New perspectives on contributing factors to the monthly behavior of the aa geomagnetic index
© The Author(s) 2016
Received: 20 April 2016
Accepted: 17 November 2016
Published: 1 December 2016
We studied the Aa geomagnetic index (aa index daily average) behavior on a monthly timescale using data from 1868 to 2015 for cycles 11–24. We identified solar- and lunar-associated periodicities in the Aa time series and found statistically significant Aa minima values a few days before the full Moon and high Aa values during the new Moon. When considering all the cycles, it was clear that the deepest Aa minima occurred during the Aa descending activity phase. However, when the cycles were separated according to the direction of the interplanetary magnetic field (IMF), the Aa minima came from the contribution of cycles with the IMF pointing toward the Sun (Type 1). Furthermore, during the descending phase of cycles with the IMF pointing away from the Sun (Type 2), the smallest Aa index values were found along with smaller changes compared to Type 1 cases. This behavior implies that during Type 1 cycles there are larger Aa perturbations than during Type 2 cycles. It is very likely that the mechanisms responsible for the Aa monthly behavior are a combination of solar and lunar effects that depend on several factors: (a) the Moon phases (new and full Moon), (b) the phase of the solar cycle (ascending or descending), and (c) the direction of the interplanetary magnetic field (away or toward the Sun).
It is well known that geomagnetic activity is modulated by solar activity and ionospheric variability produced by lunar and solar tides (Campbell 1997; Richardson et al. 2002; Yamazaki and Richmond 2013; Yamazaki 2014). On a monthly timescale, when a clear lunar role could be expected, the Moon’s influence on the geomagnetic activity has been inconclusive. In Michel et al. (1964), the authors studied the correlation between the Kp index of geomagnetic activity and 30-year period Moon data phases starting from 1931 and found no correlation. However, using the same data for solar activity cycles 17–19, Stolov and Cameron (1964) found that Kp decreases relative to the average value over several days before the full Moon and increases by the same value over several days after the full Moon. In addition, Gulyaev and Gulyaeva (1992) reported increases in the geomagnetic field disturbances during the full Moon at the solar activity minimum using the auroral electrojet index. Střeštík (1998), studying the Ap time series, found significant peaks at ~27 and 13.6 days that he associated with solar rotation and the structure of solar wind. The author claimed that he did not find a peak corresponding to the period of the synodic month (the interval between two successive lunar phases) at 29.5 days or its half. In a recent work, Akimov and Dyatel (2012) showed the dependence of the Ap index on the Moon’s phase for solar cycles 20–23 and found that in the declining phase of the solar cycle, the highest values of the Ap index relative to an average value are observed near the new Moon. In the ascending and maximum solar cycle phase, they observed minimum values of Ap over several days before the full Moon and maximum values of Ap for several days after the full Moon. They concluded that the mechanism of the Moon’s effect on the Earth’s magnetosphere is different near the new Moon and full Moon.
In the present study, we identified solar and lunar factors that may contribute to the monthly behavior of geomagnetic activity. To achieve this, we applied the wavelet, fast Fourier transform (FFT), and superposed epoch analysis to the Aa geomagnetic index using data from 1868 to the present and applied the superposed epoch analysis to the lunar phases. We further considered the ascending and descending Aa index phases, as well as epochs of different direction of the interplanetary magnetic field (IMF), to assess the 11-year solar activity cycle contribution.
Geomagnetic disturbances can be monitored by ground-based magnetic observatories recording the three magnetic field components. The aa index is a global geomagnetic activity index derived from the K indices from two approximately antipodal observatories: Hartland in the UK and Canberra in Australia. The aa index was introduced by Mayaud (1972). Since it is based on data from only two observatories, it is the simplest of the three hourly planetary indices. It strongly correlates with the ap and am indices, which are derived using data from more extensive observatory networks (http://www.geomag.bgs.ac.uk/data_service/data/magneticindices/aaindex.html). The global Kp is a 3-h index obtained as the mean value of the disturbance levels in the two horizontal field components, observed at 13 selected, sub-auroral observatories. The 3-h ap and the daily Ap indices are planetary magnetic activity indices, related to the Kp index, and are the average values of the irregular disturbance levels in the horizontal field components observed at selected magnetic observatories worldwide (http://www.gfz-potsdam.de/sektion/erdmagnetfeld/daten-dienste/kp-index/). The main advantage of using the aa index is that the time series spans from 1868, further back than any of the other planetary index time series. In this study, we used the aa index in order to have a long-term time series between 1868 and 2015. We averaged the aa index to obtain the Aa daily index.
Periodicities and harmonics of the Aa time series associated with the Moon and the Sun
Number of periodicities per cycle related to the Sun and the Moon
The Aa index time series consists of daily data from January 1, 1868, through January 31, 2015, which covers cycles 11 through 24 of the Aa index activity. We used the Aa cycles and not the sunspot cycles. While both phenomena have a similar time pattern, the time series do not exactly coincide (see Fig. 2). The aa index has several solar-associated sources, and some of them are not related to sunspots. High-speed streams account for approximately two-thirds of the long-term aa averages at solar minimum, while at solar maximum, structures associated with transients (interplanetary coronal mass ejections, shocks, etc.) make the largest contribution (~50%) from streams, and slow solar wind continues to be present. Similarly, high-speed streams are the principal contributor (~55%) to solar minimum IMF averages, while transient-related structures are the leading contributor (~40%) at solar maximum (Richardson et al. 2002).
Years of Aa cycles and their corresponding ascending and descending phases
Years of Aa Type 1 and 2 cycles and their corresponding ascending and descending phases
Values of Aa index corresponding to Fig. 4
Discussion and conclusions
The wavelet and FFT analysis suggested that lunar and solar periodicities are mingled. The summary in Table 2 showed several cycles presenting both Sun- and Moon-related periodicities. In Střeštík (1998), periodicities around 27 days and 29 and 30 days appeared as significant, although the author associated the latter to the modulation by the annual wave in solar tides. Table 2 also shows that during maxima, most periodicities are related to the Sun or mainly the Sun, which is expected since during these epochs the solar activity is higher and should dominate the lunar effects. During minima, the Sun–Moon-related periodicities are more numerous, indicating that the Moon effect is more evident than in times of higher solar activity. Because the lunar cycle and solar rotation have slightly different periods, the relative phase drifts should produce random peaks/dips as shown in Figs. 3 and 4.
Concerning the geomagnetic behavior on monthly timescales, in Akimov and Dyatel (2012) and using the Ap index for cycles 20–23, the authors found the highest values in the declining part of the solar cycle near the new Moon and aa minima near the full Moon. For the ascending and maximum part of the solar cycle, they found minimum values of Ap before the full Moon and maximum values after the full Moon. Figure 3d, f shows a behavior qualitatively similar to that described in Akimov and Dyatel (2012). However, we would like to point out that these authors used Ap data, while we used Aa index data, and, more importantly, they used sunspot cycles, while we use Aa index cycles. Therefore, differences in the behavior between the cycles are expected. Figure 3 shows that in all cases there is a strong fall in the Aa index value a few days before the full Moon. The full Moon occurs two days after the Aa minimum day, and the new Moon appears during high Aa value epochs.
In Table 5, we presented several parameters from Fig. 4 and considered statistically significant values those that are equal to or larger than 2σ. Considering the periods before and after the Aa minima, we noticed that the means of the two periods reached similar Aa index values (columns two and eight). Concerning the Aa minima, the data in the fourth and fifth columns indicate that all the cases present statistically significant minima in the Aa index value a few days before the full Moon (see also Fig. 4). The minima occur three days before the full Moon, with two exceptions: the Type 1 descending phase (see Fig. 4f), where the full Moon appears four days after the Aa minimum, and the Type 2 descending phase (see Fig. 4i), where it appears six days after the Aa minimum. When considering all the cases (ALL, first column), it is clear that the deepest Aa minimum occurred during the descending phase (ALL D, first column) according to the number of σs (fifth column). However, when the cycles are separated into Type 1 and 2, the Type 1 descending phase (T1 D) presented the deepest Aa minimum, being the main contributor to the ALL D Aa values, while the T2 D presented the smallest minimum (fifth column).
Concerning the new Moon, the data in the sixth and seventh columns show that the associated Aa index values are not statistically different from their means in the second column (they are less than 2σ), and, therefore, they presented higher values compared to the Aa minima. Nevertheless, the descending phase values are the closest to their averages for all the cases. In addition, during the T1 A and T2 D phases, the Aa means were the largest and the smallest, respectively.
Finally, the Aa full Moon values were averaged (see column eight). The T2 A phase presented the largest smallest Aa average values and T1D and T2D the smallest values, respectively (see columns eight and nine); however, they are not statistically significant (they are less than 2σ). Generally, during the descending phase, the Aa values are the smallest and closest to their means (see columns two to nine). In particular, T2 D cycles presented the smallest Aa index values of all the cases. Type 1 cases tend to present larger changes than Type 2 cases (see fifth and seventh columns). These two features may indicate that during Type 2 epochs the Aa perturbations are smaller than during Type 1 epochs. There were Aa minima values a few days before the full Moon and higher Aa values a few days after.
We looked at possible mechanisms explaining the Aa drop around full Moon. Recent observations have established that there is an interaction on magnetically connected field lines of the solar wind and magnetospheric plasma with the Moon and its exosphere, surface, and crustal magnetic fields (e.g., Mitchell et al. 2008; Poppe and Horányi 2010; Saito et al. 2012; Halekas et al. 2012). Our satellite travels through the tail of the Earth’s magnetosphere for 4 or 5 days (Hapgood 2007), and the Moon enters the magnetotail typically 2–2.5 days before the full Moon. Therefore, at 3–5 days before the full Moon, when the Aa index drops are observed, the Moon is located in the magnetosheath. However, even when the Moon is magnetically connected to the Earth in the magnetotail, the spatial scale of the Moon-related perturbed plasma is at most several lunar radii across the field lines. Therefore, the perturbations are local and seem incapable of affecting the global geomagnetic activity, as the magnetosphere is several tens of Earth radii at the lunar distance. In addition, the Aa drop occurred only when the Moon enters the magnetosphere and not at its exit. Furthermore, the lunar tidal effects also contribute to the Aa perturbation mainly during the new/full Moon (Yamazaki 2014). However, we cannot see how the tidal effect could explain the Aa drop only around the full Moon and not around the new Moon, when a similar behavior could be expected. Apparently, we cannot explain the Aa drops through lunar magnetic connection to the magnetosphere or through tidal effects on the ionosphere. Further detailed studies of both the solar and lunar effect on the geomagnetic activity at monthly timescales should be conducted, but this is out of the scope of this study.
During the descending phase, the high-speed streams make the largest contributions to Aa and IMF (Richardson et al. 2002). The presence of high-speed streams during Type 2 cycles should produce a stable interaction with the Moon, because it is during this phase that we observed the smallest Aa values and changes. Usually during Type 1 cycles, the Moon should have a larger interaction with high-speed streams and the magnetosphere compared to that during Type 2 cycles.
There are solar- and lunar-associated periodicities in the Aa index.
There are statistically significant Aa minima values a few days before the full Moon.
There are high Aa values during the new Moon.
When considering all the cycles, it is clear that the deepest Aa minima occurred during the descending phase, but when the cycles are separated into Type 1 and 2 (according to the direction of the interplanetary magnetic field), we noticed that the Aa minima in all the cycles came from the contribution of the Type 1 descending phase.
The Type 2 descending phase cycles presented the smallest Aa index values and smaller changes compared to Type 1 cases. This behavior implies that during Type 1 cycles there are larger Aa perturbations than during Type 2 cycles.
It is very likely that the mechanisms through which the Sun and Moon affect the geomagnetic activity on monthly timescales depend on several factors. In this study, we have identified the following: (a) the Moon phases (new and full Moon), (b) the phase of the solar cycle (ascending or descending), and (c) the direction of the interplanetary magnetic field (away or toward the Sun).
BM wrote the main manuscript and performed the data analysis. MP wrote the methodology and performed the data analysis and drew the figures. LXG obtained all the data and arranged it to perform the analysis. All authors read and approved the final manuscript.
B. Mendoza is currently the Coordinator of The Earth Sciences Bachelor’s Degree at the Universidad Nacional Autónoma de México (UNAM) and has the maximum level in the Mexican National Research System. She is also a member of the Space Sciences Department at UNAM. Her main field of research is Solar Physics and Sun–Earth relationships, in particular space weather impacts on Earth’s climate and biota. M. Pazos has a Ph.D. degree in Space Physics from the Universidad Nacional Autónoma de México, and her main field of research is Sun–Climate relationships. L. X. González is member of the Mexican Space Weather Service in the Instituto de Geofisica of the Universidad Nacional Autónoma de México (UNAM). He belongs to the Mexican National Research System and his main field of research is Solar Physics, Space Weather and Cosmic Ray Detectors.
M. Pazos and L. X. González acknowledge the support of grants CB-2012/180727-CONACyT and CONACyT/AEM-2014-01-247722, respectively.
The authors declare that they have no competing interests.
Availability of data and materials
The dataset supporting the conclusions of this study is included in an additional file.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Akimov LA, Dyatel NP (2012) Influence of the Moon on the Earth’s magnetosphere at various phases of a solar activity cycle. Kinemat Phys Celest Bodies 28:39–42View ArticleGoogle Scholar
- Campbell WH (1997) Introduction to geomagnetic fields. Cambridge University Press, UKGoogle Scholar
- Grinsted A, Moore J, Jevrejera S (2004) Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process Geophys 11:561–566View ArticleGoogle Scholar
- Gulyaev RA, Gulyaeva TL (1992) Alternative non gravity mechanisms of lunar influence upon the biological processes. Biofizika 37:541–545Google Scholar
- Halekas JS, Poppe AR, Farrell WM, Delory GT, Angelopoulos V, McFadden JP, Bonnell Glassmeier KH, Plaschke F, Roux A, Ergun RE (2012) Lunar precursor effects in the solar wind and terrestrial magnetosphere. J Geophys Res 117:A05101Google Scholar
- Hapgood M (2007) Modelling long-term trends in lunar exposure to the Earth’s Plasmasheet. Ann Geophys 25:2037–2044View ArticleGoogle Scholar
- Mayaud P-R (1972) The aa indices: A 100-year series characterizing magnetic activity. J Geophys Res 77:6870–6874View ArticleGoogle Scholar
- Mendoza B, Velasco V (2009) High-latitude methane sulphonic acid variability and solar activity: the role of the total solar irradiance. J Atm Solar-Terr Phys 71:33–40View ArticleGoogle Scholar
- Michel FC, Dessler AI, Walters GA (1964) A search for correlations between Kp and lunar phases. J Geophys Res 69:4177–4181View ArticleGoogle Scholar
- Mitchell DL, Halekas JS, Lin RP, Frey S, Hood LL, Acuna MH, Binder A (2008) Global mapping of lunar crustal magnetic fields by Lunar Prospector. Icarus 194:401–409View ArticleGoogle Scholar
- Poppe A, Horányi M (2010) Simulations of the photoelectron sheath and dust levitation on the lunar surface. J Geophys Res 115:A08106View ArticleGoogle Scholar
- Richardson IG, Cane HV, Cliver EW (2002) Sources of geomagnetic activity during nearly three solar cycles (1972–2000). J Geophys Res 107(A8):SSH1–SSH13View ArticleGoogle Scholar
- Russell CT, Mulligan T (1995) The 22-year variation of geomagnetic activity: implications for the polar magnetic field of the Sun. Geophys Res Lett 22:3287–3288View ArticleGoogle Scholar
- Saito Y, Nishino MN, Fujimoto M, Yamamoto T, Yokota S, Tsunakawa H, Shibuya H, Matsushima M, Shimizu H, Takahashi F (2012) Simultaneous observation of the electron acceleration and ion deceleration over lunar magnetic anomalies. Earth Planets Space 64:83–92. doi:10.5047/eps.2011.07.011 View ArticleGoogle Scholar
- Stolov HLO, Cameron AGW (1964) Variations of geomagnetic activity with lunar phases. J Geophys Res 69:4975View ArticleGoogle Scholar
- Střeštík J (1998) Spectrum of geomagnetic activity in the period range 5 ± 60 days: possible lunar influences. Ann Geophys 16:804–811Google Scholar
- Torrence C, Compo G (1998) A practical guide to wavelet analysis. Bull Am Meteorol Soc 79:61–78View ArticleGoogle Scholar
- Yamazaki Y (2014) Solar and lunar ionospheric electrodynamic effects during stratospheric sudden warmings. JASTP 119:138–146Google Scholar
- Yamazaki Y, Richmond AD (2013) A theory of ionospheric response to upward-propagating tides: electrodynamic effects and tidal mixing effects. J Geophys Res Space Phys 118:5891–5905View ArticleGoogle Scholar