it game and thought I would share with you some of the work you have been doing.

I have created a tool that allows me to plot all your clicks against a background of the realtime data you fitted – although of course I have the benefit to 20-20 hindsight, so the latest CME looked like this [the curve on the right hand side]

I also pick out clicks that failed to get through our event detection system, and for the same dataset that looks like

The near vertical feature is almost certainly due to instrumental effects, the near horizontal feature is a star or planet.

The data that does get through the event detection system is then passed to the data fitting system that shows the clicks and the fitted curve

and finally the CME speed and direction is 452km/s 42 degrees from Sun-Earth line and arrives at 1 AU at 2010-11-07 17:44.

Similar plots for the most recent data give us.

and

again there are vertical instrumental features that should be ignored. No event in this time range has been seen far enough from the Sun for us to make a meaningful prediction and so things have been a bit quiet on that front. Clicking on tracks as they are starting is however very useful in the event it does develop into a CME since that gives really good statistics for the start point and helps to constrain the fitting process.

Steve