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Published May 1, 2020 | Supplemental Material
Journal Article Open

Quantitative assessment of uncertainties in modeled crater retention ages on Mars

Abstract

With increasing high-resolution coverage of Mars' surface, crater count analysis is being used to estimate the formative ages of small depositional features (<1000 km²) to constrain timing of climate-driven events. We introduce a probabilistic cratering model that quantifies how modeled age estimates vary strongly with crater obliteration rates (β, defined as the combined rate of erosion and infilling), minimum crater diameter counted, and surface area size. Model results show that crater obliteration introduces significant uncertainty on small surfaces, where moderate obliteration rates (β ~ 25 nm a⁻¹) require surface areas of about 10,000 km² to date 2 to 3 Ga surfaces accurately, and strongly obliterated surfaces (β = 200 nm a⁻¹) require surface areas up to 100,000 km². In practice, smaller areas can nonetheless be analyzed probabilistically by estimating a range of likely obliteration rate and modeled age combinations and optimizing these values relative to observed crater count data, resulting in a distribution of possible modeled surface ages and associated β. We demonstrate this method using data from the Coprates Chasma landslide (~200 km²) and numerous fan and delta deposits in the Gale crater region. Although the deposits in and around Gale are <1000 km², a probabilistic analysis enables us to suggest that deltaic deposits in and near Gale have a higher probability of being older (~>3 Ga) than nearby fans (~1–3 Ga). This analysis provides a simple quantitative framework for assigning probable surface age ranges for small features on Mars.

Additional Information

© 2020 Elsevier Inc. Received 1 April 2019, Revised 18 December 20 19, Accepted 6 January 2020, Available online 18 January 2020. This research was conducted for the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA under the Mars Program Office. We would like to thank Kevin Lewis and Dawn Sumner for insightful discussions along the way, Brenhin Keller for converting the matlab scripts to an open source format (Julia), as well as the teams responsible for the orbital data, namely the HIRISE and CTX teams. We thank our reviewer, Stuart Robbins, for his time, thoughtfulness, and continued willingness to help improve this manuscript.

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Additional details

Created:
August 19, 2023
Modified:
October 19, 2023