The physical drivers of water levels vary widely as one transitions from the shelf, to the shore, estuarine, and riverine environments. This makes water level modelling in these environments particularly daunting. However, because the time scales of many of these drivers are on the order of several days, they are relatively easily handled by data assimilation techniques. We have leveraged these traits to develop a very low-cost data assimilation framework for modeling of coastal ocean water levels that roughly halves errors on both a storm event time scale and on a much longer reanalysis time scale.
This talk will present our method and results for flooding from Hurricane Matthew (see paper, DOI: 10.1016/j.ocemod.2019.101483), as well as updated work on the system and a 40-year reanalysis that demonstrates the system aptly corrects for water level signals from days to decades.
Taylor Asher is a PhD student under Dr. Rick Luettich in the Department of Earth, Marine and Environmental Sciences at the University of North Carolina at Chapel Hill. Mr. Asher specializes in numerical modeling, analysis, and uncertainty quantification in coastal water levels, waves, and flooding. He has been involved in FEMA coastal flood hazard studies in nearly every state along the Gulf and Atlantic, including sea level rise pilot studies, and led several studies in Florida. He has also authored FEMA guidance documentation on how to best perform these studies.
Mr. Asher designed, constructed, and validated the last generation ADCIRC-based ESTOFS / HSOFS model used by NOAA for forecasting water levels associated with tides, extratropical, and tropical storms. He has an undergraduate degree in Spanish and undergraduate and master’s degrees in Ocean Engineering from the University of Rhode Island, specializing in wave mechanics and floating body interactions.
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