In all real systems, there are limits of predictability on what we know and how precisely we know it. Repeating laboratory experiments can reduce some of these uncertainties, but many systems (like hurricanes and evacuations) cannot be recreated in the lab. Worldwide, coastal flooding is one of the most devastating natural disasters, having nearly killed a million people and cost a trillion dollars in the past 50 years. Its study traverses a broad swath of domains in engineering and science, from structural engineering and public planning to mesoscale atmospheric/oceanic thermodynamics and turbulent sediment transport. In this talk, I will present on the nature of this system and the uncertainties therein, with a focus on work I and others have done to reduce these uncertainties. For the latter, focus will be on coastal waves and water levels, both in isolation and in the context of the broader problem.

Taylor Asher has an undergraduate degree in Spanish, undergraduate degree and master's degree in Ocean Engineering with a focus on wave mechanics, and a Ph.D. in Marine Sciences with a focus on physical and statistical processes in coastal flooding. He has worked for private, public, and academic sectors on a range of flooding problems, including NOAA water level forecasting and FEMA flood hazard analysis. He is currently a postdoc for NOAA developing new ideas and methods for predicting coastal water levels over sub-seasonal to interannual time scales via both observational and model data. He is also engaged in several other research studies, including artificial intelligence-based probabilistic surge forecasting, stochastics in tropical cyclone meteorology with climate change, and data assimilation methods for water level climatologies.

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