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June 3, 2026Monthly Notices of the Royal Astronomical Society0 citationsOpen Access

A Comprehensive Three Dimensional Thermophysical Model for Mars

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KRK Samadhanam RajuKPK Durga PrasadGAG Ambily

Key Points

  • The aim is to enhance understanding of Martian surface temperatures and thermal properties through a 3D model.
  • Developed a 3D thermophysical model using finite element method.
  • Integrated high-resolution Digital Terrain Models (DTMs) to account for surface variations.
  • Validated model against KRC simulations and in-situ data from InSight lander.
  • 3D simulations show significant spatial temperature variations, contrary to 1D models.
  • Mean diurnal trends from 3D align with earlier 1D findings, but with more detail.
  • Model provides critical insights for rover-scale data interpretation and mission planning.

Abstract

Abstract Characterizing Martian surface temperatures and near-surface thermal behavior is essential for interpreting regolith thermophysical properties, surface–atmosphere interactions, and supporting mission operations. Traditional studies primarily utilize one-dimensional (1D) models, such as the widely adopted KRC framework, which assume strictly vertical heat transfer and laterally uniform terrain. While these models capture average diurnal trends, they neglect lateral heat transport, slope-dependent solar forcing, and realistic terrain-induced thermal variability. In this study, we present a comprehensive three-dimensional (3D) thermophysical model developed using the finite element method. By integrating high-resolution Digital Terrain Models (DTMs), the model explicitly accounts for surface slopes, roughness, and terrain-controlled solar illumination. We validated the model against KRC simulations under identical conditions and in-situ ground truth data from the InSight lander. To demonstrate its utility, the model was applied to a topographically complex sub-region within Jezero Crater at the Perseverance landing site. Our results show that while 3D simulations align with 1D mean diurnal trends, they resolve significant spatial temperature heterogeneities that 1D approaches fail to capture. This framework provides a more accurate representation of local thermal processes, offering critical applications for rover-scale data interpretation, landing site selection, future mission planning and science.

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Cite This Study

Raju et al. (2026) studied this question.

synapsesocial.com/papers/6a1fc58bdee9eb8c0dce6ee3https://doi.org/10.1093/mnras/stag932
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