Issue |
A&A
Volume 674, June 2023
|
|
---|---|---|
Article Number | A69 | |
Number of page(s) | 31 | |
Section | Planets and planetary systems | |
DOI | https://doi.org/10.1051/0004-6361/202245343 | |
Published online | 06 June 2023 |
An advanced thermal roughness model for airless planetary bodies
Implications for global variations of lunar hydration and mineralogical mapping of Mercury with the MERTIS spectrometer★
1
Image Analysis Group, TU Dortmund University,
Otto-Hahn-Str. 4,
44227
Dortmund, Germany
e-mail: kay.wohlfarth@tu-dortmund.de
2
Institute for Planetology,
Wilhelm-Klemm-Str. 10,
48149
Münster, Germany
3
Institute for Planetary Research, DLR,
Rutherfordstr. 2,
12489
Berlin, Germany
Received:
31
October
2022
Accepted:
22
March
2023
We present a combined reflectance and thermal radiance model for airless planetary bodies. The Hapke model provides the reflected component. The developed thermal model is the first to consistently use rough fractal surfaces, self-scattering, self-heating, and disk-resolved bolometric albedo for entire planets. We validated the model with disk-resolved lunar measurements acquired by the Chinese weather satellite Gaofen-4 at around 3.5–4.1 μm and measurements of the Diviner lunar radiometer at 8.25 μm and 25–41 μm, finding nearly exact agreement. Further, we reprocessed the thermal correction of the global lunar reflectance maps obtained by the Moon Mineralogy Mapper M3 and employed the new model to correct excess thermal radiance. The results confirm the diurnal, latitudinal, and compositional variations of lunar hydration reported in previous and recent studies with other instruments. Further, we compared the model to lunar measurements obtained by the Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) on board BepiColombo during a flyby maneuver on April 9, 2020: the measured and the modeled radiance variations across the disk match. Finally, we adapted the thermal model to Mercury for emissivity calibration of upcoming Mercury flyby measurements and in-orbit operation. Although a physical parameter must be invariant under various observation scenarios, the best lunar surface roughness fits vary between different datasets. We critically discuss possible reasons and conclude that anisotropic emissivity modeling has room for improvement and requires attention in future studies.
Key words: Moon / infrared: planetary systems / radiation mechanisms: thermal / methods: data analysis / methods: numerical / planets and satellites: surfaces
Datasets and modeling results are available under https://doi.org/10.5281/zenodo.7776031
© The Authors 2023
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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