P23B-2135
Retrieving Atmospheric Dust Loading on Mars Using Engineering Cameras and MSL’s Mars Hand Lens Imager (MAHLI)

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Christopher A Wolfe, Texas A & M University College Station, College Station, TX, United States
Abstract:
Dust in the Martian atmosphere influences energy deposition, dynamics, and the viability of solar powered exploration vehicles. The Viking, Pathfinder, Spirit, Opportunity, Phoenix, and Curiosity landers and rovers each included the ability to image the Sun with a science camera equipped with a neutral density filter. Direct images of the Sun not only provide the ability to measure extinction by dust and ice in the atmosphere, but also provide a variety of constraints on the Martian dust and water cycles. These observations have been used to characterize dust storms, to provide ground truth sites for orbiter-based global measurements of dust loading, and to help monitor solar panel performance. In the cost-constrained environment of Mars exploration, future missions may omit such cameras, as the solar-powered InSight mission has. We seek to provide a robust capability of determining atmospheric opacity from sky images taken with cameras that have not been designed for solar imaging, such as the engineering cameras onboard Opportunity and the Mars Hand Lens Imager (MAHLI) on Curiosity. Our investigation focuses primarily on the accuracy of a method that determines optical depth values using scattering models that implement the ratio of sky radiance measurements at different elevation angles, but at the same scattering angle. Operational use requires the ability to retrieve optical depth on a timescale useful to mission planning, and with an accuracy and precision sufficient to support both mission planning and validating orbital measurements. We will present a simulation-based assessment of imaging strategies and their error budgets, as well as a validation based on the comparison of direct extinction measurements from archival Navcam, Hazcam, and MAHLI camera data.