Xiao Luo, Sophie Nowicki

The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) resulted in a large number of ice sheet simulations from multiple ice sheet models. To-date, there are no model weighting studies that analyze or quantify the model performance and possible duplication of the ISMIP6 ice sheet models and the resulting effect on projections of mass loss. In this study, we adopt a model weighting scheme for the ISMIP6-Greenland that accounts for both model performance compared to observation and model similarity due to possible duplication. We choose ice velocity and thickness for the measurement of model performance, and we use as many variables as we can to compute similarity indexes. For quality weight, we choose a quality parameter that leads to reduction of ensemble bias for both present-day and future projection. For similarity weight, we use an intermediate parameter that efficiently highlights model independence. The total model weights are simply constructed as the multiplication of the quality and similarity weights. Finally, the sea level rise contribution from ISMIP6-Greenland is updated with the weights, and we find that, although the multi-model mean is not considerably shifted, the model spreads are reduced by applying the model weights.