This research develops a machine-learning and data-assimilation framework that combines idealized and operational Earth systems models into a high-resolution, physically realistic “bridging model.” Applied to the El Niño–Southern Oscillation, the approach improves climate simulation accuracy while enabling exploration of alternative climate regimes and physically consistent what-if scenarios.

This research investigates earthquake risks associated with underground carbon dioxide storage. By studying seismic activity at the Decatur CO2 storage project, the work improves predictive geological models that account for hidden subsurface structures. The findings aim to make large-scale carbon storage safer, protecting both the climate and nearby communities.

Subduction zones generate earthquakes, tsunamis, and volcanoes, yet their behavior varies between regions. This research investigates how water released from subducting plates interacts with surrounding rocks. Using supercomputer simulations, it models hydration-driven cracking and fluid migration, revealing patterns that may influence where earthquakes and volcanic activity occur.

Using cake as an analogy, this research explains how buried sandstones can store naturally heated water for geothermal energy. By studying rock outcrops, cores, and microscopic structures, the work assesses sandstone quality to unlock reliable, renewable heat for buildings—available year-round as a low-carbon energy source.