Details

Autor(en) / Beteiligte

• Davidsson, Björn J.R.
• Rickman, Hans
• Bandfield, Joshua L.
• Groussin, Olivier
• Gutiérrez, Pedro J.
• Wilska, Magdalena
• Capria, Maria Teresa
• Emery, Joshua P.
• Helbert, Jörn
• Jorda, Laurent
• Maturilli, Alessandro
• Mueller, Thomas G.

Titel

Interpretation of thermal emission. I. The effect of roughness for spatially resolved atmosphereless bodies

Ist Teil von

• Icarus (New York, N.Y. 1962), 2015-05, Vol.252, p.1-21

Ort / Verlag

Elsevier Inc

Erscheinungsjahr

2015

Quelle

ScienceDirect Pay Per View(PPV) Titles

Beschreibungen/Notizen

• •Directional thermal emission is calculated for different models of surface roughness.•We find that thermal emission depends on roughness type.•Consequences for determining roughness and thermal inertia are discussed.•Advice is given for observational strategies during spacecraft missions. Spacecraft observations of atmosphereless Solar System bodies, combined with thermophysical modeling, provide important information about the thermal inertia and degree of surface roughness of these bodies. The thermophysical models rely on various methods of generating topography, the most common being the concave spherical segment. We here compare the properties of thermal emission for a number of different topographies – concave spherical segments, random Gaussians, fractals and parallel sinusoidal trenches – for various illumination and viewing geometries, degrees of surface roughness and wavelengths. We find that the thermal emission is strongly dependent on roughness type, even when the degrees of roughness are identical, for certain illumination and viewing geometries. The systematic usage of any single topography model may therefore bias determinations of thermal inertia and level of roughness. We outline strategies that may be employed during spacecraft observations to disentangle thermal inertia, level of roughness and type of topography. We also compare the numerically complex and time consuming full-scale thermophysical models with a simplified statistical approach, which is fairly easy to implement and quick to run. We conclude that the simplified statistical approach is similar to thermophysical models for cases tested here, which enables the user to analyze huge amounts of spectral data at a low numerical cost.