Deep-time reconstructions of Earth's surface environments and elevations

Abstract

Reconstructing Earth's ancient surface topography in deep geological time demands the synthesis of plate tectonic reconstructions, geodynamic simulations, paleoclimate modelling, and advanced computational methodologies. This thesis pioneers an integrated computational framework bridging geological observations with numerical models for paleotopographic reconstruction.

A novel deformable plate tectonic reconstruction is developed incorporating time-evolving deforming meshes within rift zones, applied to the Gulf of Mexico. Systematic optimisation across 32,400 mesh configurations reduced crustal-thickness RMSE from 14.8 km to 5.6 km against the GEMMA model. The resulting subsidence histories illuminate key depositional enigmas, including ~1.5 km of pre-drift subsidence during the Sinemurian (193–183 Ma), southward migration of red-bed deposition beneath Jurassic salt, and the westward deflection of Cenomanian–Turonian clastic systems.

Transitioning to active margins, the Python Deep Time Data Mining (pyDTDM) library is introduced within an Explainable AI (XAI) framework, integrating plate reconstructions, mantle convection simulations, and paleoclimate outputs. The XAI model identifies subduction flux as the dominant orogenic driver, with trench-advance episodes intensifying crustal thickening, while mantle temperature anomalies and long-term precipitation exert secondary but significant influences.

Leveraging these insights, a deep neural network reconstructs active-margin paleotopography at 1 Myr resolution throughout the Mesozoic and Cenozoic. Validated against geochemical paleoelevation proxies and regional studies, the model reveals the East Asian Cordillera exceeding 3 km during the mid-Cretaceous and reproduces established Andean uplift phases.

All workflows are disseminated as open-source tools under GPL/LGPL licences, with broader implications extending to mineral exploration, paleoclimate modelling, and biodiversity evolution studies.