Astronomy Project Ideas

Sunspots were first discovered by Galileo Galilei in 1612. Galileo made regular observations of sunspots and was able to prove that he was seeing features on the surface of the sun, which moved as the sun rotated. (Another interesting project involving sunspots is to recreate Galileo's experiments using satellite imagery that you can collect online. See Using the Solar & Heliospheric Observatory Satellite (SOHO) to Determine the Rotation of the Sun.)

What is a sunspot, anyway? The SOHO Explore Glossary defines a sunspot this way: "a temporary disturbed area in the solar photosphere that appears dark because it is cooler than the surrounding areas. Sunspots consist of concentrations of strong magnetic flux. They usually occur in pairs or groups of opposite polarity that move in unison across the face of the Sun as it rotates." (SOHO Explore Glossary, 2006)

To see what sunspots looks like, here are two images of the sun's photosphere, taken by the Solar and Heliospheric Observatory (a joint project of NASA and the European Space Agency). The one on the left was taken on November 15, 1999. The one on the right was taken on February 20, 2006.

Solar and Heliospheric Observatory (SOHO) Michelson Doppler Imager (MDI) intensitygrams, showing the brightness of the sun's photosphere in visible light. Dark areas are sunspots. White box indicates the region covered by high-resolution imager. The image on the left was taken on November 15, 1999. The image on the right was taken on February 20, 2006.

For more solar images, check out the SOHO links in the Bibliography. The EIT (Extreme ultraviolet Imaging Telescope) images show the sun's atmosphere for specific wavelengths in the ultraviolet region of the spectrum. For example, at 171 angstroms (one angstrom is one ten-billionth of a meter, or 10^-10 m) the UV light is mostly emitted by Fe IX and X (iron ionized 8 or 9 times) at 1 million degrees Kelvin. Iron emissions provide visualization of the magnetic field lines. Here are two examples of these amazing images, corresponding to the same dates as the visible-light images, above:

Solar and Heliospheric Observatory (SOHO) Extreme ultraviole Imaging Telescope images at 171 angstroms. The image on the left was taken on November 15, 1999. The image on the right was taken on February 20, 2006. Compare to visible light images from the same dates, above.

We've come a long way from Galileo's telescope in 1612! But as you'll see, there is still value in data from hundreds of years ago. We have annual data on sunspot numbers going back to 1700, and monthly data to 1749. The sunspot number for an observation is equal to the number of individual sunspots observed plus ten times the number of groups of sunspots observed. The reason for doing this is that viewing conditions are not always ideal, and an average group has about ten sunspots. This way, the data is reliable even when small spots are hard to visualize. The monthly sunspot number is the average of all the daily numbers for the month. Below are two graphs of the monthly data.

Monthly sunspot number, 1749–2005, shown at two different vertical scales.

The data is the same in both graphs; it is just shown with two different vertical scales. It is obvious from both graphs that sunspot activity is cyclical, with the numbers regularly rising and falling. The tick marks on the horizontal axis are at 11-year intervals, the approximate length of the solar cycle. For example, if you compare the tick marks over the period from 1838 to 1893, you see that they fall at about the peak of each of those cycles.

The reason for showing two graphs is to show you that sometimes you can discover something new in your data just by looking at it differently. The top graph is how the data would appear with typical default settings of a graphing program. Typical default settings will produce a graph with an aspect ratio (horizontal length divided by vertical length) of about 1.6, and a y-axis scale chosen so that the data fills the graph region. These settings produce a reasonable-looking graph, and the cyclical nature of sunspot activity is readily apparent.

Compare the two graphs carefully, though, and see if the lower graph shows you anything more. The lower graph is made following an idea from William Cleveland. He used a computer algorithm to select an aspect ratio so that selected line segments in the data would have a slope of ±45° (Cleveland, 1994, cited in Tufte, 1997). In the upper graph, the sunspot cycles all rise and fall steeply. This makes it difficult for your eye to notice any subtle patterns in the cycles. Cleveland's idea is to select an aspect ratio so that the rising and falling slopes are closer to a ±45° angle, on average. Showing the data this way makes it much easier for your eye to see subtle patterns in the cycles. For example, compare the onset of each cycle to the decay. The onset time is the time from the beginning of the cycle to the maximum of the cycle. The decay time is the time from the maximum of the cycle to the end of the cycle. Are they about equal, or is one longer than the other? Which has a steeper slope? This comparison is much easier to make in the lower graph than in the upper one.

For some of the cycles, the onset time and decay time look fairly similar. For others, it appears that the onset time is shorter than the decay time. Is there a way to measure how strong the effect is? By answering these kinds of questions, we can get a better understanding of the solar physics underlying sunspots.

In this project, you will learn how to use basic statistical analysis of the historical data to test the hypothesis that sunspot cycles consistently have a faster rise time and a slower decay time. As an added bonus, you'll learn the basics of working with a spreadsheet program.

Terms, Concepts and Questions to Start Background Research

To do this project, you should do research that enables you to understand the following statistical terms and concepts:

• sunspots,
• parts of the sun:
  • core,
  • radiative zone,
  • convective zone,
  • chromosphere,
  • photosphere,
  • corona;
• sunspot cycle,
• statistical terms:
  • population,
  • sample,
  • mean,
  • standard deviation,
  • variance,
  • null hypothesis,
  • t-test,
  • statistical significance.