How Much Did the 20 March 2015 Solar
Eclipse Affect Cosmic Radiation Levels?
Sam Gooch
Abstract
On the 20 March 2015, a solar eclipse of very high totality (greater than 90%) occurred across the
UK. Data was taken simultaneously across the country and sent back to be analysed. Approximately
twenty different centres collected data with a total of over 8000 frames being collected. In this
project, the results from this data are analysed and then interpreted. They suggest a maximum
decrease in background radiation levels of 46.3% about 70 minutes after the time of maximum
totality (about the time of last contact). This project then concludes with a discussion of the possible
implications and explanation of these results and an evaluation of the effectiveness and success of
the experiment.
1 A Background to the Experiment
Cosmic rays, as the name suggests, are rays of ionising radiation which originated from space (rather
than on the Earth). Our atmosphere protects us from the most dangerous types of radiation, such as
heavy ion fragments, causing them to split into alpha, beta and gamma radiation by the time they
reach the Earth’s surface. Cosmic rays have many different sources with the Sun being an important
factor but neutron stars, pulsars and other stellar bodies contributing as well.
As part of an extended research project over several years, I have been studying cosmic rays and
how they vary in intensity in different areas of the UK. Over twenty schools across the country are
part of our research group and possess a Medipix 2 detector. The detector uses a silicon chip to
record ionising radiation in a grid of 256x256 pixels to create an image of radiation, allowing
different particles, alpha, beta and gamma, to be identified.
On the 20 March 2015, a partial solar eclipse covered the whole of the UK with some regions of
Scotland experiencing up to 95% totality. This was a rare opportunity to study such an event with
our network of detectors across the UK.
Radiation levels were measured using a standard method[7] developed for the eclipse with each
centre collecting two hours of data, approximately one hour before until one after the maximum
totality of the eclipse. Data was then uploaded to our analysis site
(http://starserver.thelangton.org.uk/analysis) where it was processed using a set of algorithms
developed for analysing Medipix and Timepix data. I wrote two short programs in Python 3 to first
convert the records of each frame which were stored on a database from the analysis program to a
.csv file which could be downloaded for further analysis. Throughout the analysis, I used
standardised times with time = 0 being the point of maximum totality. This allowed results to be
directly compared as the time of maximum totality varied by almost ten minutes across the country
which would have created a disparity between data sets. I then made a program that went through
each .csv file, which corresponded to each upload of data, and used a dictionary to find first the sum
and then find an average count rate for each relative second within three hours of maximum
totality. I then used Excel to plot this data on a graph. The source code is included in an appendix.
2 Introduction
I decided to do this project as I have a keen interest in cosmic rays, radiation and space, more
generally. This was a rare opportunity to study such an event so I wanted to be able to put my
curiosity in the subject to good use and find new, previously unknown results. Apart from my own
desire to find out more, this research could provide an insight into the nature of the Sun’s role in
background radiation and cosmic rays as its normal effect will be greatly diminished throughout the
eclipse. Due to the relative rarity of eclipses, this effect has had limited prior study but the reports
are included in my research section. To my knowledge, this is the first study of the change in
radiation during an eclipse using the Medipix detectors which allow for multiple different particles to
be identified: all previous experiments measured only one type of radiation. This is also the largest
study, with more data being recorded and analysed than in previous tests.
Before starting the project and doing any research, I predicted that there should be a drop in
radiation levels since a major source of cosmic radiation is being blocked out and that the maximum
drop should take place around the time of maximum totality since this is when most of the Sun is
blocked out. This seemed like a reasonable assumption based on common sense.
3 Research and Literature Review
Full referencing of the sources below can be found in the bibliography
Source 1: Structure of the extended solar magnetic field and the sunspot cycle variation in
cosmic ray intensity
Before beginning my main research on the effect of a solar eclipse on cosmic radiation levels, I
researched the importance of solar activity on cosmic radiation intensity. This article was published
in Nature, a respected weekly peer review journal. It was published almost forty years ago but the
information and data that it contains is still relevant and has not changed since then as the data
describes the sun spot cycle – a cycle that repeats itself. The authors are part of the Institute for
Plasma Research at Stanford University in the USA – a prestigious university with a strong research
background. The article is therefore likely to be highly accurate and at a high level. The article begins
by discussing the variation in solar magnetic fields and the sunspot cycle which is not applicable to
my project. However, it then goes on to use this to explain some of the changes observed in cosmic
ray intensity. The results presented in the article suggest that solar activity is the main cause of
variation in the number of cosmic rays recorded, with approximately three times as many recorded
at some points in the sunspot cycle than at others. Although this article did not directly talk about
eclipses, it has been very useful: showing just how important the sun and solar events are in varying
levels of cosmic rays. It therefore seems likely that an eclipse will also have a significant, measurable
impact in cosmic ray intensity.
Source 2: Solar cosmic ray events for the period 1561-1994
The article mainly expands upon the conclusions drawn in source 1. Again, it is published in a peer
reviewed journal by members of reputable American universities. Unlike source 1 which mainly
discusses data from the middle part of the twentieth century, the article uses data gathered from
polar ice cores to obtain data about large proton events (another, rarer but more extreme form of
solar radiation to the type measured in the previous source and our experiment). As before, it is
suggested that, based on the results of their experiment, the Sun and its cycles seem to have a very
major impact on the frequency and intensity of these events. However, the article also states that
there seems to be other, currently unknown influence on these events. For example, the number of
solar proton events seems to be highest just after the peak in sunspots: an unexpected result. There
is not enough data to explain this and it may just be some anomalous readings. Regardless, this
article again confirmed that, whilst solar activity may not be the only influence on cosmic rays, it is a
very major one, again, suggesting that we will see a significant change in cosmic ray intensity.
Source 3: Variation of Cosmic Ray Intensity During the Solar Eclipse August 11, 1999
Having looked at the effect of the Sun on cosmic rays generally, I now began to look specifically at
previous studies on past solar eclipses. This article is published through the SAO/NASA Astrophysics
Data System. Although both organisations are highly reputable, the article is not curated by them so
its reliability should be questioned. However, it provides factual, objective data and provides
citations of other peer reviewed articles that support its results, suggesting that their results are
correct. The article documents the findings of a similar experiment to ours, measuring the change in
low energy gamma radiation whereas our experiment measures alpha, beta and gamma radiation.
The source therefore helps to predict the expected results for gamma radiation - a decrease of about
20% for a period just before the maximum totality until just before last contact. This is supported by
source 4, again, adding reliability to this experiment's results. The source has given me evidence
about a previous solar eclipse, helping me to predict the results of our experiment. It also suggests
when the drop in radiation levels is likely to take place - during the second half of the eclipse. This
was somewhat of a surprise as I expected the drop to be greatest at maximum totality so this will
require further investigation.
Source 4: Cosmic ray intensity and surface parameters during solar eclipse on 22 July 2009
at Kalyani in West Bengal
The article is published as a peer reviewed article in Current Science, a leading science journal in
India with a high academic reputation. The article supports the results from Source 3, again,
suggesting that the solar eclipse caused a large drop in the solar radiation reaching the Earth. A very
steep drop in radiation levels was noted shortly before the maximum totality, as with the other
experiments, with a drop in intensity of about 18%. The low intensity continued for approximately
two hours after the end of the eclipse before rapidly returning to previous levels. These are similar
values to the data from the experiment in Source 3, giving the results reliability. The data was also
captured in a very different geographical location and climate to the previous experiment and used a
different method: a Geiger-Muller tube, giving the results reproducibility. The article notes that the
weather was partly cloudy, particularly at maximum totality, which may have affected the results,
however, it is also stated that the drop in intensity of cosmic rays cannot be explained by weather
alone and that there must have been another factor, i.e. the eclipse. This reinforced what I had
already learnt and also provided some commentary on the effect of weather. This was particularly
useful as there was high cloud coverage over much of the UK on the day of the eclipse but this
source suggests that the eclipse would have still had a measureable effect on our results.
Source 5: Pixelman: a multi-platform data acquisition and processing software package for
Medipix2, Timepix and Medipix3 detectors
I decided that to finish my research, I should look further at the equipment that would be used to
capture and analyse the data in my experiment. I started by reading through the articles concerning
the use of Pixelman, the software used to capture the solar eclipse data. The article was published in
a peer review journal by the creators of the Pixelman software so it is likely to be highly accurate and
detailed. All authors are members of the Institute of Experimental and Applied Physics, Czech
Technical University in Prague so are highly experienced and skilled in the field. The source discusses
the use and workings of the software, giving instructions on how the output functions and provides
a high level view of how the software works in order to produce the data. Reading through the
source has allowed me to gain a better understanding of Pixelman and judge the effectiveness of it
in order to capture radiation data. The source is well referenced and provides sufficient detail on the
use of the software to make Pixelman seem a reasonable and useful program for the experiment.
Source 6: Timepix, a 65k programmable readout chip for arrival time energy and/or photon
counting measurements
The Timepix chip is made by the same group as the Medipix 2 chip used in our experiment. It is
slightly more advanced but the chip architecture and processes are very similar, especially in Time
Over Threshold (TOT) mode, which was the one used in the experiment, where there is almost no
difference between the two chips. The article is written by the scientists who developed the chip at
CERN. The authors are therefore highly knowledgeable about the chip design and its
implementation. It is possible that they may be biased in regards to its potential and uses but as any
claims about the technology could be easily checked by academics (which they have through its
constant use in various experiments), it seems credible that the article is highly factual without bias.
The article begins by discussing the physical chip design, making it clear exactly how each pixel works
to obtain its data. The article then goes on to explain how the different modes work to produce the
256x256 pixel readout, also evaluating their accuracy. In TOT mode, there is an error of less than 5%
in energy readout which is acceptable, especially bearing in mind that the cluster count is used in
our experiment rather than absolute energy values. The article concludes with an explanation of the
importance of threshold equalisation in reducing the errors in the chip further and some examples
of captured frames. This article has been very useful in helping me to understand the way that the
chip works, allowing me to be confident in the use of the chip in capturing data in order to obtain
accurate results.
Source 7: CERN@school Solar Eclipse: Protocol For Background Radiation Measurements
Version II
This is an independently published article published by a school student so its reliability is
questionable. However, this is the protocol designed for the eclipse by the leader of RAY at the time
in conjunction with Dr. T Whyntie, a lecturer at Queen Mary, University of London who is
experienced with the Medipix 2 chips and particle analysis. This was therefore chosen to be the
method to be followed on the day of the eclipse in order to obtain the necessary data. A protocol
was necessary to ensure that data was captured in the same way at different centres, allowing the
data to be compared fairly. The protocol itself mostly states the appropriate values for the settings
that need to be changed from their default values, including screenshots to allow users unfamiliar
with the software to follow the instructions. Any measures needed to ensure standardised data
capture are also made clear, such as start times and a naming format to make the data easily
identifiable.
After this research, I still believed, and had some confirmation from academic sources, that the
radiation levels would dip. I was also able to now predict a quantitative decrease: about 20%.
However, this research contradicted with my assumption that the maximum decrease would be at
the maximum totality and instead suggested that it would be at around the time of last contact. This
was fairly counter-intuitive but there were multiple studies supporting this so this seemed like the
correct result. I therefore decided to amend my previous hypothesis to having a maximum drop at
around last contact to match the research that I had completed.
4 Presentation of Results
All graphs are included in the appendix.
The initial results (Figure 1) were not very promising. A near random set of points showed very little
pattern. To try and understand this better, I tried to narrow the data set by only using the results
from our school (Figure 2). This was less confusing as there were fewer points but there was still not
a clear pattern.
I decided that a major source of the complexity was a very broad ‘cloud’ of points. I therefore edited
my code to average the particle count on each frame for each minute, rather than each second to
try and decrease the variance (Figure 3). This created a much clearer curve with an unquestionable
dip in count rate.
I plotted several regression lines for the beta and gamma counts and calculated R2 values for each
line to suggest the suitability of the curve and the likelihood of a correlation. I chose the line which
gave the highest value which in both cases was of the sixth order. The alpha count rate seemed to
vary very little but for completeness, I also plotted a regression line for this data set as well. The
equations of these lines and their R2 values are shown below (Table 1).
Particle
Alpha
Beta
Gamma
Regression Line Equation
y = -2.10-13x6 + 3.10-11x5 + 8.10-9x4 - 6.10-7x3 - 7.10-5x2 +
0.0032x + 0.304
y = 5.10-13x6 - 1.10-10x5 - 6.10-9x4 + 3.10-6x3 - 7.10-5x2 0.0162x + 1.5876
y = -3.10-13x6 - 4.10-11x5 + 2.10-8x4 + 2.10-6x3 - 0.0003x2 0.0112x + 3.0603
R2 Value
0.7472
0.6263
0.6741
Table 1: The regression line equation and R2 value for each particle
I differentiated each of the curves to find their minimum points and their values. The results are
summarised in the table below (Table 2).
Particle
Local Minimum
Time (min)
Alpha
Beta
Gamma
83.5
63.4
74.3
Local Minimum
Count Rate
(particles / frame)
0.177
0.877
1.86
Local Maximum
Time (min)
19.7
-35.2
-16.6
Local Maximum
Count Rate
(particles / frame)
0.337
1.94
3.16
Table 2: Values of local minimum and maximum particle count; all values are to 3 s.f.
This shows a clear decrease in particle counts during the eclipse. The beta count dropped by 1.06
particles per frame or 54.8%. The gamma count dropped by 1.30 particles per frame or 41.1%. This
was a very large dip, suggesting that the Sun has a major role in background radiation levels. The
alpha count was very low throughout the whole eclipse and any variation seems more likely to be
due to random variation or different numbers of detectors contributing a constant rate to the
average.
The R2 value s for all three particles are in the range of about 0.65. This suggests a reasonable
correlation between the time and count rate but this could be stronger so the relationship should be
treated with slight scepticism.
There were some slightly unexpected results. Initially, the radiation count rate seems to increase
before the eclipse. Although a very small amount of increase may be expected due to the Sun rising,
this was far greater than expected. Upon checking the number of values averaged for each minute, I
noticed that these early, lower values (where t < -80 mins) had only four centres worth of data
compared to over twenty in later values. This suggests that these centres all had low count rates
throughout the eclipse but later on, the average was increased by centres with much higher count
rates. A similar situation occurs later at the end of the eclipse (where t > 130 mins) where much
fewer centres contributed data but this fits the other data better, although these later results should
be taken to be less certain as earlier results during the ‘main’ part of the eclipse.
The local minimum for particle count took place just over an hour after the maximum totality, at
approximately the time that the eclipse had finished (last contact was approximately seventy
minutes after). This is somewhat surprising but fits with the research I had conducted previously.
The research on the 1999 eclipse [3] reported a drop of about 20% with a maximum decrease at
about the time of last contact. Our data suggests a greater drop than this, approximately twice as
much (since this experiment measured gamma radiation) but the time of maximum drop in radiation
matches our results. This seems to suggest consistency between our experiment and the 1999
eclipse.
The study on the Bengal eclipse in 2009[4] found a drop of 18% in total radiation, compared to our
46.3%, which is a lot lower. However, it found the maximum drop to be about two hours after
maximum totality (just after the time of last contact) which, as with the previous experiment, again
matches our results. The study also commented on the rapid increase of the count rate after two
hours, back to previous levels, which is observed in our results.
As our results match the results of these previous two studies, the results seem repeatable and
reasonably correct. In general, the time of maximum totality is fairly consistent between previous
experiments and ours although the magnitude of decrease seems to be much larger, approximately
twice as much.
5 Interpretation of Results
The results from our experiment, and other previous experiments, suggest that the maximum
decrease in radiation levels occurs at about the time of last contact. This is a somewhat surprising
conclusion to make as common sense would suggest that the maximum dip should be during
maximum totality.
In my research, I have been unable to find an existing explanation as to why this is the case so, after
discussing the matter with teachers and other members of the project, I have created some
conjectures to explain this.
One possibility is that the time delay is due to the finite speed of the particles of radiation. A time lag
should exist while the particles travel from the Moon to the Earth. However, as the speed of the
solar wind is approximately 400 kms-1 [8] and the Earth is, on average, only about 385,000 km from
the Moon, this would only account for about a 960 second delay or about 16 minutes. Therefore,
this is not sufficient to explain the delay of over an hour.
An alternative is that reactions in the atmosphere that occur due to radioactive interactions (such as
radical reactions) would not occur during the eclipse, creating a well which would need to be refilled
before the count rate returned to normal. This seems a more likely explanation than the previous
hypothesis as this would explain why the count rate only starts to returns to normal after the eclipse
is over. However, this would suggest that the rate should still drop for the entirety of the eclipse
which is not observed: the rate only starts to drop just after maximum totality.
Neither explanation seems completely right and seems to only be a part of the real cause. It is also
possible that there is simply a correlation between time and count rate but since there have been
several different experiments in different locations during different eclipses with different weather
conditions that all found the same results, this seems unlikely.
6 Evaluation
In general, I think that this was a successful experiment as the results matched those expected based
on previous studies and showed a very clear relationship between time and count rate. The results
also matched my refined hypothesis made after my research.
In terms of accuracy and repeatability, although the time of maximum decrease matched previous
experiments which is promising, the magnitude of the decrease was about twice what was expected.
This suggests that there was some error with our experimental procedure as such a large difference
cannot be simply put down to random error as so much data was collected and it seems unlikely that
this eclipse would be so different to previous ones. The relatively low R2 values should also be
considered as although they suggest that a relationship does exist, this relationship is fairly
uncertain. This reflects the disparity between the maximum decrease and expected maximum
decrease and suggests that the experiment could be improved.
If I had the opportunity to conduct a similar experiment in the future, I would make several changes
based on what I have learnt from this one. For example, I would continue collecting data for longer
after the maximum totality to get a better picture of how the count rate returns to normal. This was
lacking from the experiment as most schools stopped recording about the time of the maximum
decrease. More data from before the eclipse would also be desirable but since little change is
expected, this is less vital.
I would also collect more environmental data, such as temperature, wind speed and air pressure.
This would allow us to eliminate environmental factors contributing to the change in radiation levels.
They may also help to explain the results observed.
In conclusion, I think that the experiment was very successful, although not perfect, and has helped
contribute to our understanding of the Sun’s effect on background radiation levels. The experiment
has been unable to suggest a reason for its observations so more testing will be required in the
future. Using what I have learnt from doing this project, I am confident that future experimentation
on the effect of a solar eclipse on cosmic radiation levels will yield even better and more revealing
results.
Appendix
18
16
14
Number of Particles Per Frame
12
10
8
6
4
2
0
-10000
-8000
-6000
-4000
-2000
0
2000
Relative Time (s)
Alpha
Figure 1: Average particle counts per relative second
Beta
Gamma
4000
6000
8000
10000
12000
12
10
Number of Particles Per Frame
8
6
4
2
0
-5000
-4000
-3000
-2000
-1000
Relative Time (s)
Alpha
Figure 2: Average particle counts per relative second for our school only
Beta
Gamma
0
1000
2000
4.5
4
3.5
Number of Particles Per Frame
3
2.5
2
1.5
1
0.5
0
-150
-100
-50
0
50
Relative Time (min)
Alpha
Figure 3: Average particle counts per relative minute
Beta
Gamma
100
150
200
sqlCsvConvert.py (run on Linux server hosting database)
import sys, datetime, MySQLdb
def convert(uploadId, eclipseTime):
db = MySQLdb.connect(host="localhost",
user=[USERNAME],
passwd=[PASSWORD],
db="analysis")
# username and password removed for security
query = "SELECT id, name, capture_time, latitude, longitude,
alpha, beta, gamma FROM “webanalysis_frame” WHERE upload_id_id = " +
str(uploadId) + " ORDER BY capture_time ASC"
cur = db.cursor()
cur.execute(query)
if len(str(uploadId)) == 1:
uploadIdName = "0" + str(uploadId)
else:
uploadIdName = str(uploadId)
fileName = "files/" + str(uploadIdName) + ".csv"
with open(fileName, "w") as f:
f.write("ID,Name,UNIX Capture Time,Readable Capture
Time,Relative Capture Time,Latitude,Longitude,Alpha,Beta,Gamma")
for row in cur.fetchall():
f.write("\n" + str(row[0]) + "," + row[1] + "," +
str(row[2]) + "," + str(datetime.datetime.utcfromtimestamp(row[2])) + ","
+ str(row[2] - eclipseTime) + "," + str(row[3]) + "," + str(row[4]) + ","
+ str(row[5]) + "," + str(row[6]) + "," + str(row[7]))
print("File processed!")
if __name__=="__main__":
convert(int(sys.argv[1]), int(sys.argv[2]))
summaryMaker.py (run on home computer running Windows)
totalAlpha = {}
totalBeta = {}
totalGamma = {}
avgAlpha = {}
avgBeta = {}
avgGamma = {}
def summary():
for i in range(8,55):
try:
if i < 10:
fileName = "0" + str(i) + ".csv"
else:
fileName = str(i) + ".csv"
with open(fileName, "r") as f:
for line in f:
line = line.strip("\n")
values = line.split(",")
try:
relTime = int((float(values[4]) / 60) + 0.5)
if abs(relTime <= 180):
if relTime in totalAlpha:
totalAlpha[relTime] += int(values[7])
totalBeta[relTime] += int(values[8])
totalGamma[relTime] += int(values[9])
else:
totalAlpha[relTime] = int(values[7])
totalBeta[relTime] = int(values[8])
totalGamma[relTime] = int(values[9])
except:
continue # Continue if line is non-numeric (i.e.
header)
except:
continue # Continue if file does not exist
with open("Total Results.csv", "w") as f:
f.write("Relative Time,Alpha,Beta,Gamma,Frame Count")
i = 0
for time in totalFrame:
avgAlpha[time] = totalAlpha[time] / totalFrame[time]
avgBeta[time] = totalBeta[time] / totalFrame[time]
avgGamma[time] = totalGamma[time] / totalFrame[time]
line = "\n" + str(time) + "," + str(avgAlpha[time]) + "," +
str(avgBeta[time]) + "," + str(avgGamma[time])
f.write(line)
i+=1
print(str(i) + " times stored")
if __name__ == "__main__":
summary()
Bibliography
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sunspot cycle variation in cosmic ray intensity. Nature. 262. pp. 766-768.
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Geophysical Research. 106(A10). pp. 21599-21609.
[3] Kandemir, G. et al. 2000. Variation of Cosmic Ray Intensity During the Solar Eclipse August 11,
1999. Last Total Solar Eclipse of the Millennium. 205. pp. 202-207.
[4] Bhattacharya. R. et al. 2010. Cosmic ray intensity and surface parameters during solar eclipse on
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http://iopscience.iop.org/1748-0221/6/01/C01046/pdf/1748-0221_6_01_C01046.pdf
[6] Llopart, X. et al. 2007. Timepix, a 65k programmable readout chip for arrival time energy and/or
photon counting measurements. Nuclear Instruments and Methods in Physics Research Section A:
Accelerators, Spectrometers, Detectors and Associated Equipment. 581(1-2). pp. 485-494.
[7] Beesty, R.B. et al. 2015. CERN@school Solar Eclipse: Protocol For Background Radiation
Measurements Version II. [Online]. Accessed 30 Jun 2015. Available from:
http://rayproject.wdfiles.com/local--files/eclipse-datacollection/CERN%40school%20Solar%20Eclipse%20Version%20II%20%5BMX10%5D.pdf?ukey=5aacd084caa9fe25a959be74faac1655c49891f7
[8] NASA. The Solar Wind. [Online]. Accessed 18 Nov 2015. Available from:
http://solarscience.msfc.nasa.gov/SolarWind.shtml