16 Years Staring at the Sun (without sunglasses)
The data we are using for this stage of Sunspotters comes from the Michelson Doppler Imager (MDI; Scherrer, 1995) instrument, which is on-board the Solar and Heliospheric Observatory (fact sheet; shown in images above).
SOHO orbits the Sun between the Sun and Earth at the first Lagrange point (L1). Enjoy a video of SOHO being launched into space on board an ATLAS rocket. An L1 orbit allows uninterrupted views of the Sun, without the Earth or Moon getting in the way. The MDI instrument was turned off in 2011, but successfully took data for about 16 years.
Around 60,000 magnetic images of the Sun’s surface were beamed back to Earth over this time interval, and have allowed the study of the magnetic properties of sunspots and the Sun as a whole over more than an entire 11-year solar cycle. In this project we take advantage of these features to study the magnetic complexity of sunspot groups over a long timescale and with regards to eruptive activity.
The current dataset used in Sunspotter includes cut-out images that are based on the locations of sunspot groups determined by hand (by the National Oceanic and Atmospheric Agency and the US Air Force; Figure 14). The current dataset includes around 10,000 images, and will allow us to determine the relationship between sunspot group magnetic complexity and other magnetic properties, such as magnetic area, flux, polarity imbalance, and the length of the polarity separation line (separating positive and negative regions of a given sunspot group image).
Making Sense of the Data
We have processed the data in a specific way to aid volunteers in comparing the sunspot group images. The thick white line shows the limb of the Sun (beyond the limb lies outer space). MDI provides us with images of the whole disk of the Sun. We have cut out images of sunspot groups centered on a set of human detections, as explained above. The cut-outs end up being all different sizes, so we buffer out the smaller ones with generated noise to make them a uniform size.
Within the images you will see blobs of white and black. White areas represent magnetic fields oriented toward the observer, and black areas represent magnetic fields oriented away from the observer. If you could put a bar magnet on the Sun, the magnet would look white when facing one way, and black when facing the other way.
However, not everything you see in these images is a magnetic field (or necessarily even a physical feature, for that matter). The following images show some examples of odd looking stuff you’ll find in the data. We have tried to explain the cause of each observed feature, below.
You will probably notice that the sunspot groups have a rectangular boundary. This is due to the detection algorithm we used to extract each sunspot group. We get rid of all the stuff that we do not consider to be a part of the sunspot group in question. It is an arbitrary choice of what to keep and what to get rid of, but one that has to be made- at least it is done in a uniform manner. You will be able to see a ‘context’ image of what exists outside of this rectangular area after making a classification and going to the ‘Profile’ tab. We buffer out the images to the same field of view so that one can compare the scale of the features in the images. We are discussing the possibility of removing the scale information in the next batch of data (to remove the potential bias that larger spot groups would always be judged to be more complex- which should not always be the case…).
Very rarely, a scratchy speckled pattern will be seen, like that shown in the image above. This is due to a large eruption being launched from the Sun, that actually hit our spacecraft! The scratches and speckles are energetic particles (e.g., protons), travelling close to the speed of light that hit our camera and were recorded, while we were trying to take a picture of the Sun. Its kind of like trying to film a tornado in Kansas, and your film crew keeps getting hit by airborne cows. Movie of the ‘Halloween Storm’ in 2003; pay attention at ~8 seconds into the movie.
The black line seen at the bottom of the feature in this image is likely due to MDI’s camera not recording certain pixels. Once in a while a large block of data (not shown here) may go missing, and this tends to occur when the ground station on Earth was in the process of receiving data and an interruption occurred, resulting in the loss…like having dropped cell-phone call.
These images show sunspot groups during their emergence phase. The first and last images show pairs of sunspots (one positive/white, and the other negative/black) bursting through the solar surface. They often show a characteristic double-C shape, like two lions roaring at each other, face-to-face. The middle image shows a sunspot pair emerging (in the top left corner of the image) into an already established sunspot group (the stuff in the center of the image). One explanation for the double-C is that it is the result of helical magnetic fields passing through the solar surface (all you can see is the cross-section). Here is the best example I have ever seen, as noted by Sunspotter volunteer, @artman40.
Often, you will notice that circular blobs of a given polarity will have an edge that appears to be of the opposite polarity. It will always be the edge facing the limb (edge) of the Sun. These circular blobs are sunspots, and because their magnetic fields fan out at their boundaries (penumbrae), this can cause a ‘false’ polarity to be observed when the sunspot is near the limb of the Sun, because of the way that we measure magnetic fields with this instrument. The ‘true’ polarity of a sunspot is the one that is on the edge facing away from the limb of the Sun. In the images above, the first sunspot is ‘truly’ positive/white, the middle one is ‘truly’ positive/white, and the last one is ‘truly’ negative/black.
The ‘hollowed-out’ artifact seen in the leading sunspot is due to a saturation effect, as noted by Sunspotter volunteers @Quia and @Mjtbarrett. The problem is that for MDI, much of the data was processed on-board the spacecraft. Because of the way that the processing was designed from the beginning, the model used to calculate the magnetic fields broke down for very large fields (>2000 gauss), resulting in the saturation. Unfortunately, the effect isn’t even linear, so even at lower fields (1k-1.5k G) you start to see problems. Also, the non-linearity makes it hard to correct for.
A paper on the effect is available. In a future blog post, we will explain the making of a magnetograms, and also touch on the saturation problem.
Often, there will be nothing to see at all. This is usually because the sunspot group that was recorded by human observers at the beginning of the day has already progressed beyond the edge of the Sun by the time our spacecraft took the data. And since we are relying on human observers to pick out sunspot groups in the current data set, sometimes we end up with nothing…
Last but not least: this is an image of a particularly large sunspot group that released many significant eruptions (some of the largest that we know of!). Note the elongated strip of negative (black) magnetic flux, sandwiched between the two areas of positive (white flux). This sandwiching may have caused the shearing and stretching of the fields to the point of breakage. The double polarity separation line pattern seen here (tracing the dividing line between the white and black areas) is of particular interest to me, as I am convinced it that it is often a sign that a large eruption could occur.
If you come across any other interesting artifacts or patterns in the data, save them by going to the ‘Profile’ tab in the main sunspotter interface. There is plenty to discover about what makes sunspots go boom!
Sunspots emerge in groups, and their configuration varies in complexity (as you can see when you click through a few classifications). But, what does complexity really mean?
Allow me to start where many of my research projects start- Wikipedia 🙂 -which defines complexity as follows:
- Complexity characterises something with many parts in intricate arrangement.
- ‘Complexity science’ is the study of the phenomena that emerge from a collection of interacting objects.
- Displaying variation without being random.
In our case, something = a sunspot group, parts = sunspots, phenomena = eruptions emerging from a group of sunspots… and so on. Since we are using magnetograms to study sunspot groups, we define the ‘parts’ as regions of a given polarity (positive/white or negative/black) within a given sunspot group. Thus, to describe a sunspot group as simple (the opposite of complex), we consider whether a straight line could be drawn, so that all the white areas of the image are on one side and black on the other.
Panel A in the above image shows a simple ‘bipolar’, with basically one area of white and one of black (an even more simple configuration would be all white or all black). A more complex region, like the one shown in the panel B, would require a more curvy (possibly more than a single line) to divide the image into white and black regions. An image of countless white and black spots (like that shown in the rightmost panel) appears to be random (like noise), and thus simple. So, true complexity lies between the two extremes of being uniformly white/black and being composed of random speckles of white and black. Unfortunately, computers have a hard time finding that sweet spot of true complexity, but humans can spot it quite easily– looks like 3.5 billion years of evolution for the human brain was worth the wait!
The top row of images shows the configuration of the magnetic field in the solar atmosphere above the sunspot groups; hot, bright gas is confined to magnetic loops, much like iron filings being confined to the magnetic field of a bar magnet. The bottom row shows the magnetic ‘footprint’ of the above magnetic structures.
There is currently a sunspot group ‘classification’ system which is used as a ‘proxy’ or place-holder for complexity, since the real thing hasn’t been measured yet. Experts at observatories around the world sort images of sunspot groups into several classes. The most simple class is ‘alpha’: one polarity of magnetic field (bottom-left panel.). Slightly more complex is ‘beta’: two polarities, or bipolar. A classification of ‘gamma’ is more complex, and indicates that the polarities are mixed together (i.e., essentially that a single, fairly straight line cannot divide the regions of white and black). There are other variations of these basic classifications, that are part of the ‘Hale’ or ‘Mt. Wilson’ classification scheme. The Hale scheme relies on both magnetograms and visible light images of sunspot groups.
Another widely used scheme is called the McIntosh system The drawback to using these schemes for indicating complexity is that there are only a few broad classes and it is not entirely clear how these classes should be ordered in terms of complexity. On the other hard, we want a continuous measure of complexity, like a scale from 1-100, with arbitrary precision; basically a meter stick for sunspot group complexity.
Lots of previous work (Abramenko 2005; McAteer et al. 2005; Ireland et al. 2008; Conlon et al. 2008; Hewett et al. 2008) has sought to design an algorithm that could indicate the complexity of a sunspot group. A common method utilises the concept of ‘fractals’. The fractal dimension of a 2D object can range between 1 (a line) and 2 (a square). It has been found sunspot groups with certain fractal dimensions are somewhat more likely to produce flares. More recently, Georgoulis (2012) has shown that the association is marginal at best. Moreover, fractality is incredibly hard to interpret physically.
Other proxies for complexity consider the magnetic connectivity between different areas within a sunspot group (Georgoulis & Rust 2007; Ahmed et al. 2010). Properties based on connectivity scale much better with sunspot group flaring than fractal dimension. However, the relationship between these properties and ‘complexity’ is not clear. Also, these properties cannot be accurately determined away from the center of the observed solar disk, due to foreshortening (since the Sun is a sphere, the sunspot groups get squashed at the edges).
This plot shows the Hale class of a large sample of sunspot groups (colored symbols), the size of each group (horizontal, X-axis) and the magnitude of the largest solar flare produced by each group (vertical, Y-axis). The point is that larger and more complex sunspot groups produce larger flares, which is very important in solar flare prediction, and supports our motivation for running Sunspotter.
By the way, you may enjoy some interesting TED talks related to the idea of complexity that put this abstract concept into a more practical light:
- Nicolas Perony on the interface between Puppies and Complexity Theory
- Stephen Wolfram on using Chaos theory to achieve a ‘Theory of Everything’
- Benoit Mandelbrot on the discovery of Fractals
Complexity is difficult to put into words. If you have an ideas about complexity you would like to share, lets discuss it on Talk or the comments section below!
Hello citizen scientists! As leader of the Sunspotter science team, it is my job to welcome you to the project. If you would like to learn something about solar activity, and what makes the Sun such an interesting system to study, then I’m sure you will enjoy following this blog. And, as the project develops, we will keep you up to date on what we are learning from your classifications.
I am a solar astrophysicist and have spent the last few years investigating what makes sunspots tick. Sunspots are like animals – they are born, they grow and change, and then slowly they decay and fade away, leaving barely a trace (the trace they leave is important, but I’ll explain that in a future blog post). They live for a couple of weeks, and although their lives are short, from time to time they release the most powerful (in energy per time) events in the solar system: solar flares. It is my job to study the evolution of sunspots to determine when and why they release flares, in an effort to predict them; much like a weather forecaster on Earth, I try to forecast space weather. This is important work because adverse space weather resulting from solar flares can jeopardise our GPS system, affect the health of our astronauts, inhibit long range radio communications, endanger our power grid, and the list goes on…
If you have already tried a few classifications, you may have noticed that the images of sunspots shown do not look like a dark spot on a bright Sun, they look more like a mix of black and white on a gray background. This is because they are maps of the sunspot magnetic fields (a.k.a., magnetograms). Magnetic fields are what make the Sun and especially sunspots (where the strongest magnetic fields are) so interesting.
We use computer programs to automatically track sunspots and calculate their various physical properties. For example, we determine the area they cover on the Sun’s surface, their maximum magnetic field values, their total magnetic flux (magnetic field times area) and so on. We have found that the properties most likely to help us predict the future occurrence of eruptions are related to the line(s) separating the black and white areas of the magnetogram, known as a polarity separation line. For example, a sunspot group is much more likely to flare if it has a long line separating the white and black areas, rather than a short one.
It is also known that the more complex a sunspot group is, the more likely it is to flare. Thus, we seek to reliably measure the complexity of sunspot groups. And this is where you come in … and where computers fail, since they cannot yet determine the complexity of an image in a meaningful way. Humans on the other hand, have a pretty easy time of indicating which is the more complex of a pair of images. Scientists have been trying (pretty unsuccessfully) to come up with a way to represent the complexity of sunspot groups for a long time. The Sunspotter project might just be the golden ticket!
So, please help us reliably measure the complexity of our sunspot group images. The results of this project could lead to significant advances in our ability to predict flares. This is only phase 1 … stay tuned for more!
¡Bienvenido a nuestro blog curioso voluntario!
El proyecto SunspotZoo consiste en crear una nueva clasificación de manchas solares a base de muchos voluntarios como tú. Este proyecto fue aceptado dentro de la familia de Zooniverse recientemente y durante estos meses estamos averiguando que es lo mejor que les podemos preguntar para conseguir los resultados deseados.
¿Y cuáles son esos resultados? estarás preguntándote. Pues bien, seguramente habrás oído que las manchas solares producen unas fulguraciones, conocidas en inglés como flares, que tienen cierto efecto en nuestro planeta (ya comentaré sobre esto en otra artículo en un futuro no muy lejano). La predicción de estas fulguraciones es vital si salimos del escudo protector que el campo magnético terrestre nos ofrece. Junto con estas fulguraciones, una gran cantidad de partículas a altas energías son eyectadas del sol a altísimas velocidades, recorriendo la distancia entre el sol y la tierra en menos de 30 minutos. Imagínate lo desagradable que podría ser que te pille una de estos chorros de partículas en tu viaje de vacaciones a la Luna. Vale, de acuerdo, todavía nos quedan unos años para ese tipo de aventuras… pero los astronautas del Apollo 17 se salvaron por los pelos. Es nuestro propósito, y con la ayuda de todos ustedes, de conseguir una nueva clasificación de manchas solares que nos permita predecir con antelación estos eventos.
Por supuesto ya hay varias clasificaciones de manchas solares, unas más nuevas que otras (también recordaré escribir sobre los distintos tipos algún otro día), pero ninguna nos ofrece un sistema de predicción por si misma, y es eso nuestro principal objetivo. ¿Cómo? Pues aún no lo sabemos, pero será algo del tipo “¿cuál de estas dos manchas solares te parece más compleja?”. Y la gran pregunta… ¿por qué ustedes? pues simple, lo podríamos hacer nosotros, expertos en el campo, pero nos llevaría años para clasificar todas ellas, por eso optamos por desarrollar códigos que lo hiciesen automáticamente, y bueno, eso nos ha ayudado a extraer ciertas propiedades (tamaño, intensidad,…) pero no hemos conseguido extraer las que parece importar, por ejemplo, complexidad. Sin embargo, nuestros ojos hacen eso naturalmente, como por intuición, nos dice que una cosa parece más compleja que otra. Así pues, con la ayuda de todos ustedes podemos conseguir en pocos días lo que nosotros tardaríamos años, permitiéndonos estudiar los resultados desde ahora mismo y poder mejorar así los sistemas de predicción.
No puedo asegurarles a partir de que fecha tendremos los datos preparados para clasificar (si estás impaciente por ayudar a la ciencia, no dudes participar en alguno de los otros proyectos disponibles), pero hemos hecho tres pruebas con un número reducido de personas. La primera era con un grupo de estudiantes de bachillerato que visitaron al equipo de Dublín (Irlanda), la segunda consistía en un grupo de 20 científicos que trabajan conmigo pero que no son expertos en el sol, y en la última nos pusimos a prueba nosotros mismos y a unos cuantos amigos más (no expertos). El test consistía en clasificar 15 manchas solares comparándolas una con otra en tamaño, intensidad, complexidad y compacidad. Los resultados de los dos primeros tests están aún siendo investigados, pero aquí les presento el nuestro, que acabamos de presentar en el encuentro astronómico del Reino Unido ( NAM) esta semana. En el poster (en inglés) se visualiza el grado de concordancia entre los distintos sujetos para las distintas preguntas.
Como se puede observar, tamaño, intensidad y complejidad presentan resultados similares, en cambio hay una mayor discrepancia en compacidad. Ya veremos que encontramos con los resultados de los otros dos tests.
Espero que les haya abierto el apetito para ayudarnos a encontrar las claves para entender las manchas solares.