Mercury exosphere. III: Energetic characterization of its sodium component

Icarus xxx (2012) xxx–xxx

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Mercury exosphere. III: Energetic characterization of its sodium component Francois Leblanc a,⇑, Jean-Yves Chaufray b, Alain Doressoundiram c, Jean-Jacques Berthelier a, Valeria Mangano d, Arturo López-Ariste e, Patrizia Borin f a

LATMOS/IPSL, Université Versailles Saint Quentin, CNRS, France LMD/IPSL, Université Pierre et Marie Curie, CNRS, France c Observatoire de Paris, Meudon, CNRS, France d INAF/IAPS, Roma, Italy e THEMIS – UPS 853, CNRS, C/Via ´Lactea s/n, 38200 La Laguna, Spain f Università di Padova, Padova, Italy b

a r t i c l e

i n f o

Article history: Available online xxxx Keywords: Mercury Spectroscopy Solar wind

a b s t r a c t Mercury’s sodium exosphere has been observed only few times with high spectral resolution from ground based observatories enabling the analysis of the emission spectra. These observations highlighted the energetic state of the sodium exospheric atoms relative to the surface temperature. More recently, the Doppler shift of the exospheric Na atoms was measured and interpreted as consistent with an exosphere moving outwards from the subsolar point (Potter, A.E., Morgan, T.H., Killen, R.E. [2009]. Icarus 204, 355–367). Using THEMIS solar telescope, we observed Mercury’s sodium exosphere with very high spectral resolution at two opposite positions of its orbit. Using this very high spectral resolution and the scanning capabilities of THEMIS, we were able to reconstruct the 2D spatial distributions of the Doppler shifts and widths of the sodium atomic Na D2 and D1 lines. These observations revealed surprisingly large Doppler shift as well as spectral width consistent with previous observations. Starting from our 3D model of Mercury Na exosphere (Mercury Exosphere Global Circulation Model, Leblanc, F., Johnson, R.E. [2010]. Icarus 209, 280–300), we coupled this model with a 3D radiative transfer model described in a companion paper (Chaufray, J.Y., Leblanc, F. [2012]. Icarus, submitted for publication) which allows us to properly treat the non-maxwellian state of the simulated sodium exospheric population. Comparisons between THEMIS observations and simulations suggest that the previously observed energetic state of the Na exosphere might be essentially explained by a state of the Na exospheric atoms far from thermal equilibrium along with the Doppler shift dispersion of the Na atoms induced by the solar radiation pressure. However, the Doppler shift of the spectral lines cannot be explained by our modelling, suggesting either an exosphere spatially structured very differently than in our model or the inaccuracy of the spectral calibration when deriving the Doppler shift. Ó 2012 Elsevier Inc. All rights reserved.

1. Introduction Numerous observations of the spatial distribution of the Na emission from Mercury’s exosphere (Sprague et al., 1997; Schleicher et al., 2004; Potter et al., 2006, 2007, 2009; Baumgardner et al., 2008; Leblanc et al., 2009; Vervack et al., 2010) contribute to clarify our understanding of the global dynamics of this exosphere. They also illustrate its complex spatial structure which was also observed to vary on short and long time scales (Potter et al., 2009; Leblanc and Johnson, 2010; Mouawad et al., 2010). A few of these observations also highlighted the energetic state of Mercury’s Na exosphere by measuring Doppler width and shift of

⇑ Corresponding author. E-mail address: [email protected] (F. Leblanc).

the emission Na lines (Killen et al., 1999; Leblanc et al., 2008, 2009; Potter et al., 2009). The first attempt to measure the Doppler width of the emission Na D2 line was reported by Potter and Morgan (1987) and later discussed by Killen et al. (1999) along with additional high resolution observations from the AA telescope. These authors concluded that the Na exosphere was significantly hotter than the corresponding surface temperature, a signature of an exosphere not in thermal equilibrium with the surface. Such an observation was later confirmed by Leblanc et al. (2008). But both analyses were based on a simple theoretical analysis of the measured Doppler width. Leblanc et al. (2008) used optically thin and maxwellian distributions when describing the Na exosphere. Killen et al. (1999) considered the optical thickness of the exosphere but for an exosphere at thermal equilibrium, with a spatially uniform source and at rest with respect to Mercury. However, it is now well known that Mercury’s Na exosphere is

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neither thermodynamically at equilibrium nor spatially uniform nor at rest with respect to Mercury (Killen et al., 2007; Leblanc et al., 2007). As a consequence, downward modelling when analyzing spectral Doppler width measurements of Mercury’s exosphere can only provide a first order approximation. Only simultaneous forward modelling of the Doppler width and shift would be able to take into account the non-uniformity of the exosphere, its variable optical thickness and its non-thermal equilibrium state. As a matter of fact, Potter et al. (2002) reported for the first time the measurement of the Doppler shift of the Na atoms in Mercury’s tail. These authors deduced from their observations the heliocentric anti-sunward velocity component, suggesting a velocity increase from 2 km/s at 2 Mercury radii from Mercury’s centre up to 10 km/s at 15 Mercury radii in the tail. This velocity profile was later reproduced by Leblanc and Johnson (2003) who demonstrated the role of the solar radiation pressure in producing such characteristics along the tail as suggested by Smyth (1986). A first map of the spatial distribution of the Doppler shift in Mercury exosphere was published by Leblanc et al. (2008) underlining also the effect of the solar radiation pressure close to Mercury. Recently, Potter et al. (2009) measured the Doppler shift of the Na atoms at various orbital positions of Mercury and discussed its main origins. These authors used a 2.7 m telescope at the University of Texas McDonald observatory with a spectral power resolution of 433,000 as well as the McMath Pierce solar 1.6 m telescope with spectral resolving power of 430,000, 267,000 and 140,000. They reported velocity towards the observer (perpendicular to the surface) from 0 to 1 km/s and variations consistent with an acceleration of the Na atoms in the anti-sunward direction. Actually, most of the measured Doppler velocities correspond to Na atoms moving towards the observer, away from the surface. Potter et al. (2009) explained the observed Earthward Doppler shift by an exosphere moving outward from the subsolar point towards the terminator because of the effect of the solar radiation pressure but identified also in all of their observations contributions from local sources of sodium atoms spatially variable from one observation to another. In this paper, we present two new sets of observations of both the Doppler shift and Doppler width of the Na exospheric D1 and D2 lines obtained at a resolving power of 370,000. These two observations were performed at two opposite orbital positions of Mercury with good atmospheric conditions (Section 2). We then performed simulations of the Na exosphere at these two positions using Mercury Exosphere Global Circulation Model (Leblanc and Johnson, 2010) and compared the results to the observations (Section 3). Such comparison was possible thanks to the use of a nonmaxwellian radiative transfer model developed specifically for this application (Chaufray and Leblanc, 2012). In Section 4, we discuss the results and in Section 5 we conclude on the possible origins of the observed features.

2. Themis observations 2.1. Data treatment THEMIS (López Ariste et al., 2000) is a French–Italian solar telescope on the Canary Island of Tenerife with a 0.9 m primary mirror (with a central obscuration of 0.4 m) and a 15.04 m focal length. The slit size was 0.2500  69.600 and the spectral resolution of 15.9 mÅ provided 370,000 resolving power. Two independent cameras are used to measure the D2 and D1 Na emission lines. Each camera covers a spectral range of 4 Å and is composed of 512 by 512 pixels at 7.8 mÅ/pixel spectral dispersion (0.4 km/s). The telescope provided tip-tilt corrections at 1 kHz. In order to image Mercury’s exosphere, we moved the slit between each individual

position perpendicular to its spatial axis by a distance equivalent to the slit width. More than 24 positions of the slit were used to cover the brightest part of the exosphere. At each slit position, ten individual exposures of 20 s were taken with negligible overhead for CCD readout and slit motions. The data were bias corrected and flat fielded. The flat field was obtained by observing the Sun using a special mode avoiding solar bright or dark spots. For each D1 or D2 camera, we used dedicated observations of the Sun to spectrally calibrate these cameras, the two cameras being completely independently calibrated. The spectral calibration is based on the identification of telluric lines and of the solar Fraunhofer Na line (for each camera, we usually could identify between 4 and 5 telluric lines within the measured spectral range). The sky background was calculated from two segments at each end of the slit interpolated over the whole slit by fitting these two parts with a second degree polynomial. In order to subtract the reflected solar spectrum from Mercury’s surface, we used solar spectra obtained for the closest atmospheric terrestrial conditions (similar air mass and zenith angle), shifted in wavelength, and scaled to the measurements. The exospheric emission line is then spectrally integrated after subtracting an average background level calculated outside the emission line. We then fitted the emission line with a Gaussian function and derived the Doppler shift and the spectral full width at half maximum (FWHM) of the observed emission line. The FWHM is then corrected by the spectral resolution of the instrument measured from the telluric lines. For each position of the slit during a sequence of observations, we retrieved the exact Doppler shift of Mercury with respect to Earth and Sun (using JPL/Horizon ephemerides) and derived the exact position of the exospheric emission in the frame of Mercury. The brightness calibration is based on the Hapke theoretical model of the reflected solar light from Mercury’s surface, which has the advantage of avoiding any uncertainty due to Earth’s atmospheric absorption (Sprague et al., 1997). This theoretical model takes into account the range of possible seeing estimated from the observations as explained in Leblanc et al. (2008). The main source of uncertainty on the Doppler shift and width is first of all the spectral calibration. As an example, a systematic error in the calibration cannot be excluded because of the very few telluric lines that could be identified in the 4 Å spectral range of each camera, the uncertainty to accurately identify the bottom of these telluric lines, and the difficulty to very accurately calibrate a solar spectrum due to Earth rotation, air mass issue, spectral variability of the spectral calibration during a day of observation. . . A second important source of uncertainty is the subtraction of the reflected solar flux on Mercury’s surface. A final potential source of uncertainty is the presence of weak telluric lines close to the exospheric emission line that could deform the emission line and lead to an incorrect determination of the spectral shift and width. Following the same approach developed in Leblanc et al. (2008), we also determined the uncertainty in the retrieved Doppler width of the spectra as being equal to 0.27 km/s from signal/noise analysis. Spectral width determination is clearly less dependent on the spectral calibration but could be significantly impacted by an inaccurate subtraction of the reflected solar line or/and the presence of telluric lines. Table 1 provides the main parameters of the two observations that are described in the following sections. 2.2. July 2009 observation The first observation that will be described was obtained on the 1st July 2009, starting at 08h51 UT. Mercury was at a true anomaly angle (TAA) of 315.9°, a distance from the Sun of 0.323 AU, and a heliocentric radial velocity of 6.99 km/s. The phase angle was equal to 51.6° (the minus means that the evening part of Mercury’s dayside was facing the Earth) and the size of Mercury radius

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Table 1 Observations of Mercury’s D2 and D1 exospheric emissions by THEMIS. The spectral resolution of both observations was 15.9 mA and the spectral dispersion 7.8 mA/pixel (or 0.4 km/s/pixel). During both observations, the dusk terminator was in view. Date of observations

True anomaly angle (°)

Phase angle (°)

Distance to the Sun (AU)

Mercury’s angular radius (00 )

Seeing (00 )

Mercury/Sun Doppler velocity (km/s)

07/01/2009 19/22/2009

316 96

308.4 324.6

0.323 0.38

2.83 2.6

1.67 ± 0.35 1.33 ± 0.3

6.99 9.99

equal to 2.8300 . Twenty-four subsequent positions of the slit were used to build a complete image of Mercury’s exosphere (covering 600 ) in 90 min. The seeing deduced from the continuum measurement was estimated from both cameras as being equal to 0.59 ± 0.12 Mercury radius. Fig. 3 presents the measurements deduced from the D2 (panels a, brightness, c, Doppler shift, and e, Doppler width) and D1 (panels b, d and f) cameras. There is a good agreement between the spatial distributions of the emission brightness intensities measured by these two cameras (Fig. 3a and b). Clear peaks in intensity can be seen at high latitudes with the most extended peak in the Southern hemisphere. This discrepancy between northern and southern hemisphere extensions of the peak of sodium is actually in agreement with the recent global mapping of the magnetic field suggesting a wider cusp footprint location in the southern hemisphere than in the northern hemisphere (Anderson et al., 2011; Richer et al., 2012). The average emission brightness of the D2 line per Mercury disc area is 2.39 ± 0.13  103 kR and 1.87 ± 0.21  103 kR for the D1 line. The ratio of these two brightness intensities is therefore equal to D2/ D1 = 1.28 ± 0.34 (and is relatively independent of the spatial region where it is measured). The g-factors of these two lines taking into account Mercury’s distance to the Sun and its heliocentric radial velocity are 22.3 and 30.4 s1 for the D1 and D2 emission lines respectively (calculated following Fulle et al. (2007)). Their ratio is therefore equal to gD2/gD1 = 1.36 close to the observed ratio. As a consequence, the emission lines of the Na exosphere can be considered optically thin on average across the planet’s disc. Panels c and d display the measured Doppler shift of the Na atoms with respect to Mercury. On both emission lines, negative Doppler velocity are observed from 0.6 ± 0.2 km/s close to the subsolar region to 0.3 ± 0.1 km/s close to the dusk terminator. The Doppler velocity measured on the D2 line is significantly less noisy than on the D1 emission line. Negative Doppler velocities correspond to Na atoms moving Earthward. The spatial distribution of the Doppler in Fig. 3 panels c and d might be explained, as a first order approximation, considering the drawing in Fig. 1a. The velocity which is measured from Earth is indeed dominated by two populations of Na atoms: – The atoms ejected from the surface which velocity is essentially perpendicular to the surface (the red arrows in Fig. 1a). – The atoms accelerated by the solar radiation pressure which velocities are in an average anti-sunward (green arrows) and increase from the subsolar to the terminator. The size of these arrows in Fig. 1a corresponds to a scenario where the peak of ejection is at the subsolar point (largest red arrow). In that case, the accumulated effect of the solar radiation pressure increases from the subsolar point to the terminator (largest green arrows). Fig. 1 is similar to Fig. 5 of Potter et al. (2009) who suggested that for such a configuration, in the case of a globally horizontal subsolar to terminator flow, the observed Doppler velocity should peak towards the observer between the subsolar and subEarth points and be directed in the opposite direction at the extreme sides of the field of view close to the terminator and the limb. Contrary to what we could expect from the simple hori-

Fig. 1. Schematic drawing showing the dependency of the global exospheric Na velocity with respect to the observer. The green arrows correspond to the antisunward flux (increase in the anti-sunward direction). The red arrows correspond to the flux ejected from the surface and the dark arrows to the sum of the two components along the line of site of the observer (dashed-dotted lines). Panel a: in the case of a source of the exosphere peaking at the subsolar region. Panel b: in the case of a source of the exosphere peaking at the dawn terminator (top part of the figure). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

zontal subsolar to terminator flow, Fig. 3c and d, show Earthward Doppler velocity everywhere, suggesting a situation where the Earthward Doppler shift is dominated by the component due to atoms ejected from the surface rather than by the component due to atoms accelerated in the anti-sunward direction since an Earthward Doppler velocity is observed within the full field of view of the telescope. Potter et al. (2009) also reported observations of Mercury Na exospheric Doppler shift. In particular, one of their observations was obtained at TAA = 295° for a phase angle of 40° (their February 3 and 4 2000 observations), that is close to Fig. 3 position of Mercury. Potter et al. (2009) observed with a similar phase angle but faced the morning side of the planet contrary to our case. Potter et al. (2009) reported Earthward velocity from 0.5 km/s close to the subsolar region to 0.8 km/s off of the dawn terminator that is negative velocity (when moved into Fig. 3 frame) increasing towards the dawn terminator. These authors explained the peak of Earthward Doppler velocity at the terminator as being due to a local source of sodium resulting from the evaporation of condensed atoms at dawn as depicted in Fig. 1b. In such a case, the component

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Fig. 2. Projection in the velocity plan of the sunward/anti-sunward and dawn/dusk directions of the simulated MEGCM Na normalized velocity distributions in the equatorial plane. The projection is calculated in cells between 1.0 RM and 1.07 RM from the surface. For TAA = 316°: Panel a: at 12° from the dawn terminator on the dayside. Panel b: at 12° from the dusk terminator on the dayside. Panel c: at the subsolar point. For TAA = 96°: Panel d: at 12° from the dawn terminator on the dayside. Panel e: at 12° from the dusk terminator on the dayside. Panel f: at the subsolar point. Contour levels are 0.5, 0.1, 0.01 and 0.001 of the maximum starting from the centre of each panel (also indicated on each panel). Solid line: simulated Na distribution. Dashed line: bimaxwellian distribution with full width at half maximum and mean velocity similar to the simulated distribution along each direction.

perpendicular to the surface would be larger close to the dawn terminator and as a consequence the component towards the observer larger close to the terminator than near the subsolar region. In our observation Fig. 3, we were observing the evening side of the planet. A dawn enhancement of the production of Na exospheric atoms would occur behind the apparent disc. In that case,

the observed Earthward component of the Doppler velocity would be consistent with Na atoms moving from the dawn terminator towards the dayside. However, it is not consistent with the dusk terminator Earthward component observed also in Fig. 3c and d. A peak of ejection on the nightside close to the dawn terminator could be also consistent with Potter et al. (2009) observations. It

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could explain the observed Doppler shift with a global circulation from dawn to dusk leading to a Earthward apparent Doppler shift at both terminators. However, the solar pressure should push back in the anti-sunward direction all non-escaping Na atoms towards the terminator. As shown in Fig. 1a and b, all these non-escaping particles pushed in the anti-sunward direction by the solar pressure should lead to an anti-Earthward Doppler velocity at limb and terminator. Fig. 3c and d displaying a different distribution

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of the Doppler shift could be explained only if most of these potential anti-sunward moving particles disappear from THEMIS field of view during their motion towards the subsolar point. At the subsolar point, Potter et al. (2009) observed velocity of 0.5 km/s with respect to our own observations of values between 0.8 and 0.4 km/s (Fig. 3c and d respectively). Potter et al. (2009) considered the possibility to have systematic errors of up to 0.5 km/s. In our case, we also cannot exclude systematic spectral

Fig. 3. THEMIS observations of the D1 and D2 Na emission lines realized on the 2009/07/01 (TAA = 316°). Panels a, c and e: D2 emission line. Panels b, d and f: D1 emission line. Panels a and b: Emission brightness. Panel c and d: Doppler shift. Panels e and f: Doppler width. Only pixels with signal noise ratio larger than 30 are plotted. Mercury’s disc is also plotted (placed in the observation field of view using the continuum measurements and JPL/Horizon ephemerides). The subsolar point corresponds to the intersection of the two dashed lines (the subsolar and equator lines) in the bottom part of each panel. The top part of the disc with several dashed lines corresponds to the part of the apparent disc on the nightside.

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calibration errors of 1 km/s considering the uncertainty on the spectral calibration and the difference in Doppler shift between the D2 (Fig. 3c) and the D1 (Fig. 3d) emission lines. 1 km/s is equivalent to 2.5 pixels along the spectral axis. It is also close to the spectral resolution of 0.8 km/s. Another possible explanation for the difference between our two sets of observations comes from the difference in observation conditions. Between Potter et al. (2009) February 2000 observations and THEMIS 1st July 2009 observation, the slight difference in Mercury’s positions applies different solar pressure, equal to 120 cm2/s at TAA = 316°, that is 33% of Mercury’s gravity acceleration, and to 192 cm2/s at TAA = 295° that is 53% of Mercury’s gravity acceleration. A higher solar pressure would induce a decrease of the Earthward velocity component, which is consistent with what we observed. Dawn/ dusk asymmetry may also contribute to this discrepancy as well as the presence of two bright peaks at high latitude in our observation contrary to the case of the Potter et al. (2009) observation. If bright peaks of the emission intensity at high latitude are associated with ejection of sodium from the surface, this should contribute to increase the Doppler shift away from the surface and towards the observer. However, we do not observe in Fig. 3c and d local increases of the Doppler shift in association with these bright spots even if the seeing was smaller than 0.5 RM. 2.3. October 2009 observation We selected a second observation to illustrate the dependency of the Doppler shift and width with respect to Mercury’s orbital position. Panel 2 displays an observation obtained on the 22 October 2009 (09h21 UT) at TAA = 96° with a phase angle of 25.4° (evening side of Mercury) at 0.38 AU from the Sun. The seeing during that observations was equal to 0.51 ± 0.11 Mercury radius with Mercury radius 2.600 . Thirty successive positions of the slit were used for a complete scan lasting 1h40. Mercury heliocentric velocity was equal to 9.99 km/s (corresponding to an orbital position roughly opposite to Fig. 3 observations). Contrary to Fig. 3 case, the distribution of the emission brightness does not display significant peaks at high latitude but an increase of the signal at the limb. As explained in Leblanc and Johnson (2010), such a limb increase may be interpreted as an exosphere peaking behind the planet (at the dawn terminator). The average emission brightness measured was 2.34 ± 0.08  103 kR and 1.17 ± 0.06  103 kR for the D2 and D1 emission lines respectively. The g-factors of these two emission lines were gD1 = 19.3 and gD2 = 34.5. The ratio of the two measured emission brightnesses is therefore D2/ D1 = 2 ± 0.14 whereas the ratio of the two g-factor is equal to gD2/ gD1 = 1.79. The observed ratio is therefore larger from the theoretical one which is probably related to the quality of the D1 measurements (Killen, 2006). The Doppler shift measured during that observation displays the same global increase from subsolar to terminator as in Fig. 3 but with an increase significantly larger from 1.5 km/s at the subsolar limb to 0.6 km/s at the terminator (panel c). As for Fig. 3 observation, we did not find a good agreement between the measured Doppler shift from the D2 and the D1 lines. The Doppler shift velocity retrieved from the D1 line is in general 0.5 km/s smaller than the ones retrieved from the D2 line. Potter et al. (2009) observed Mercury Na exosphere at TAA = 84° on May 23 2007 at a phase angle of 78° (morning side of the planet) and a spectral resolution of 140,000. This is slightly different from our case, in particular the solar pressure was equal to 190 cm2/s (51% of the gravity acceleration) in the case of TAA = 84° and 170 cm2/s (46%) at TAA = 96°. Potter et al. (2009) reported Earthward Doppler velocity around 0.6 km/s almost constant along the slit placed parallel to the equator. Unfortunately, the 78° phase angle of Potter et al. (2009) observation limits the possibility to compare to our measurements which were obtained

at a much smaller 25.4° phase angle. In another way, the contribution of the anti-sunward component of the exospheric velocity to the measured Doppler shift was four times smaller in Potter et al. (2009) observation than in THEMIS one. Actually, comparing February 3 observation by Potter et al. (2009) obtained at a phase angle of 40° to May 23 observations obtained at a phase angle of 78°, it is remarkable that the same range of velocity was measured by Potter et al. (2009). If the velocity of the particles in the exosphere was dominated by the heliocentric component, this component would be larger at TAA = 84° than at TAA = 295° according to Potter et al. (2009) observations and always directed towards the Sun. Contrary to the measurement of the Doppler shift, the measurement of the Doppler width of the exospheric emission line is less dependent on the quality of the spectral calibration. Whereas the Doppler shift measurement will depend on the determination of the spectral dispersion and of the determination of an absolute reference in the observed spectral range, the measurement of the Doppler width does depend only on the spectral dispersion. Fig. 3e and f and Fig. 4e and f display the measured Doppler width deduced from the D2 and D1 emission lines. Both lines being the product of 3 and 2 hyperfine structures respectively, their spectral width cannot be compared directly. Actually, to invert spectral width into a physical parameter describing the energetic state of the exosphere is not straightforward. As a consequence, we chose to discuss these parameters of the observed spectra by comparing observation with a simulation coupled to a radiative transfer model adapted to an exosphere at non-local thermodynamic equilibrium (Section 3). This theoretical model is described in a companion paper (Chaufray and Leblanc, 2012).

3. Comparison between model and observed Doppler speed and width Mercury Exosphere Global Circulation Model (MEGCM) is a 3D Monte-Carlo model of Mercury potassium and sodium exospheric components which takes into account the temporal variation of the exosphere along Mercury’s orbit by coupling a neutral model of the exosphere, a model of ion circulation in Mercury’s simplified magnetosphere and a simplified description of the Na exospheric particles trapped in Mercury’s upper surface (Leblanc and Johnson, 2003, 2010; Leblanc and Doressoundiram, 2011). In this approach, the neutral exosphere is described as being composed of two components: – a source component which is produced by exogenic processes, that is, meteoroid vaporization and gardening or regolith diffusion bringing fresh sodium atoms in the upper surface of Mercury, – an ambient component which corresponds to the population of exospheric atoms moving around the planet up to their ionization, reabsorption in the surface or loss by Mercury’s gravity field. MEGCM considers the four main processes of ejection of volatiles into Mercury’s exosphere, namely: solar wind sputtering, photo induced desorption, thermal desorption and meteoroid vaporization (Leblanc et al., 2007). A typical simulation corresponds to the simulation of 10 successive years of Mercury to reach a stationary solution on a yearly base. At each time step of the simulation (less than 1 s), the typical number of simulated exospheric test-particles is around 10,000, of few times 106 test-particles in the upper surface and of 100 ionized test-particles. This model was successfully applied to reproduce the observed spatial distribution of the exosphere (Leblanc and Johnson, 2003) and Mercury’s

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Fig. 4. THEMIS observations of the D1 and D2 Na emission lines realized on the 2009/10/22 (TAA = 96°). Same legends as in Fig. 3.

sodium exosphere annual cycle (Leblanc and Johnson, 2010). In this latter paper, it was shown that none of the ejection processes dominates the production of Mercury sodium exosphere during the whole Mercury’s year (Leblanc and Johnson, 2010). Moreover, Mercury sodium exosphere seasons were highlighted with a global variation of the exosphere total content by a factor 5 along one Mercury’s year. MEGCM was also applied to model the potassium component of Mercury’s exosphere and compared to observations (Leblanc and Doressoundiram, 2011). This later work suggested that the unusual sodium/potassium ratio observed from Earth

might be due to the difference in spatial distributions of these two exospheric elements enhanced by the poor spatial resolution of ground-based observations. In order to compare the observations of Doppler width and shift described in the previous section with MEGCM simulations, we have calculated the 3D velocity distribution of the Na atoms in the exosphere on a 30  10  30 grid in longitude (linearly distributed), latitude (distributed following a cosine distribution) and altitude (exponentially distributed between 1 and 2 RM) respectively. Within each cell of the grid, the 3D velocity is then inte-

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grated on a 10  10  10 grid in the velocity space Vx  Vy  Vz on a [5, 5] km/s range centred on Mercury’s frame. Mercury exosphere for the two sets of observations discussed in Section 2 is simulated using the exact ephemerides. At a given TAA, the 3D velocity distributions are integrated during 20 h. Twenty hours of simulation centred on TAA = 316° corresponds to the portion of Mercury’s orbit [314.3°, 319.1°] and to [94.3°, 97.8°] at TAA = 96°. Fig. 2 presents few examples of velocity distributions calculated at these two TAA. No significant differences between the two Mercury positions are seen in Fig. 2. Panels a and d corresponding to the velocity distributions calculated at the dawn terminator of the planet display a velocity distribution with average velocity directed towards the anti-sunward direction and away from the surface whereas the velocity distribution at the subsolar region (panels c and f) is at rest in Mercury’s frame (and almost maxwellian as shown by the comparison with a bimaxwellian distribution represented by the dashed lines). Panels b and e taken at the dusk terminator also display clear shifted distributions towards the anti-sunward direction. At TAA = 316°, the main sources of the Na atoms in the exosphere are for 40% of the particles photon-stimulated desorption, for 30% thermal desorption, for 20% solar wind sputtering and for 10% micro-meteoroid vaporization. At TAA = 96°, 65% of the Na atoms in the exosphere were ejected by photon-stimulated desorption, 15% by solar wind sputtering, 12% by thermal desorption and 8% by micro-meteoroid vaporization (Leblanc and Johnson, 2010). To properly compare simulation and observations, we reconstruct for a given observation the emission spectra as it should have been observed through our simulated solution (considering the phase angle of the observation, the solar illumination and the terrestrial atmospheric effects). Because, the optical thickness is not negligible at limb (see Section 2.3) and because of the nonmaxwellian nature of the velocity distribution as shown in Fig. 2, we built an original theoretical radiative transfer model able to take into account these two particular properties of Mercury’s exosphere. These properties are particularly important to interpret the Doppler width of the sodium spectral line as presented in the companion paper (Chaufray and Leblanc, 2012). This radiative transfer model based on a Monte-Carlo approach is able to fully take into account non-uniform sodium exospheric densities as well as the non-analytical velocity distribution functions as provided by the MEGCM model. In this model, the directional spectral emission volume rate is computed for six selected directions, one of these directions correspond to the opposite direction of the line of sight of the observations. The emergent spectral brightness on the line of sight is then calculated by formal solution of the radiative transfer. The main drawback of such an approach is the typical running time needed to reconstruct the emission spectra. To get a reasonable signal/noise ratio, few hundred thousand scatterings need to be simulated and even with that number only the brightest regions are properly simulated. The seeing effect due to the terrestrial atmosphere is also taken into account. This was done by convolving a Gaussian with the simulated 2D distribution of the emission spectra in the same way as done in Sprague et al. (1997). This Gaussian distribution takes into account the spatial blurring of the emission spectra at each Doppler velocity in the terrestrial rest frame. The seeing strength is deduced from the measurement (Section 2). The final product of our simulation is a 2D spatial distribution of the emission spectra along the line-of-sight calculated for Mercury’s orbital position, the configuration and the terrestrial atmospheric conditions during each observation. We then used the same method as used to analyze the observations, to derive both Doppler shift and Doppler width in the simulation. Fig. 5 provides the results of the simulated intensity, Doppler shift and Doppler width of the D2 emission line for the conditions of observation by THEMIS at TAA = 316° (Fig. 3). The right column

corresponds to the simulated emission without terrestrial atmosphere (without seeing effect), whereas the left column was deduced from the right column for a seeing equal to 1.700 as suggested by the observations. As shown when comparing these two columns (not plotted at the same scales), the atmospheric terrestrial seeing essentially decreases the peak intensity of the emission and moves its position inside Mercury’s apparent disc (as suggested by Potter et al. (2006)). The seeing also slightly changes the apparent range of simulated Doppler shift because it mixes various velocity distributions with different Doppler shifts. This is particularly true in regions of low emission brightness (close to the terminator at the top of each panel) because the seeing would lead to a mixture of photons coming from bright regions close to the limb and the subsolar region with photons coming from much less bright regions. The simulated velocity distribution in the terminator region is therefore affected by the bright regions, moving the apparent Doppler shift towards the one of the brightest regions. The Doppler width is also affected by the seeing for the same reasons. The main effect is to increase the apparent Doppler width because the apparent velocity distribution along a line-of-sight at the terminator will derive from the relative velocity of photons emitted from atoms with terminator Doppler shift and from atoms with limb Doppler shift. Panels a, c and e of Fig. 5 should be therefore compared to panels a, c and e of Fig. 3 respectively (plotted with the same scales). The spatial distribution of the simulated emission simulated does not fit well with the observed one which is not surprising since we did not specifically include in our model peaks of exospheric production at high latitude as suggested by the observations. Beside these two regions of emission peaks, the global intensity of the exosphere is well reproduced by the simulation. As shown in Fig. 5d, the simulation suggests Earthward Doppler shift which are varying from 0.2 km/s to 0.2 km/s with a global increase from the subsolar region to the terminator. We chose to arbitrarily shift the simulated velocity by 0.8 km/s after convolution with the seeing (Fig. 5c) in order to compare with Fig. 3c. As seen in Fig. 5c, in that case the comparison is very good, the global distribution of the measured Doppler shift is well reproduced by the simulation both in intensity and in spatial distributions. This shift of 0.8 km/s of the simulated Doppler should be compared with the spectral dispersion of THEMIS observations which was 7.8 mÅ or 0.4 km/s, the spectral resolution being equal to 15.9 mÅ or 0.8 km/s. The error suggested by the correction we applied to our simulation is therefore of the same order as the spectral resolution of THEMIS observations. It is also of the order of the resolution of the simulation in velocity which is of 1 km/s. When comparing Figs. 5e and 3e, we also conclude that the simulated Doppler width is in relatively good agreement with the measured one taking into account the 0.27 km/s uncertainty on the retrieved spectral width. It is somewhat puzzling that the observed emission brightness spatial distribution is so different than the simulated one whereas both Doppler shift and Doppler width spatial distributions are much less different. In particular, the observation suggests no association between observed peaks in brightness and energetic structures of the exosphere. The comparison between THEMIS observations at TAA = 96° and the simulation is not as good as at TAA = 316° except for the measured emission. As shown in Fig. 6c and e, the simulated Doppler shift and width are all significantly different than observed (Fig. 4a, c and e). We convolved these simulated images with the 1.300 seeing effect estimated from THEMIS observations (Fig. 6a, c and e). The spatial distribution and intensity of the Na emission is well reproduced by the simulation. But the Doppler shift measured by THEMIS is significantly different than simulated, an arbitrary shift by 1.4 km/s is indeed needed to be applied to the simulation to reproduce the observed Doppler shift range

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Fig. 5. Simulation of 2009/07/01 D2 measurements. Panel a: Emission brightness with seeing of 1.700 . Panel b: Emission brightness obtained with no seeing. Panel c: Doppler shift obtained with a seeing of 1.700 and shifted by 0.8 km/s for comparison with the observations displayed in Fig. 3c. Panel d: Doppler shift obtained with no seeing. Panel e: Doppler width obtained with a seeing of 1.700 . Panel f: Doppler width obtained with no seeing. Same legends as in Fig. 3.

(Fig. 4c). When applying such a value, the Doppler shift spatial distribution is then relatively well reproduced by the simulation with a minimum close to the subsolar point and an increase of the Doppler shift away from this region by 0.6 km/s. In order to retrieve the observed range of Doppler width, it is also needed to increase all simulated values by 0.6 km/s (two times the estimated

resolution) in order to find a good agreement with the observations as indicated in Fig. 6e. For these observations the spectral widths deduced from the D1 and D2 spectral lines were much more different than for the TAA = 316° observation. The D1 spectral width is 0.4–0.8 km/s smaller than the D2 spectral width whereas it was only 0.2 km/s larger at TAA = 316°. As for the Doppler shift, we con-

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Fig. 6. Simulation of 2009/10/22 D2 measurements. Panel a: Emission brightness with seeing of 1.300 (Fig. 4a). Panel b: Emission brightness obtained with no seeing. Panel c: Doppler speed obtained with a seeing of 1.300 and shifted by 1.4 km/s for comparison with the observations (Fig. 4c). Panel d: Doppler shift obtained with no seeing. Panel e: Doppler width obtained with a seeing of 1.300 and increased by +0.6 km/s for comparison with the observations (Fig. 4e). Panel f: Doppler width obtained with no seeing. Same legends as in Fig. 3.

clude that the uncertainty on the Doppler width was significantly larger at TAA = 96° than during TAA = 316°.

4. Discussion Between the two observed orbital positions, the difference in Mercury’s heliocentric motion applies a different effect of the solar

pressure on the Na atoms. At TAA = 96°, Mercury moves away from the Sun at 9.99 km/s. The solar radiation pressure leads to the increase of the anti-sunward velocity of the Na atoms. The spectral Doppler shift of these atoms will increase towards the red and outside of the solar Fraunhofer absorption line, so that the solar radiation pressure will continuously increase. In the case of TAA = 316°, Mercury is moving towards the Sun (at 6.99 km/s, that is, an atom at rest on Mercury, will see the solar spectrum blue shifted). A par-

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ticle ejected from the surface towards the Sun will be first slowed down by the solar radiation pressure and then will be accelerated in the anti-sunward direction. In that case, this exospheric particle will see initially a blue shifted solar spectrum. Under the effect of the solar radiation pressure, the relative Doppler shift of this particle with respect to the Sun will decrease and will then increase when the particle velocity, directed in the anti-sunward direction, become larger than the velocity of Mercury. This particle will see progressively a solar spectrum spectrally Doppler shifted from blue at ejection to red after a significant acceleration by the solar pressure. Since from the continuum down to the bottom of the Na Fraunhofer line, the solar flux varies by more than a factor 10, an atom moving from a blue Doppler shift to a red shift with respect to the solar line will be much less accelerated by the solar radiation pressure than a particle more and more red shifted as at TAA = 96°. The heliocentric velocity of the particles at TAA = 96° should be more anti-sunward than at TAA = 316°. As shown in Figs. 3 and 4, we observed the contrary with larger heliocentric velocity at TAA = 316° than at TAA = 96°. The difference in phase angle between the two observations may explain the discrepancy. The TAA = 96° observation was obtained with a phase angle smaller than at TAA = 316°, so that the observational configuration was more favourable for observing the heliocentric component of the Na atoms at TAA = 96° than at TAA = 316°. As an example, if we suppose that the heliocentric component is the dominant velocity component of the Na exospheric particles during these two observations and is the same, the difference in phase angles between the two observations should induce a 50% larger measured Doppler shift during TAA = 96° observation that at TAA = 316°. Moreover, since all ground based observations are done through the terrestrial atmosphere, seeing effects should be taken into account. This is particularly true when deriving the Doppler width. Since the seeing mixes various spatial regions, the main effect on the velocity distribution is to mix regions of various Doppler shift, and to increase the width of the distribution. Therefore, we can expect also larger Doppler width where larger range of Doppler shift is expected, that is, at TA = 96° with respect to TAA = 316° as observed. By comparing the two sets of observations described in this paper, we conclude that: – The variation of the Doppler shift is opposite to what was expected. We observed larger sunward heliocentric velocity at TAA = 96° than at TAA = 316°. We also observed the effect of the solar radiation pressure on the exosphere, the heliocentric velocity towards the Sun decreases moving from subsolar to terminator but is never suggesting an anti-sunward motion. These surprising results, in particular when comparing to simulation, casts doubt on the quality of the calibration of our observations. Spectral calibration and Doppler shift retrieval are difficult tasks that depend on several choices that lead to a global uncertainty on the Doppler shift of the order of the measured value. However, the two sets of observation were obtained during two independent campaigns with independent calibration. Moreover, comparisons with Potter et al. (2009) observations suggest a relatively good agreement with our measured Doppler shift. We are therefore left with the conclusion that our modelled exosphere is significantly different from the observed one. In particular, an exosphere produced from the nightside or early morning may lead to such observations if a large proportion of the particles moving towards the dayside are lost during their motion on the dayside, or, did not get pushed back in the anti-sunward direction by the solar pressure. – The Doppler width measured at TAA = 96° is globally larger than at TAA = 316°. At TAA = 316°, our simulated exosphere displays a relatively good agreement with the measured

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one and suggests also a small increase of the Doppler width from TAA = 316° (Fig. 5f) and TAA = 96° (Fig. 6f), but much smaller than the observed one. The comparison between observations and simulations highlights several points: – The simulation does not properly reproduce the observed Doppler shift. A systematic shift of the calculated Doppler shift at least of the order of the uncertainty due to the spectral calibration needs to be considered to retrieve a good agreement. – The simulation does reproduce the Doppler width range observed at TAA = 316°. This suggests that the energy range of the processes of ejection is properly approximated in the simulation. Such an agreement might be also due to the fact that even if the Doppler shift is not well reproduced by the simulation, the dispersion of the Doppler shift is correctly reproduced. We performed a simulation where we shifted all velocity distribution of the ejecta in our model by +2 km/s, in order to simulate the case of a peak of ejection at 3 km/s. In that case, the simulated Doppler shift at the subsolar point is in good agreement with the observations (around 1.6 km/s). But, the simulated emission brightness is around six times less intense at the limb and the contrast from limb to terminator is more than 15, contrary to the observations where such a contrast is less than 5. Even considering the seeing effect, the observed spatial distribution of the emission is not consistent with a globally escaping exosphere. Moreover, the simulated Doppler shift is not everywhere sunward but at the terminator is dominated by particles moving away from the Sun. Therefore, there is an incompatibility between a sunward moving exosphere at the terminator and an exosphere essentially produced on the dayside. There is also an incompatibility between larger velocities at ejection and measured Doppler width. Indeed, we also found in the simulation Doppler width always larger than 3.2 km/s, that is, between 0.4 and 0.6 km/s larger than observed. As explained earlier, a larger range of ejection velocity implies a larger range of Doppler shift induced by the solar radiation pressure and as a consequence larger Doppler shift dispersion of the particles in the exosphere. As a conclusion, a more energetic exosphere than simulated in Section 3 would not provide a much better fit of the observations. The observed Doppler shift is essentially suggesting an exosphere produced very early on the dayside and even on the nightside, as discussed in Potter et al. (2009), but seems not to be consistent with the spatial distribution of the observed Na emission.

5. Conclusion THEMIS solar telescope realized two sets of observation with high spectral resolution (370,000) at two positions of Mercury around the Sun. These two positions were opposite in terms of Mercury’s heliocentric Doppler, one being obtained at a true anomaly angle (TAA) of 316° (heliocentric Doppler of 6.99 km/s) and a second observation performed at a TAA of 96° (heliocentric Doppler of 9.99 km/s). In both observations, we were able to reconstruct the 2D spatial distribution of the D2 and D1 Na emission intensities, of its Doppler shift in Mercury’s frame and of its Doppler width. The measured Doppler shift is suggesting an exosphere moving towards the Earth everywhere in the observed exosphere, a motion even stronger at TAA = 96° than at TAA = 316°. The associated Doppler width is also larger at TAA = 96° than at TAA = 316°. Particular spatial distributions of the emission were observed, with two

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clear bright peaks in emission at TAA = 316° and a very bright limb at TAA = 96°. In these two cases, no clear correlated spatial distribution of the measured Doppler width and shift corresponding to the emission distribution could be identified. The energetic spatial structures do not suggest that these bright regions are produced by significantly more energetic processes than what produced the bulk of the exosphere. Solar wind sputtering which is suggested by the positions of the two peaks in emission observed during TAA = 316° observations either does not directly produce the observed exosphere but induces enhancement in Na diffusion in the Na surface as an example or is not significantly more energetic than other processes of ejection. In a second part, we present the results of the simulation of these two observations. Mercury Exosphere Global Circulation Model (MEGCM) is used to model the Na exosphere (Leblanc and Johnson, 2003, 2010; Leblanc and Doressoundiram, 2011), to reconstruct the velocity distribution of the Na atoms along each line-of-sight and to estimate the spatial distribution of the Doppler shift and width taking into account the exact configuration of the two observations and the seeing effect of the terrestrial atmosphere. Moreover, in order to take into account the small optical thickness and the non-maxwellian nature of the velocity distribution of the Na atoms in Mercury’s exosphere, a radiative transfer approach has been specifically developed. This model is described in a companion paper (Chaufray and Leblanc, 2012). The comparison between observation and simulation highlights several important discrepancies. First at all, the simulation was not tuned to specifically reproduce some of the observed features, in particular the two bright peaks observed at TAA = 316°. Despite that, the comparison between simulation and observation was relatively good. In both simulation and observation, we found similar Doppler width at TAA = 316°. As shown in Leblanc and Johnson (2003), in MEGCM, the velocity distribution of the ejecta typically peaks around 1 km/s with a half width of 1 km/s. Such a range is relatively close to the measured range of Doppler shift. Therefore, because of seeing, it is probable that the measured width of the velocity distribution along a line-of-sight is derived from a convolution of the dispersion of the particle velocity at ejection and the dispersion of the Doppler shift of the particles induced by the solar radiation pressure. In other words, the Doppler width cannot be interpreted simply as a measurement of the energetic state of the exosphere but needs also to be interpreted knowing the Doppler shift of the particles in Mercury’s Na exosphere, which strongly depends on the strength and nature of the solar radiation pressure. As a matter of fact, the comparison between the measured and simulated Doppler shift of the Na atoms is much less satisfying. We do reproduce the spatial variation of the Doppler shift at TAA = 316° but not in the case of TAA = 96°. In both cases, the simulated Doppler shift suggests an exosphere globally at rest with respect to Mercury in the field of view of the observation whereas the observed Doppler shift suggests an exosphere moving from early morning/nightside towards the dayside in contradiction with the expected effect of the solar pressure. We have no good explanation for the observations. An exosphere that would globally escape should be produced by much more energetic processes than simulated, inducing a significantly different spatial distribution of the emission and a significant larger Doppler width and therefore a discrepancy between Doppler shift and width. Spectral calibration could be another explanation. However, a comparison with

the only other data set of measured Doppler shift (Potter et al., 2009) suggests a relatively good agreement between our two observations. We are therefore left with a puzzling conclusion that could be only solved by new observations confirming or not the measured Doppler shift. Acknowledgments The data from THEMIS could not have been obtained without the great help of THEMIS staff and in particular without the help and support of C. Le Men and B. Gelly. References Anderson, B.J. et al., 2011. The global magnetic field of Mercury from MESSENGER orbital observations. Science 333, 1859–1862. Baumgardner, J., Wilson, J., Mendillo, M., 2008. Imaging the sources and full extent of the sodium tail of the planet Mercury. Geophys. Res. Lett. 35, L03201. Chaufray, J.Y., Leblanc, F., 2012. Radiative transfer of emission lines with nonMaxwellian velocity distribution function: Application to Mercury D2 sodium lines. Icarus, submitted for publication. Fulle, M. et al., 2007. Discovery of the atomic iron tail of comet McNaught by the Heliospheric imager on STEREO. Astrophys. J. 661, L93–L96. Killen, R.M., 2006. Curve-of-growth model for sodium D2 emission at Mercury. Publ. Astron. Soc. Pacific 118, 1344–1350. Killen, R.M., Potter, A.E., Fitzsimmons, A., Morgan, T.H., 1999. Sodium D2 line profiles: Clues to the temperature structure of Mercury’s exosphere. Planet. Space Sci. 47, 1449–1458. Killen et al., 2007. Processes that promote and deplete the exosphere of Mercury. Space Sci. Rev. 132, 433–509, 10.1007/s11214-007-9232-0. Leblanc, F., Doressoundiram, A., 2011. Mercury exosphere. II: The sodium/ potassium ratio. Icarus 211, 10–20. Leblanc, F., Johnson, R.E., 2003. Mercury’s sodium exosphere. Icarus 164, 261–281. Leblanc, F., Johnson, R.E., 2010. Mercury exosphere. I: Global circulation model of its sodium component. Icarus 209, 280–300. Leblanc, F. et al., 2007. Mercury’s exosphere: Origins and relations to its magnetosphere and surface. Planet. Space Sci. 55, 1069–1092. Leblanc, F. et al., 2008. High latitude peaks in Mercury’s sodium exosphere: Spectral signature using THEMIS solar telescope. Geophys. Res. Lett. 35, L18204. http:// dx.doi.org/10.1029/2008GL035322. Leblanc, F. et al., 2009. Short term variations of Mercury’s Na exosphere observed with very high spectral resolution. Geophys. Res. Lett. 36, L07201. http:// dx.doi.org/10.1029/2009GL038089. López Ariste, A., Rayrole, J., Semel, M., 2000. First results from THEMIS spectropolarimetric mode. Astron. Astrophys. 142, 137. Mouawad, N. et al., 2010. Constraints on Mercury’s Na exosphere: Combined MESSENGER and ground-based data. Icarus. http://dx.doi.org/10.1016/ j.icarus.2010.10.019. Potter, A.E., Morgan, T.H., 1987. Variation of sodium on Mercury with solar radiation pressure. Icarus 71, 472–477. Potter, A.E., Killen, R.M., Morgan, T.H., 2002. The sodium tail of Mercury. Meteorit. Planet. Sci. 37, 1165–1172. Potter, A.E., Killen, R.M., Sarantos, M., 2006. Spatial distribution of sodium on Mercury. Icarus 181, 1–12. Potter, A.E., Killen, R.M., Morgan, T.H., 2007. Solar radiation acceleration effects on Mercury sodium. Icarus 186, 571–580. Potter, A.E., Morgan, T.H., Killen, R.E., 2009. Solar winds on Mercury. Icarus 204, 355–367. Richer, E., Modolo, M., Chanteur, G., Hess, S., Leblanc, F., 2012. A global hybrid model for Mercury’s interaction with the solar wind: Case study of the dipole representation. J. Geophys. Res. – Space Phys., submitted for publication. Schleicher, H., Wiedemann, G., Wöhl, H., Berkefeld, T., Soltau, D., 2004. Detection of neutral sodium above Mercury during the transit on 2003 May 7. Astron. Astrophys. 425, 1119–1124. Smyth, W.H., 1986. Nature and variability of Mercury sodium atmosphere. Nature 323, 696–699. Sprague, A.L., Kozlowski, R.W.H., Hunten, D.M., Schneider, N.M., Domingue, D.L., Wells, W.K., Schmitt, W., Fink, U., 1997. Distribution and abundance of sodium in Mercury’s atmosphere, 1985–1988. Icarus 129, 506–527. Vervack Jr., R.J. et al., 2010. Mercury’s complex exosphere: Results from MESSENGER’s third flyby. Science 329, 672–675.

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