Long-term climate change impacts on regional sterodynamic sea level statistics analyzed from the MPI-ESM large ensemble simulation

Abstract

Abstract Statistics of regional sterodynamic sea level variability are analyzed in terms of probability density functions of a 100-member ensemble of monthly mean sea surface height (SSH) timeseries simulated with the low-resolution Max Planck Institute Grand Ensemble. To analyze the impact of climate change on sea level statistics, fields of SSH variability, skewness and excess kurtosis representing the historical period 1986–2005 are compared with similar fields from projections for the period 2081–2100 under moderate (RCP4.5) and strong (RCP8.5) climate forcing conditions. Larger deviations of the models SSH statistics from Gaussian are limited to the western and eastern tropical Pacific. Under future climate warming conditions, SSH variability of the western tropical Pacific appear more Gaussian in agreement with weaker zonal easterly wind stress pulses, suggesting a reduced El Niño Southern Oscillation activity in the western warm pool region. SSH variability changes show a complex amplitude pattern with some regions becoming less variable, e.g., off the eastern coast of the north American continent, while other regions become more variable, notably the Southern Ocean. A west (decrease)-east (increase) contrast in variability changes across the subtropical Atlantic under RCP8.5 forcing is related to changes in the gyre circulation and a declining Atlantic Meridional Overturning Circulation in response to external forcing changes. In addition to global mean sea-level rise of 16 cm for RCP4.5 and 24 cm for RCP8.5, we diagnose regional changes in the tails of the probability density functions, suggesting a potential increased in variability-related extreme sea level events under global warmer conditions.