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Title: Modeling sea level processes on the US Atlantic coast Authors:  Candace Berrett - Brigham Young University (United States) [presenting]
William Christensen - Brigham Young University (United States)
Steve Sain - Jupiter Intelligence (United States)
Nathan Sandholtz - Simon Fraser University (United States)
Davod Coats - Northrup Grumman Corporation (United States)
Claudia Tebaldi - Climate Central (United States)
Hedibert Lopes - INSPER (Brazil)
Abstract: One of the major concerns engendered by a warming climate are changing sea levels and their lasting effects on coastal populations, infrastructures, and natural habitats. Sea levels are now monitored by satellites, but long term records are only available at discrete locations along the coasts. Sea levels and sea level processes must be better understood at the local level to best inform real-world adaptation decisions. We propose a statistical model that facilitates the inclusion of known sea level processes, such as sea level rise and seasonal cycles, and also accurately accounts for residual spatio-temporal processes, all together governing sea level behavior along the coast. By combining a spatially-varying coefficient modeling approach with spatio-temporal factor analysis methods in a Bayesian framework, the method represents the contribution of each of these processes and accounts for corresponding dependencies and uncertainties in a coherent way. Additionally, the model provides a consistent way to estimate these processes and sea level values at unmonitored locations along the coast. We show the outcome of the proposed model using thirty years of sea level data from thirty-eight stations along the Atlantic (east) coast of the United States. Among other results, our method estimates the rate of sea level rise to range from roughly 1 mm/year in the northern and southern regions of the coast to 5.4 mm/year in the middle region.