Exploring Changes in Coastal Sea Level Distributions in Observations and Climate Models

Studies agree on a significant global mean sea level rise in the last century and its recent acceleration in the satellite record. At the regional scale, the evolution of sea level distributions is often assumed to be dominated by changes in the mean. However, a rigorous quantification of changes in distributional shapes and their significance is still lacking. To this end, we propose a unified statistical framework quantifying changes in individual quantiles and in the first four statistical moments from time series data. The framework proposed is general and can be applied to any climate observable with close-to-linear changes in distributions. We focus on both tide gauges data and climate model experiments performed with the state-of-the-art GFDL-CM4 model. The model is run under the historical scenario for comparison with tide gauges and under a 1% per year atmospheric CO2 (i.e., 1pctCO2) increase for 150 years up to quadrupling to investigate emergence of changes in distributions of sea level. Shifts in the sea level mean are evident in both observations and modelled outputs. However, changes in higher order moments (i.e., extremes) emerge mainly in the 1pctCO2 simulation. To explore the causality behind such changes, we further compare ocean-only and coupled ocean-atmosphere contributions to changes in sea level distributions. By focusing on model outputs we investigate the historical and future evolution of sea level distributions and quantify the relevant drivers behind such changes. Finally, we discuss the implications of the model's results for understanding possible drivers of sea level rise statistics in the real world.