As part of a project working to improve coupled climate-ice sheet modelling by studying the response of ice sheets to changes in climate across different periods since the Last Glacial Maximum, we present an analysis of an ensemble of coupled climate and ice sheet simulations of the modern Greenland using the FAMOUS-BISICLES model and statistical emulation.
FAMOUS-BISICLES, a variant of FAMOUS-ice (Smith et al., 2021a), is a low resolution global climate model that is two-way coupled to a higher resolution adaptive mesh ice sheet model, BISICLES. It is computationally affordable enough to simulate the millennial evolution of the coupled climate-ice sheet system as well as to run large ensembles of simulations.
The ice sheet volume and area are sensitive to a number of parametrisations related to atmospheric and snow surface processes and ice sheet dynamics. Based on that, we designed a perturbed parameters ensemble using a Latin Hypercube sampling technique and ran simulations with climate forcings appropriate for the late 20th century that produced a wide range of ice sheet and climate behaviours.
Gaussian process emulation allows us explore parameter space in a more systematic and faster way than with more complex earth system models and make predictions at input parameter values that are not evaluated in the simulations. We find that the mass balance is most correlated to three parameters:
• n, the exponent in Glen’s flow law, and beta, the coefficient of the basal drag law, both influencing the amount of ice lost through discharge
• rho_threshold, a parameter setting the minimum value the dense firn albedo can possibly reach