GSA Connects 2021 in Portland, Oregon

Paper No. 108-9
Presentation Time: 3:45 PM


HAYNE, Paul1, EDWARDS, Christopher2, GREENHAGEN, Benjamin T.3, KLIMA, Rachel3, PAIGE, David A.4, POSTON, Michael J.5, WILLIAMS, Jean-Pierre6 and WU, Yunzhao7, (1)Laboratory for Atmospheric and Space Physics, University of Colorado Boulder, 3665 Discovery Dr, Boulder, CO 80303-7819, (2)Astronomy and Planetary Science, Northern Arizona University, NAU BOX 6010, Flagstaff, AZ 86011, (3)Johns Hopkins University Applied Physics Laboratory, 11101 Johns Hopkins Rd, Laurel, MD 20723, (4)Department of Geosciences, Stony Brook University, Stony Brook, NY 11794, (5)Southwest Research Institute, San Antonio, TX 78238, (6)Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles, Los Angeles, CA 90095, (7)Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, China

Thermal infrared emission measurements provide valuable information on a wide range of compositional and thermophysical properties of planetary surfaces. Typically, infrared brightness is measured in one or more spectral bands to derive surface temperature and spectral emissivity. However, unresolved surface roughness across a range of spatial scales can lead to pronounced variations in temperature that make interpreting IR measurements ambiguous (Bandfield et al., 2015). Even in the near-IR, roughness complicates the interpretation of spectra: the region from ~2.3 to 3.5 µm wavelength is particularly problematic, requiring deconvolution of combined reflected solar and emitted IR radiation (Bandfield et al., 2018). Correcting solar reflectance spectra for this thermal emission has become one of the primary challenges in remotely measuring the hydration state and abundance of water of the Moon’s surface (e.g., Li and Milliken, 2016). In this presentation, we will review current understanding of how roughness on airless planetary bodies leads to anisothermality, and how this affects interpretation of thermal- and near-IR spectra. We will present new results expanding upon the model developed by Bandfield et al. (2015), with further constraints from the Diviner instrument on NASA’s Lunar Reconnaissance Orbiter, and the short-wave IR instrument on the Chinese Space Agency’s Chang’E-4 lunar rover (Wu et al., 2021). Finally, we will discuss implications and approaches to incorporating roughness into future models in order to improve retrieval of surface composition (particularly H2O content) and thermophysical properties of airless planetary bodies.


Bandfield, J. L., Hayne, P. O., Williams, J. P., Greenhagen, B. T., & Paige, D. A. (2015), Lunar surface roughness derived from LRO Diviner Radiometer observations, Icarus, 248, 357-372.

Bandfield, J. L., Poston, M. J., Klima, R. L., & Edwards, C. S. (2018), Widespread distribution of OH/H2O on the lunar surface inferred from spectral data, Nature geoscience, 11(3), 173-177.

Li, S., & Milliken, R. E. (2016). An empirical thermal correction model for Moon Mineralogy Mapper data constrained by laboratory spectra and Diviner temperatures. Journal of Geophysical Research: Planets, 121(10), 2081-2107.

Wu, Y., Kührt, E., Grott, M., Jin, Q., Xu, T., Helbert, J., ... & Hayne, P. (2021). Chang’E‐4 Rover Spectra Revealing Micro‐scale Surface Thermophysical Properties of the Moon. Geophysical Research Letters, 48(4), e2020GL089226.