A noisy-input generalized additive model for relative sea-level change along the Atlantic coast of North America

Abstract

Abstract We propose a Bayesian, noisy-input, spatial–temporal generalized additive model to examine regional relative sea-level (RSL) changes over time. The model provides probabilistic estimates of component drivers of regional RSL change via the combination of a univariate spline capturing a common regional signal over time, random slopes and intercepts capturing site-specific (local), long-term linear trends and a spatial–temporal spline capturing residual, non-linear, local variations. Proxy and instrumental records of RSL and corresponding measurement errors inform the model and a noisy-input method accounts for proxy temporal uncertainties. Results highlight the decomposition of regional RSL changes over 3,000 years along North America’s Atlantic coast. The physical process glacial isostatic adjustment prevailed before 1800 CE, with anthropogenic forcing dominating after 1900 CE.