Ice-Sheet Model Calibration and Parametric Uncertainty Analysis for 2000-2020

The Antarctic Ice Sheet (AIS) exerts a critical influence on global sea level rise (SLR). Accelerating mass loss, particularly in West Antarctica, is projected to significantly enhance its contribution in the coming centuries. Approximately half of the surface mass gain is offset by ocean-induced basal melting, highlighting the critical role of ice-ocean interactions (Depoorter et al., 2013; Paolo et al., 2023). Despite advances in AIS modelling, significant uncertainties persist, largely arising from the representation of basal melt processes, which are influenced by varying parameterizations, parameter choices and sparsely sampled oceanic forcing datasets. These uncertainties, coupled with divergent future climate forcing scenarios, lead to a large spread in future ice-sheet trajectories and their contribution to SLR by 2300 (Seroussi et al 2024).

To enable robust estimates of future mass fluxes from the AIS, this study uses a circum-Antarctic high-resolution configuration of the Úa ice-sheet model (Gudmundsson, 2020, 2024) to conduct a series of transient simulations spanning 2000-2020. These simulations are used to quantify uncertainties and sensitivities in modelled ice-shelf melt. We apply multiple basal melting parameterizations and a plausible range of parameter choices, including the Local Quadratic Melting (Jourdain et al., 2020), PICO (Reese et al., 2018), and Plume Models (Jenkins, 1991; Lazeroms et al., 2019; Rosier et al., 2024), forced by two different observational oceanic datasets. By varying initial ice-sheet conditions, basal melting schemes, and external forcing, a large ensemble of hindcast simulations was generated and validated against observed changes in ice velocity, thickness, and grounding line position, providing robust insights into model behaviour and ice-ocean interactions.

This initial work, funded by the Horizion Europe project OCEAN ICE, forms a robust foundation for the next phase of forecast transient simulations, enabling long-term projections of AIS contributions to SLR for an ensemble of observationally-constrained model parameters. Our work aims to quantify the complex interplay between basal melting, ice dynamics, and oceanic forcing, while delivering key insights for enhancing the predictive capability of coupled ice-sheet-ocean models in a rapidly changing climate.