AN INDEX OF SUBSURFACE VOLATILES ON MARS. Eriita Jones Jones, E. (2015) Identifying an index of subsurface volatiles on Mars through an analysis of impact crater morphometry using principal component analysis. J. Geophys. Res. 120, 2084-2101.

Introduction SLE % SLE Attributes Locations A number of morphological and group craters morphometric attributes of Martian Group 1 41 High impactor energy (PC1); Volcanic provinces (Elysium, layered ejecta (LE) craters may provide low volatiles (PC2). Hesperia, Olympus Mons) or information on the presence and abundance of subsurface ice, allowing in areas of catastrophic fluvial these craters to be probes of the location, release (e.g. circum-Chryse depth and abundance of subsurface Planitia). volatiles throughout Martian history e.g. Group 2 14 Low impactor energy (PC1); Northern mid-latitudes north [1-3]. In this study of over 10,000 high target volatiles (PC2); low of the dichotomy. Martian SLE and DLE craters analyzed impactor angle (PC3); high via principal component analysis (PCA), resurfacing / young terrain a number of significant principal components were identified and (PC4). interpreted. PCA revealed the existence Group 3 8 Very high impactor energy Mid-latitude Noachian and of four significant principal components (PC1); very high target Hesperian terrains such as for single-layered ejecta craters, and five volatiles (PC2). Solis Planum, Arabia Terra, for double-layered ejecta craters (see Terra Sabeae and Hesperian Table 1). These components were Planum. interpreted as indices of impactor energy, Group 4 12 Very high impactor angle Similar to group 1, and some target volatiles, impactor angle, resurfacing/ surface age, and impact (PC4); high resurfacing/young parts of southern mid- preservation/ freshness. When terrain (PC4). latitudes. transformed into the principal Group 5 25 Low impactor energy (PC1); Southern mid- to high- component dimensions, a statistical high target volatiles (PC2); low latitudes and northern Arabia grouping analysis revealed a number of resurfacing/old terrain (PC4). Terra. significant clusters of SLE and DLE craters (Table 2a and 2b). Using the target volatiles index, in conjunction with Significant % of explained variation Interpretation resurfacing or crater preservation indices, Principal in crater sample DLE % Attributes Locations the spatial distribution of potential Components SLE DLE group DLE subsurface volatiles, both past and PC1 29 41 Impactor energy craters geologically recent, can be mapped PC2 23 17 Target volatiles Group 1 33 Low impactor energy (PC1); high volatiles Same as SLE (Figure 1). PC3 12 9 Impactor angle (PC2); high resurfacing/young terrain (PC4). Group 2 PC4 9 7 Regional resurfacing /geologic age Group 2 31 High impactor energy (PC1); low target Same as SLE PC5 N/A 6 Crater preservation/freshness volatiles (PC2); low impactor angle (PC3). Group 1 Total 73% 80% Group 3 15 Very high impactor energy (PC1); high target Same as SLE Datasets volatiles (PC2); low preservation/freshness Group 3 • The data for this study were primarily extracted from Robbins & Hynek’s (PC5). crater database [4]. Group 4 21 High impactor angle (PC3); low Same as SLE • Analysis variables consisted of crater and resurfacing/old terrain (PC4); high Group 5 ejecta dimensions, a number of indices preservation/freshness (PC5). (such as crater degradation, ejecta mobility, and lobateness) calculated from the primary measurements, plus several additional parameters related to surface age and crater preservation.

What can you use these components for? • Identify regions of volatiles, and the relative ice-table depth, volatile abundance, and relative age. • Effectively determine relative crater ages and preservation states. • Provide morphologic evidence for ice-table models from ancient climate scenarios. • Compare the surface modification rates between regions. • Analyse the relationship between geologically recent ice and present-day thermophysical properties of the surface. • Easily identify elliptical craters. • Elucidate the differences between the SLE and DLE crater populations and their relationship to target characteristics.

Eriita Jones, PhD Astrophysics Postdoctoral Researcher, Division of IT, Engineering and the Environment, University of South Australia Email: [email protected] Research interests: Thermophysical modelling; multivariate statistical analysis of planetary datasets; liquid water and habitability of planetary References [1] Kuzmin, R.O., 1980. Morphology of fresh martian impact craters as an indicator of the depth of the upper boundary of the ice-bearing permafrost: a environments. photogeologic study. Lunar Planet. Sci. Conf. 11, 585–586. Interested in collaborating? Please contact me. [2] Mouginis-Mark, P., 1981. Ejecta emplacement and modes of formation of martian fluidized ejecta craters. Icarus 45, 60–76. [3] Barlow, N.G., 2004. Martian subsurface volatile concentrations as a function of time: Clues from layered ejecta craters. Geophys. Res. Lett. 31, L05703. Want GIS-ready products from this research? I’m [4] Robbins, S.J., Hynek, B.M., 2012a. A new global database of Mars impact craters ≥1 km: 1. Database creation, properties, and parameters. J. Geophys. Res. happy to share. 117, 1–18.