My work focuses on understanding anthropogenic changes in precipitation and atmospheric circulation by employing climate models of varying levels of complexity. This thesis has two goals: (1) to understand the forced response of tropical air-sea interactions across time scales and their extratropical impact, and (2) to explore reasons underlying model uncertainties in simulating tropical and extratropical climate. My dissertation comprises four individual projects.

As seismology enters the era of big data, the exponential growth in data volume and processing needs surpasses the capacity of traditional seismic monitoring workflows. The recent success of machine learning applications across various scientific domains has made a paradigm shift in image processing and simple task automation. Within this context, this thesis portrays a modern earthquake monitoring workflow with deep learning integrated into different fronts.

Ground-level Ozone (O3­) and fine particulate matters (PM

Our understanding of the composition and uptake of zinc into Southern Ocean diatom frustules has been enhanced by X-ray fluorescence (XRF) microscopy and X-ray absorption spectroscopy (XAS). These findings potentially resolve decades of debate about the close correlation of zinc and silicate in the global ocean.