Cosmic ray counts hidden in spacecraft data highlight influence of solarcycle at Mars and Venus AAS_Publishing
1. IntroductionGalactic cosmic rays and solar energetic particles contribute to the high-energy particles that are a threat to human activities in space. Robotic missions suffer electronics failures because of these high-energy particles. Humans in space also suffer damage to their deoxyribonucleic acid .
2. Microchannel Plate Background SourcesAn MCP is a component widely used for counting photons and particles . MCPs have wide effective areas and high precision for determining the positions of incoming particles hitting the plate. However, background counts are unavoidable . In this section, we briefly overview the characteristics of MCP background sources.
It is well-known that a clear solar cycle modulation exists between GCR intensity and the solar cycle . This modulation is caused by the different states of turbulence in the solar system as a function of solar activity, resulting in GCR transport disturbances . Geomagnetic disturbances called Forbush effects, caused by magnetic storms, also modulate GCR intensity at the ground on shorter timescales .
Several other processes can result in background counts. Siegmund et al. explained that outgassing from an MCP can do this, as well as a hotspot produced by a dust particle on the MCP. However, these contributions are presumably minor for space instrumentation, because the sensors are baked and cleaned adequately before launch. After launch, the instruments operate in a high-vacuum environment.
Among the many scientific instruments on board Mars Express and Venus Express, two space plasma instruments, the Analyzers of Space Plasma and EneRgetic Atoms , were carried to Mars and Venus . These sensors were based on a common design, but were tailored to each environment. These instruments have been used to reveal the solar wind interaction with nonmagnetized planetary atmospheres. A specific focus has involved quantifying atmospheric escape in the form of charged particles .
The background counts are visible as a spread of constant counts over the whole energy–mass bins. On top of the background counts, the foreground signal can be clearly seen as clusters of counts. For example, the solar wind protons, with energies of 0.5–2 keV q−1, are visible along the M/q=1 curve on the mass ring numbers >25 in the Mars Express data ). A weaker signal at M/q=2 can also be seen at 1–4 keV q−1.
4. Decadal VariationsIn this section, the long-term trends in the IMA background counts are described to discuss an 11 yr solar activity cycle. Figure 3 shows the time series of the background data. The median values of the background counts for every three months are shown. The typical number of IMA scans was ∼10,000 within each three-month window. In addition to the median, the 5%, 25%, 75%, and 95% percentiles are also indicated in Figure 3.
It would be an exciting discussion to determine how much this GCR flux differs between Mars and Venus . Honig et al. claimed that there was a 3% au−1 gradient in the GCR intensity between 1 and 4.5 au. If we apply the decrease rate, only a couple of percent of decrease might be expected between Venus and Mars. However, comparing the absolute background count rates from the Mars Express and Venus Express IMAs is complex because the details of the implementation were not entirely identical.
Figures 6 and 7 illustrate the correlation coefficients between the Mars Express IMA background counts and the time-shifted sunspot number . Figure 6 shows the best correlation for the nine months of time lag, with a correlation coefficient of –0.86. Figure 7 shows the data with the nine-month time lag. This is slightly longer than the previously reported four-month lag from the ground-based measurements and the lag of 5.5 months from the Mars Express EDAC counters.
Using the above assumptions, we first formulated the GCR-induced counts. From the isotropic GCR directional-differential flux without planetary blockage, denoted as j , the background counts detected by a planar MCP, denoted dC, contributed from a solid angle can be calculated by Figure 8 shows the typical background counts overlaid with the fitting results using the simple model ) . A clear dip in the background counts is visible, depending on the distance of the spacecraft to Mars or Venus. The lowest background counts can be seen in Figure 8 at a pericenter of ∼250 km, when the apparent size of Mars was at a maximum. For Venus, precisely the same signature can be seen ).
This is indeed a puzzling result, and the reason for the extraordinarily large effective blocking radius was inconclusive from the present analysis. While Mars has an atmosphere, any atmospheric effect that could reduce the GCR flux is expected to be small . On the other hand, our assumption of an isotropic GCR flux with a simplified cosine-dependence of the response function may possibly have created serious bias.
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