High-resolution spatiotemporal solar irradiance mapping on Mars through coupled terrain-atmosphere modeling

Abstract Accurate modeling of solar irradiance on Mars is essential for future exploration missions, including landing site selection, rover energy optimization, and habitat planning. Existing models, however, often rely on broad meteorological approximations and neglect the complex interplay between atmospheric scattering, terrain occlusion, and solar geometry, particularly in areas with complex topography. This paper introduces a novel, high-resolution solar irradiance modeling method that integrates detailed terrain and atmospheric data, constructing high-fidelity horizon profiles and calculate full radiative transfer to accurately model both direct and diffuse solar radiation components. This approach not only enhances the accuracy of solar irradiance simulations on the Martian surface but also generates high-precision spatiotemporal irradiance maps, enabling detailed illumination analysis over localized areas, along specific trajectories, or across extended timeframes. The model was rigorously validated using 30 sols of data (sols 35-64) from the Mars Environmental Dynamics Analyzer aboard the Perseverance rover, achieving a root mean square error (RMSE) of 6.57 W m −2 and a mean absolute percentage error (MAPE) of 4.07%. Notably, in areas with significant terrain variation during periods of low solar elevation, the model reduced the MAPE by up to 6.7% and decreased the RMSE by up to 9.7 W m −2 compared to atmosphere-only models, demonstrating a substantial improvement in accuracy. Furthermore, the model accurately predicted abrupt irradiance changes due to terrain-induced solar obstruction, a phenomenon not captured by traditional methods. These results underscore the model’s significance in providing critical, location-specific irradiance data and demonstrate its potential to inform optimal path planning for rovers, site selection for future habitats, and a deeper understanding of the Martian environment.