Global thermophysical characterization of Mercury’s diurnal temperature cycle in support of BepiColombo SIMBIO-SYS

Mercury undergoes the largest diurnal temperature variations in the Solar System, with surface temperatures oscillating from below 100 K at night to above 700 K at local noon. These extreme cycles, driven by the planet’s 3:2 spin–orbit resonance and strong solar irradiance, have profound implications for regolith evolution, surface modification processes, and the interpretation of remote-sensing data. In preparation for the BepiColombo SIMBIO-SYS observations, we developed a global thermophysical model of Mercury that solves the diurnal and seasonal evolution of surface and near-subsurface temperatures using a one-dimensional heat-conduction scheme coupled with MESSENGER topography. From these simulations, we derived planet-wide maps of maximum surface temperature $$T_{\max }$$ , diurnal temperature amplitude $$\Delta T$$ , longitudinal gradients of $$\Delta T$$ , and a thermal stress index $$S_{\text{therm}} = \Delta T / t_{\text{day}}$$ that quantifies the mean rate of temperature cycling over one Hermean solar day. The resulting products reproduce the characteristic two-lobed thermal structure imposed by the spin–orbit resonance, with peak $$T_{\max }$$ and $$\Delta T$$ at the hot longitudes and a smooth decrease toward the poles, and identify belts of enhanced horizontal thermal gradients. Building on these global fields, we further quantify how local surface morphology modulates the thermal environment by correlating $$T_{\max }$$ with slope, roughness, hillshade, and aspect derived from the global Mercury Digital Elevation Model. Pixel-by-pixel Pearson coefficients and a multiple linear regression show that these morphological parameters together explain only $$\sim$$ 4% of the spatial variance in $$T_{\max }$$ , indicating that latitude and insolation geometry overwhelmingly dominate the diurnal thermal regime, while local relief and roughness provide only a weak, second-order modulation. The thermophysical maps and tools presented here provide a quantitative framework for the scientific exploitation of SIMBIO-SYS data, supporting observation planning and the interpretation of future high-resolution imaging and spectroscopic datasets.