This study presents a novel enhancement for Lagrangian particle transport modeling by integrating Coherent Structures theory. Lagrangian transport modeling is frequently utilized to forecast the trajectories of floating particles in the ocean despite the unstable nature of geophysical velocity fields that inevitably result in large trajectory errors. Current particle tracking methodologies often rely on deploying numerous particles and incorporating diffusion mechanisms into models to estimate particle probabilities across different locations. However, this approach can result in significant disparities in the final particle locations, thereby posing challenges in scenarios such as search and rescue operations and oil spill containment. To address these limitations, this study leverages dynamical systems and Eulerian Coherent Structures to improve particle tracking accuracy and diminish uncertainty.

The expected rise in major tropical cyclones due to climate change will increase their associated hazards, including ocean waves which are the main design parameter for maritime structures. To assess how climate change will affect tropical cyclone waves in the Gulf of Mexico we use physics-based synthetic tropical cyclones derived for present and future climates, overcoming the limitations imposed by insufficiently long records and inadequate resolution in General Circulation Models. Using events derived from six Coupled Model Intercomparison Project Phase 5 models, we estimate the probability of extreme waves for the present climate, and global warming under the Representative Concentration Pathway 8.5 scenario. The results show the importance of non-stationary wave climates for planning and design of maritime structures to reduce structure failure probability as we transit into a future climate with an increased probability of extreme waves.