Investigating stratification of lunar regolith through modeling of the ground based detection of the LCROSS debris plume light curve
Abstract
The Lunar CRater Observation and Sensing Satellite (LCROSS) mission impacted a Centaur second stage rocket into Cabeus crater, a permanently shadowed crater near the southern pole of the Moon. This impact produced a debris plume in which a shepherding spacecraft detected spectroscopic signs of water ice (Colaprete et al. 2010). Ground-based observations were also acquired in an international campaign to collect complementary data in support of the mission (Heldmann el al. 2012). A signal was detected in the V-band images from the Astrophysical Research Consortium 3.5 m telescope at Apache Point Observatory (APO) using a principal component analysis (Strycker et al. 2013). In order to match the observed plume light curve, Strycker et al. (2013) generated a series of ballistic plume models with a range of initial conditions with which they were able to identify constraints on the shape and mass of the plume. We present here a new analysis of the ground-based observations wherein we fit the modeled light curves to multiple datasets simultaneously. We have two new detections of the LCROSS plume taken with two cameras at the Magdalena Ridge Observatory (MRO) (Strycker et al. 2017). Both of the light curves were extracted using an improved principal component analysis that allows for higher signal to noise at finer spatial resolution. The original Strycker et al. (2013) models imposed strict constraints on the initial velocities of plume particles in order to match observations. Newer results (Lucey et al. 2014) instead support an albedo variation of the lunar regolith particles with depth, suggestive of a stratified ice content in permanently shadowed regions. We will fit our model to the data using this stratified lunar sediment. This model will therefore provide information about the distribution of water ice in permanently shadowed regions on the Moon. This work was supported by the Lunar Data Analysis Program through grant number NNX15AP92G. References: Colaprete, A. et al. (2010) Science, 330, 463-468. Heldmann, J. L. et al. (2012) SSRv, 167, 93-140. Lucey, P. G. et al. (2014) J. Geophys. Res. Planets, 119, 1665-1679. Strycker, P. D. et al. (2013) Nat. Commun., 4:2620. Strycker, P. D. et al. (2017) AAS DPS #49, 417.14.
- Publication:
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AAS/Division for Planetary Sciences Meeting Abstracts #50
- Pub Date:
- October 2018
- Bibcode:
- 2018DPS....5011602L