Quiet Time Precipitation Patterns of Energetic Particles

Transcription

1 Quiet Time Precipitation Patterns of Energetic Particles Bachelor Thesis Torsten Stamer University of Osnabrueck Examinator: Prof. Dr. May-Britt Kallenrode Co-Examinator: Prof. Dr. Klaus Betzler September 20,

2 I would like to thank Professor May-Britt Kallenrode for providing me with the opportunity to write this thesis and the study project before it, as well as for her input of ideas during our discussions and for explaining all the strange effects cropping up now and then. This work would also have been impossible without the help of Jan Maik Wissing, whom I want to thank for the help in interpreting my data, answering my questions, and showing me where to find the data I needed in the vastness of the Internet. 1

3 Abstract The deep solar minimum in the years enables us to study an unusually calm magnetosphere with few disturbances caused by solar events. This thesis presents the changes in some of the most important parameters that depend on solar activity - K p index, global average particle flux and the movement of particle precipitation areas. The relationships between these parameters are investigated and visualized using satellite data. Zusammenfassung Das tiefe solare Minimum in den Jahren ermöglicht uns, eine ungewöhnlich ruhige Magnetosphäre mit wenigen durch solare Ereignisse ausgelösten Störungen zu untersuchen. Diese Arbeit zeigt die Veränderungen einiger der wichtigsten Parameter, die von solarer Aktivität abhängen - K p Index, globaler durchschnittlicher Teilchenfluss und die Bewegung von Teilcheneinfallsgebieten. Unter der Benutzung von Satellitendaten werden die Zusammenhänge zwischen diesen Parametern untersucht und visualisiert. 2

4 Contents 1 Introduction On Solar Activity On the Magnetosphere General Outline Data used 7 3 Solar Wind Speed and Particle Fluxes 9 4 Precipitation Patterns Global Average Flux Precipitation Areas Relationship with K p index Global Average Flux Precipitation Areas Conclusion 19 3

5 1 Introduction 1.1 On Solar Activity Except from polar lights, effects of solar activity on Earth are generally not observable with the naked eye. It is therefore not surprising that this field of study is comparatively young. First telescopic observations of sunspots were taken in the 17th century, and long-term observations prompted the discovery of the 11-year cycle of solar activity in 1843: The number of sunspots, which was the only known indicator of activity at the time, fluctuated with a period of approximately 11 years. Changes on Earth resulting from this activity are electromagnetic in nature, so discovering and measuring them required the development of the corresponding physical theories by scientists such as Faraday and Maxwell. The spread of electricity-based technology also resulted in large solar events becoming a potential hazard. This is evidenced by an especially strong solar storm on September 1-2, 1859, which resulted in telegraph systems in North America and Europe failing and being set on fire due to large induced currents. Polar lights were seen over most of the globe, even in places like Hawaii and Cuba [1]. The solar flare which caused this was even observable as a brightening of the sun in visible light. Astronomer Richard Carrington described it as two patches of intensely bright and white light [2]. A solar event of similar magnitude occurring today would likely cause considerable damage to electricity and communication networks. More exact measurements of the magnetosphere s topology became possible with the advent of satellites in the second half of the 20th century. An outside look on the whole of the magnetosphere is not possible, and a satellite can only measure plasma data at its own position. However, a large quantity of such measurements allows us to construct models of the Earth s magnetic field, and the particle populations in it, with some confidence. 1.2 On the Magnetosphere The Earth s magnetic field, which is thought to be generated by a dynamo process in the interior, can be approximated by a magnetic dipole. However, the magnetic field s axis is inclined by about 11 with respect to the axis of rotation (see Figure 1). Geographic north actually corresponds to a magnetic south pole and vice versa. As the magnetic field is the decisive factor in this work, any dependency on latitude will be given as geomagnetic instead of geographic latitude. The Earth s field is constantly assailed and distorted by the solar wind, so the actual topology of the magnetosphere looks more like the one shown in Figure 2, with the field compressed on the dayside and elongated on the nightside. The magnetic field has a shielding effect which is very important for life on the planet [4]: Since the solar wind consists of charged particles (it is a plasma), 4

6 Figure 1: Magnetic and rotational axis of the Earth [3] these are affected by the Lorentz force F = q ( v B) and gyrate around magnetic field lines, with their center of movement following the direction of the field. Therefore, the bulk of the charged energetic particles is deflected by the magnetic field, which effectively shields equatorial latitudes in particular. Other particles follow the field lines and enter the atmosphere, mostly near the poles where the field is nearly perpendicular to the surface. It is also possible for particles to become trapped in the magnetic field. Due to the magnetic mirror effect, they can be reflected when entering regions of increasing magnetic field strength, effectively bouncing back and forth along a field line. This is the reason for the existence of radiation belts such as the Van-Allen-Belt. Particles in these belts also drift around the Earth, with the direction depending on charge. This is a ring current whose magnetic field weakens that of the Earth, an effect which is especially strong during magnetic storms, when the amount of particles in the radiation belts increases significantly. If these particles are accelerated towards the atmosphere, polar lights are created [5]. 1.3 General Outline This Bachelor thesis aims to give an overview of various relevant parameters (such as particle fluxes and precipitation areas, geomagnetic indices, solar wind data) and to explore their relationships. It expands on a study project named The Polar Aurora - Variations in Time which I completed in April In this project, I concentrated on the intensity and position of the auroral oval, using electron flux data from the POES satellites NOAA 15 and NOAA 16 to visualize the oval s position (see Figure 3). 5

7 Figure 2: Earth s magnetosphere. The sun is to the left in this figure, compressing the magnetic field on the dayside and elongating it on the nightside. The field s shielding effect can be seen in the way particles coming from the sun flow around it. The polar cusp is the border between closed field lines, on which trapped particles reside, and open field lines which lead around the Earth. [4] The impetus for this work was the recent extreme solar minimum [6, 7], which provides a very undisturbed magnetosphere to study. As its title states, this Bachelor thesis gives some special consideration to the quiet time as well, but its focus lies on the relationships between different parameters, not just on the oval s position. The work is structured as follows: Section 2 describes the data and methods used. In section 3, the solar wind s changes in speed between 2002 and 2010 are shown and compared to the geomagnetic K p index as well as to the overall fluxes measured outside the magnetosphere. Section 4 describes the changes in overall global flux on Earth. Also, the movement of the precipitation areas is visualized and discussed. Finally, in section 5, the relationship between K p index and the aforementioned properties of global flux and precipitation areas is investigated. 6

8 Figure 3: Visualization of the auroral oval, using electron data only. The decrease in intensity towards the minimum is reflected in the colors growing darker. At the same time, the colored areas can be seen to grow thinner and move towards the poles on both hemispheres. The brighter area around 20 S is due to the South Atlantic Anomaly, an area where the Van Allen radiation belt is very close to the surface because the (fictuous) magnetic dipole does not go exactly through the center of the Earth. 2 Data used For this work, we used data from two satellites, NOAA 16 [8, 9] and ACE [10]. The former was launched in 2000 into a sun-synchronous, near-polar orbit at an inclination of 98, an altitude of 850 km and a period of 120 minutes. It is part of the POES (Polar Operational Environmental Satellite) program and the data is available on the Internet at [11]. The NOAA satellites 15 and 16 were also the main data source for the aforementioned project on the polar aurora. Of the various data measured by NOAA 16, I was interested in the following channels of the SEM-2 instrument [12]: 7

9 Table 1: NOAA 16 TED and MEPED data channels Instrument Channel Number Particle Type Energy Range TED 04 electrons,protons kev TED 08 electrons,protons kev TED 11 electrons,protons kev TED 14 electrons,protons kev MEPED 0e1e2 electrons MeV MEPED 0e2e3 electrons MeV MEPED 0e3 electrons MeV MEPED 0P1 protons MeV MEPED 0P2 protons MeV MEPED 0P3 protons MeV MEPED 0P4 protons MeV MEPED 0P5 protons MeV These energy ranges, taken from [13], are slightly different from the original due to the unpacking routine, which substracted electron channels from each other. This was done because these electron MEPEDs all had the same upper boundary of 2.5 MeV. Energy ranges for protons and electrons are identical for TED. The particle flux is given in particles / m 2 * sr * s * MeV, i.e. differential flux. In cases where I calculated overall or average fluxes of different channels (as with all TED Electron channels in Figure 3), I normalized them beforehand by multiplying with the energy range in MeV. In addition to these measuring channels, data fields indicating the time and position of the satellite were used, most importantly geomagnetic latitude. For this, the foot-of-field-line - data was used. This is the footpoint of a field line connecting the recent satellite position and the ground, as calculated using the International Geomagnetic Reference Field (IGRF) [14]. Particles following that field line should therefore precipitate at that geomagnetic latitude. The IGRF is a static model, so obviously this calculation cannot be exact, especially if the magnetosphere is strongly disturbed. Nevertheless, it is still preferable to the satellite s own latitude, because the interesting information is where the particle actually enters the atmosphere. The second satellite is NASA s ACE (Advanced Composition Explorer). Launched in 1997, it moves on an elliptical orbit around the L1 Lagrange Point. Data on solar wind speed from the ACE Real Time Solar Wind (RTSW) instrument [15] was used, downloaded from [16]. Particle flux data from the Electron, Proton, and Alpha-particle Monitor (EPAM) can be found at [17]. The particle flux channels are from the LEFS60 and LEMS120 detectors, and their energy ranges are as follows: (more information on the various detectors can be found at [18]). 8

10 Table 2: ACE EPAM data channels Detector Channel Particle Type Energy Range LEFS60 E1 electrons kev LEFS60 E2 electrons kev LEFS60 E3 electrons kev LEFS60 E4 electrons kev LEMS120 P1 ions kev LEMS120 P2 ions kev LEMS120 P3 ions kev LEMS120 P4 ions kev LEMS120 P5 ions kev LEFS60 FP5 ions kev LEFS60 FP6 ions 761 kev 1.22 MeV LEFS60 FP7 ions MeV The numbers 60 and 120 indicate the detector s orientation relative to the satellite s spin axis in degrees. The temporal resolution is 5 minutes. For the processing of all data, the program MATLAB was used. Details about certain calculations will be given where necessary. 3 Solar Wind Speed and Particle Fluxes Since the solar wind is the ultimate source of geomagnetic disturbance, its change from the time of the last maximum (2002) to the height of the last minimum (2009) will be our initial point. The relationship between the solar wind s speed and the degree of geomagnetic disturbance (as expressed by the 3-hourly K p index) is the first to be investigated (see Figure 4). Running averages have been calculated and are shown in the figures. The averages are over 500 data points, which corresponds to about 2 months. This interval was chosen because it is sufficiently long to suppress effects of the 27- day rotation period of the sun, while not cutting off too much data at the edges. The same argument holds for the running averages in all following figures. The similarity of both curves in Figure 4 is evident at first sight. The K p index is less smooth because it has only 28 possible values, but the overall shapes are almost identical, suggesting a linear relationship between the two properties (note that K p is a logarithmic index [19]). Individual events can also be identified in both plots, such as the two large spikes in 2005, and the largest one on October 29th, 2003, which is the only occasion in this time interval where the K p index reached 9, its maximum value. Because changes in KP-Index and solar wind speed ultimately have a common cause in solar events, the correlation seen here is not surprising. For effects on Earth, such as aurora, particles have to be able to penetrate into the atmosphere. Generally, much higher energies than the bulk of the solar wind s several hundred ev are required for this. Therefore, the distribution of particles in the high energetic tail is interesting. Data of ACE s EPAM instrument (Electron, Proton, 9

11 Figure 4: Developments of solar wind speed and K p index. Temporal resolution is 3 hours each. Running average of 500 data points. 10

12 and Alpha-particle Monitor), which measures particles with energies of hundreds of kev (Table 2), is shown in Figure 5. The fluxes decrease for higher energies. An increase would be expected for energies around that of galactic cosmic rays, but these are not reached here. All curves share a significant, sudden decrease in large disturbances from 2006 onward (with some exceptions in 2007), coincident with the beginning of the minimum. There appears to be a rather sharp border between minimum and maximum here, much sharper than in the above plots of solar wind speed and K p index. During disturbances (i.e. solar events), the particle fluxes for all channels jump by several orders of magnitude, as expected following a CMEdriven particle event. The increase relative to background levels appears to be largest for higher energies. There are two peculiarities in these plots: First, both lowest-energy channels (proton and electron) show a strong sinus form with a period of exactly one year, and secondly, all channels show a general increase in fluxes over time, despite the solar minimum. Through private communication to Mr. Dennis Haggerty of the ACE science center, I was informed that these effects are due to a temperature dependency of the instrument. The sinus form is caused by changes in temperature due to the changing distance from the sun over the year, and the fact that there is a general temperature increase over the whole mission is the cause of the values rising overall (these issues are documented in [20]). Unfortunately, this makes it impossible to show and quantify the expected decrease in overall fluxes, and to investigate whether there is any unusual behaviour in this minimum. The only thing that can be shown with certainty is the sudden decrease in disturbances during minimum, which by this definition begins in Precipitation Patterns 4.1 Global Average Flux Another parameter to examine is the global average flux of energetic particles. I calculated the total average of all MEPED channels of NOAA 16 (as listed in Table 1), protons and electrons together. A simple average of all values measured over some time interval would not be exact for these reasons: 1. Differential channels of different energy widths are being added 2. The satellite NOAA 16 s near-polar orbit means that high latitudes have far more coverage than low latitudes, i.e. the number of measurements depends on latitude. 3. The average of all measurements at a given (geographic) latitude has to be weighted differently depending on that latitude, because higher latitudes represent a smaller part of the global area. 11

13 Figure 5: ACE s EPAM electron and proton differential fluxes. Temporal resolution is 3 hours. For the sake of viewability, some channels have been multiplied with a constant to reduce overlapping, and some proton channels have been omitted. 12

14 Because point 3 is a purely geometrical consideration having nothing to do with the magnetic field, geographic instead of geomagnetic latitude is used throughout this algorithm. Each channel is multiplied by its energy range in MeV for normalization. To account for Point 2, the number of measurements at a given latitude must be counted. If i is an integer between -90 and 90, the algorithm calculates the average value of all measurements within a geographic latitude of i ± 0.5 over each 3-hour inteval. The result is the average flux for that latitude. The global average is then calculated from these 181 latitude-averages minus those for which there are zero measurements (because the satellite never reaches them, or all values in that time interval have error codes). Each latitude-average is weighted by the cosine of its degree of geographic latitude because of point 3. The result, shown in Figure 6, shows the expected development of fluxes decreasing towards the minimum. The running average was calculated from the logarithm of the actual flux data, so as to better fit with the original curve. It is similar in form to the plots of solar wind speed and K p index (Figure 4): maxima in 2003 and 2005, and a general decrease which becomes steeper after However, the y-axis here is logarithmic, so a logarithmic dependency of K p index on global average flux seems to be a reasonable - if tentative - hypothesis. This will be investigated further in section 5.1. Figure 6: Global average flux of all NOAA 16-MEPED channels, both electron and proton. Temporal resolution is 3 hours. Running (logarithmic) average of 500 data points. 4.2 Precipitation Areas Not just the amount of precipitating particles depends on solar activity, but also the areas where they enter the atmosphere. If the solar wind pressure is 13

15 lower, the magnetic field can expand. This means that the polar cusp, and the particles precipitating there, move to higher latitudes [21]. The movement in main precipitation areas was the focus of my study project, and it can be seen clearly in Figure 3. I calculated a center of precipitation, which is a weighted average latitude for precipitating particles (cutoff at 50 ). Each latitude is weighted by its particle flux. This algorithm is analogous to calculating the center of mass of a body, with the fluxes corresponding to the masses and the latitudes corresponding to the locations of the individual mass points. In the project, I concentrated on the TED electron channels exclusively. Figure 7 expands on this topic and shows the center of precipitation for the lowest energy TED- and MEPED channels, for both protons and electrons. Running averages, which better visualize the overall development, are shown seperately in Figure 8. The general tendency of the expected poleward movement towards the minimum is evident. High-energetic particles are closer to the equator than lowenergetic particles (compare mepe1e2 and TEDElectron04). Also, comparison of the TED04 channels implies that protons precipitate closer to the equator than electrons with the same energy. During the maximum, the difference amounts to about 5, though both curves meet again in the minimum. The fact that mepp1 is consistenly closer to the poles than mepe1e2 does not contradict this, because the latter has much larger energies (see Table 2). This can be explained as follows: Since the particles are affected by a magnetic field, their behaviour is determined by their magnetic rigidity R = p q, which is a measure of a particle s resistance against deflection by a magnetic field. This also means that a stronger field is required to control it. Since magnetic rigidity depends on momentum, we get different values for a proton and an electron with the same energy: R = p q = m v q = m 2 E m q Since only the absolute value of the electric charge q is relevant here, the only remaining difference is the mass. With m p 1800 m e, we find that mp R p = m p/ R e m e / m e If a proton has more than 40 times the magnetic rigidity of an equal-energy electron, it is not suprising that it can be found closer to the equator, where the field is stronger. The gyroradius is proportional to momentum as well. This means that the satellite will measure a higher-rigidity particle farther away from the field line around which it actually gyrates. What is surprising, however, is that the TED04 proton curve is so much more chaotic than that of the TED04 electrons. If anything, the protons would be expected to be less susceptible to variations because of their higher magnetic rigidity. 14

16 Figure 7: Center of precipitation for various channels of NOAA 16. Temporal resolution is 1 day. 15

17 Figure 8: Center of precipitation, 60-day running averages. In the minimum, the TED curves of protons and electrons converge. It is not clear why this is the case; possibly the undisturbed state of the magnetosphere allows slower processes such as drift to happen without frequent interruptions. Looking at the TED04 channels of Figure 7, a wavelike movement with a period of what seems to be one year can be seen. I had already noticed this during the study project, but was unable to explain it. It is very similar to the wavepattern in the low-energy channels of Figure 5, which was explained by the periodically changing temperature due to the distance from the sun. However, this explanation does not work here, because it s the precipitation area that is affected, not the intensity. The characteristics of this phenomenon summarized: 1. The period appears to be one year, suggesting a seasonal effect of some sort. 16

18 2. The amplitude is about 5 in maximum and 2 in minimum. 3. There is no charge dependency, since proton and electron movements are in phase. 4. The effect diminishes with higher energies. 5. The centers of precipitation shift towards the south in (northern) winter and towards the north in (northern) summer. Formulated differently: Particles move towards their respective pole in a hemisphere s summer and away from it in winter. Assuming the magnetic field is the source of this, it is possible that the effect is caused by some periodic change in the Earth s orbit around the sun, such as the position relative to the plane of the ecliptic and to the interplanetary magnetic field. Figure 9 shows the magnitude of the IMF s vertical component, B z. Figure 9: Development of Bz, with running average of 500 data points. Temporal resolution is 3 hours. However, no periodic movement of this sort can be seen here. Because of the 1-year period, there is little doubt that there is a connection to some seasonal parameter. The second formulation of Point 5 implies that the direction of movement depends on the season in the respective hemisphere, which is basically defined by the amount of electromagnetic radiation that hemisphere receives from the sun. Indeed, the ultimate cause may be electromagnetic radiation, which affects the system through ionization processes. In addition to the TED channels, mepe1e2 also shows some curious behavior, since its own wave-movement is very strong in the southern hemisphere but small in the northern one. Its direction is also opposite that of the TEDs. Because 17

19 of the north-south-asymmetry, the most likely cause is the offset between the Earth s rotational axis and the fictious dipole axis, which also causes the South Atlantic Anomaly. Unfortunately, a thorough investigation of these effects is beyond the scope of this thesis. 5 Relationship with K p index 5.1 Global Average Flux The hypothesis of an exponential dependency of global flux on K p index can be tested by directly relating the two properties. Figure 10 shows all 3-hour global average fluxes (as calculated in section 4.1) against the KP at the time. An average has also been calculated using the logarithm of the flux data, so it should be a line if the dependency is indeed exponential. This is approximately the case. However, even though the density of the points cannot be seen very well due to the low number of possible KPs, the variation around the average commonly spans 3 orders of magnitude. Because of this, one cannot actually speak of an exact exponential relationshop or dependency, since predictions based on this would be far off. When given a K p value, only the probablity of global flux being in some interval could be calculated. Figure 10: Correlation between global average flux of all MEPED channels and K p index. 5.2 Precipitation Areas It is also possible to plot the shift of precipitation areas against the K p index by going through all possible K p values and calculating a vector of 181 latitude- 18

20 averages for each of them. Using TED data, I created three variants of the plot (see Figure 11). One includes all data, the other two are subsets, namely maximum only ( ) and minimum only ( ). These subsets are capped at a maximum K p of 6.3, because higher values did not occur in 2006 and after. The intent of this was to investigate whether the particle flux and precipitation areas depend on K p index only, or whether there is some other parameter which differs between minimum and maximum and has an effect here. The general tendency of fluxes rising and precipitation moving away from the poles at higher levels of disturbance is evident in the plots. The roughness and block-shapes in the figure are due to the K p index having only 28 possible values. Comparison of the two subsets reveals that indeed, particle fluxes are higher during maximum for identical K p values, as the colored areas are both brighter and larger. It has already been shown in section 5.1 that K p alone is not sufficient to calculate global flux values with confidence because of the large variations. From Figure 11, it would seem that this is not entirely statistical variation, but that there is a systematic difference between maximum and minimum (or at least this current minimum). This difference results in lower particle fluxes even when the K p value is the same. The shape of the magnetosphere and the K p value depend mostly on solar wind pressure. A change in the relationships of solar wind properties (temperature, density) during minimum might result in fewer particles creating the same pressure, which would then lead to the observed difference. 6 Conclusion In this Bachelor thesis, the development of various parameters from solar maximum to an (especially intense) minimum were presented, using data from the satellites ACE and NOAA 16. Solar wind speed was found to be directly correlated to the degree of geomagnetic disturbance, as expressed by the K p index. Outside of the magnetosphere, the expected decrease of overall flux of energetic particles towards the minimum could not be shown due to an instrumental effect on the ACE satellite. Nevertheless, the minimum can be seen in these data as a sudden lack of large solar events beginning in This lack of events appears as the most significant characteristic of the minimum, and it shows a rather sharp boundary at the beginning of More gradual changes include the decreasing global flux values, which are substantiated for the interior of the magnetosphere by NOAA 16, and the movement of particle precipitation centers towards the poles. Visualizing the dependency of global flux on K p index showed that, while the average value shows an exponential correlation, the variations from this average are too large to allow formulating an actual dependency. Furthermore, the correlation between precipitation areas and K p showed that there is a difference between minimum and maximum that can not be entirely attributed to 19

21 Figure 11: Relationship between particle precipitation areas and K p index. The top picture was created using all data from , the middle one only , and the lower one

22 K p, since even for the same K p value, precipitation tends to be stronger during maximum than during minimum. Therefore, K p alone does not seem to be sufficient to quantify the degree of geomagnetic disturbance, since some other factor - probably a change in solar wind properties - seems to be at work here. A few unresolved questions remain concerning the movement of precipitation areas, most noticeably a wavelike movement with a period of what seems to be exactly 1 year. The interplanetary magnetic field shows no periodicity that could explain this. A seasonal effect related to the intensity of electromagnetic radiation seems to be the most likely explanation at this point. References [1] URL carringtonflare/. [2] Carrington,R.C. Description of a singular appearance seen in the sun on september 1, Monthly Notices of the Royal Astronomical Society, 20. [3] URL [4] URL [5] H.C. Carlson, Jr. and A. Egeland. The Aurora and the Auroral Ionosphere. In Introduction to Space Physics [6] Phillips,T.,. URL science-at-nasa/2009/01apr_deepsolarminimum. [7] Phillips,T.,. URL science-at-nasa/2009/03sep_sunspots/. [8] URL [9] URL spacecraft=16. [10] URL [11] URL [12] URL [13] Wissing, J.M., Kallenrode, M.-B. Atmospheric Ionization Module Osnabrück (AIMOS): A 3-D model to determine atmospheric ionization by energetic charged particles from different populations. Journal of Geophysical Research, 114, [14] URL [15] URL [16] URL 21

23 [17] URL [18] URL [19] Bartels, J., Heck, N.H. Johnston, HF. The three-hour range index measuring geomagnetic activity. Terr. Magn. Atmos. Electr., 44, [20] Haggerty, D. K., E. C. Roelof, G. C. Ho, and R. E. Gold. Qualitative Comparison of ACE/EPAM Data from Different Detector Heads: Implications for NOAA RTSW Users. Advances in Space Research, 38, [21] R.J. Walker and C.T.Russell. Solar-Wind Interactions with Magnetized Planets. In Introduction to Space Physics

24 Statutory Declaration I hereby declare that I have completed this Bachelor Thesis myself independently without outside help and using only the sources declared under References. Osnabrück, September 20th, Torsten Stamer 23