Study of Seasonal Variations in Thermophysical Characteristics of Gale Crater, Mars

Thesis Summary:

Surface energy budget and thermal inertia are two major thermophysical parameters that play an important role in understanding the thermal behaviour and habitability of a planet. The estimation of surface energy balance is important to study the energy exchange processes and boundary layer dynamics of any planetary body since radiative transfer processes play a significant role in regulating the near surface thermal weather on the planet. For planetary surface materials, thermal inertia is the key property controlling the diurnal and seasonal surface temperature variations and is typically dependent on the physical properties of near-surface geologic materials. Thermal inertia, on the other hand, determines the capability of the surface to store heat.
The surface energy budget and radiative transfer of Mars is primarily dependent on the characteristics of the Martian atmosphere, which change with the change in season of the Martian year. A study of its seasonal variation would enable a greater understanding of the thermal environment in each season on Mars. Many scientists and researchers have developed various methods and numerical models to partially compute energy budgets using various orbiter thermal infrared data. With the advancement of space technology and the landing of rovers on the Martian surface, work in the direction of understanding the thermal environment of Mars has substantially increased.

Here, the best methods for efficient calculation of each surface energy budget component have been assimilated and an attempt is made to enhance computational accuracy using in situ rover observational data from MSL Curiosity across twelve sols for four locations near the Gale crater. The amount of flux stored by the ground for conduction is thereby estimated from the equilibrium of surface energy transfer, which otherwise is difficult to compute directly. Ground heat flux is also computed by solving the one-dimensional heat conduction equation with inputs from Curiosity GTS measurements and compared with the former value to estimate thermal inertia. Thermal inertia is also calculated by running a thermal model on THEMIS thermal infrared night-time imagery and compared with the rover derived thermal inertia.

Observations reveal that the nature of variations are similar to that of Earth, except for the magnitudes of surface forcing. However, spring and autumn tend to be the seasons experiencing extreme weather conditions unlike the case with our planet. Thermal inertia from Curiosity inputs was calculated by incorporating the effects of diurnal variation of atmospheric dust opacity and wind turbulence with an uncertainty of around 8.85%. THEMIS thermal inertia was also calculated within an error of less than 20%.
However, it was also observed that thermal inertia is not constant for a particular surface with respect to time, as thought of previously. A plot of the thermal inertia at different solar longitudes at the four locations showed a sinusoidal variation of thermal inertia peaking at Ls = 95° to 100° and dipping at around Ls = 250° to 270°, roughly near the perihelion of the Martian year.
The thermal inertia generated was used to derive particle sizes to enable surface characterization of the study area using an empirical equation developed by Presley (2002). The thermal inertia ranges for different particle sizes based on USGS soil classification system at an average atmospheric pressure of 6 torr and average volumetric heat capacity of 1.3x106 J m-3 K-1 were calculated and the THEMIS derived thermal inertia images were reclassified based on the ranges obtained. It was seen that the surface is covered by dust and fine sand owing to deposition during the dust seasons which gradually reduces as the global wide dust storms recede.

This study provides a rough idea of the thermal behaviour of each season on Mars and aims to help future Mars missions in efficient mission scheduling and rover design. This study could also be enhanced by using multi-dimensional thermal models and accounting for sub-surface layering of the ground so that thermal inertia can be estimated more precisely and accurately.