Presentation on theme: "Mercury’s Seasonal Na Exosphere Tim Cassidy, Aimee Merkel, Bill McClintock and the MASCS team."— Presentation transcript:
Mercury’s Seasonal Na Exosphere Tim Cassidy, Aimee Merkel, Bill McClintock and the MASCS team
Literature on Na exosphere, pre-MESSENGER: That there is a dawn/dusk asymmetry, with more Na at dawn Na brightness peaks at the poles and is rapidly variable there, and that this is due to rapidly variable ion flux there Sometimes the brightness peaks near the subsolar point A mix of processes supply the exosphere: sputtering, impact vaporization, thermal desorption In contrast to the rapid variability seen by most, models focus on seasonality Potter and Morgan, 1990 Smyth and Marconi, 1995
Messenger limb scan vs. Earth-based Na observations Messenger UVVS data is especially valuable because it gives high resolution vertical profiles (‘limb scans’) of the atmosphere Potter and Morgan, 1990 Killen et al., 2008
column density or radiance Altitude For Na, we will focus on near-surface (<1000 km) limb scans Of particular interest is the slope of the limb scan—which tells us the energy of ejected Na Gravity acts as an energy spectrometer. hot cold What is a limb scan and why is it useful? lines of sight
Limbscan examples They are seasonal For a given local time and true anomaly (time of year) we see the same thing every Mercury year.
Possible conclusions from the repeatability Episodic processes (ion flux, impacts) do not directly control the exosphere (though we know these processes are operating on the surface and liberating Na) There is no direct connection between surface properties and the exosphere (Killen et al., 2001). (though we know the Na must come from the surface) Instead, it seems that transport processes control the exosphere (see work by Potter et al., Leblanc et al.) Even the upper (hot) exosphere is seasonal Conclusions we can reach by casual inspection of the limbscans: The exosphere has two temperature components (Vervack et al., 2010)
To explore the exosphere’s basic properties and behaviors, I fit these limbscans with Chamberlain models, which give approximate temperature and surface density Noon DawnSouth Pole Fits are based on this part of the exosphere (see extra slides for notes on model and conversion between column density and g values: this conversion is approximate)
The South polar scans are a little unusual: We don’t get comparable data at the North pole
Temperature Dayside temperatures: a consistent 1200 ± 100 K Dawn, dusk, South Pole (not shown): 1500 ± 100 K Note: this does not include the high altitude, high-T component, but does include the majority of the exosphere
We can compare temperature with possible ejection mechanisms Thermal Desorption <700 K (and thermal accommodation) PSD Photon Stimulated Desorption similar to ESD, electron stimulated desorption Meteorite Impact Vaporization 1000s degrees Sputtering thousands to 10s of thousands of degrees Molecular dissociation (e.g. CaX Ca + X + energy) 10s of thousands of degrees Experimental Data (Yakshinskiy and Madey, 1999 & 2004) 900 K Maxwellian PSD from ice Johnson et al., (2002) Conclusion: PSD is the best match to supply the near-surface exosphere temperature The temperatures we derive are similar to, but slightly colder, than Earth-based observations (Killen et al., 1999) There is no evidence of thermal desorption
But PSD would quickly deplete surface of Na, Na must be continually resupplied to surface by other processes such as impacts or ion-enhanced diffusion (e.g., Killen et al., 1989).
Is there any evidence of such a thermal component? That is, Na near Mercury’s surface temperature (<700 K). Could a small thermal component be hidden down near the surface? 1200 K Chamberlain model Models often include thermal desorption and/or accommodation
600 K ~1200 K 1200 K + 600 K Here’s what the data would look like with a surface-temperature component: The vertical column of the 600 K component was set equal to the 1200 K components
Dawn & dusk We see a dawn/dusk asymmetry, but only during part of the year.
Dawn & dusk : comparing with ground-based transit observations Schleicher et al. (2004) Dawn/dusk asymmetry Potter et al. (2013) No dawn/dusk asymmetry
Dayside Example: 10:00 local time, different Mercury years indicated
Dayside All local times Peak seems to move in local time, first it peaks in the morning, then noon, then afternoon FIPS peak here?
Dayside and dawn/dusk comparison Dawn/dusk peak when dayside is at a minimum: this suggests that photon pressure is driving Na toward the terminator
South pole behavior, when we see it, is similar to dawn and dusk.
“Radiation pressure will only redistribute sodium from the subsolar point to the terminator (see Fig. 1)…the sodium zenith column density is the same everywhere along a small circle of constant solar zenith angle“ -Killen et al., 1990, on the effects of radiation pressure transport The South pole, when we see it, looks like just another terminator. Is this a result of radiation transport?
Summary Exosphere is seasonal, we see the same data Mercury year after Mercury. Need to reconcile this with ground-based observations, which see variability at the 2x level This means that geology and magnetosphere don’t affect magnetosphere in a prompt way Dayside peaks when g values are low, dawn peaks with g values are high—suggests a transport mechanism South pole is similar to dawn and dusk
Extra slides *relating g value and column density *Chamberlain models with photon pressure
Since the gas isn’t actually at rest wrt Mercury, what is the actual g value? We need to convolve the g value-radial velocity function with the actual speed distribution. Schleicher et al., Potter et al., and Leblanc et al. (2009) found that the Na absorption had a range of wavelengths due to Doppler shift. They modeled the dispersion with Gaussians. exp[-(λ-λ o ) 2 /2σ 2 ] Which is converted to line-of-sight speeds via Doppler shift: exp[-(v-v 0 ) 2 /2σ 2 ] where v 0 is relatively to Mercury’s rest frame. Column density/g value relationship Schleicher et al., 2004 σ (km/s) v 0 (km/s) Schleicher et al. (2004): 1.1 0 Potter et al.: 0.5 ± 0.2 0.8±0.25 (Potter et al. linewidths similar to Killen et al., 1999) Leblanc et al. (2009): 0.9-1.4 0.9-1.1 Note: the definition of ‘linewidth’ varies between these papers, making it difficult to compare them. Sometimes that factor of 2 is in the Gaussian definition, sometimes not. For the Potter paper, at least, I spoke with the authors about these details. Leblanc and Schleicher are more explicit about their definitions, but Schleicher makes a mistake in referring to the quantity sqrt(2)*sigma as the RMS, whereas sigma, as defined here, is the RMS of a Gaussian.
To see what effect this would have on the g values I convolved the g values with a Gaussian moving Earthward. Here is the example using Schleicher’s relatively large dispersion (~3000 K) and including an offset of 1 km/s as in Potter and Leblanc. But we know it can’t be a perfect Gaussian, how does that change things?
So if it’s not a perfect Gaussian… Here I’ve multiplied by random numbers, it doesn’t change the result significantly. The atmosphere is not a perfect Gaussian of course, but that’s a distinction without a difference. Whatever its exact shape, the measured dispersion is relatively small, and a small dispersion means little effect on the g values. Warp that speed distribution however you like, as long as the dispersion is small the convolution won’t change much.
Chamberlain model: density ~ n 0 e -U/kT where U is the potential energy (times another factor called zeta…) Radiation acceleration term, analogous to U = -mgh Gravitational potential sunlight To get atmospheric properties we have fitted limb scans with a simple function, called a Chamberlain model. Chamberlain model fits give us two parameters: surface density and temperature Note: Radiation acceleration is up to ½ Mercury’s gravity