An Assessment of the Antarctic Sea Ice Mass Budget Simulation in CMIP6 Historical Experiment - Li, Sirui; Huang, Gang; Li, Xichen; Liu, Jiping; Fan, Guangzhou (Frontiers in Earth Science, 2021)
The sea ice formation and dissipation processes are complicated and involve many factors and mechanisms, from the basal growth/melting, the frazil ice formation, the snow ice processes to the the dynamic process, etc. The contribution of different factors to the sea ice extension among different models over the Antarctic region has not been systematically evaluated. In this study, we evaluate and quantify the uncertainties of different contributors to the Antarctic sea ice mass budget among 15 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Results show that the simulated total Antarctic sea ice mass budget is primarily adjusted by the basal growth/melting terms, the frazil ice formation term and the snow-ice term, whereas the top melting terms , the lateral melting terms, the dynamic process and the evaporation process play secondary roles in comparison with the first four factors. In addition, while recent studies indicated that the contributors of the Arctic sea ice formation/dissipation processes show strong coherency among different CMIP models, our results revealed a significant model diversity over the Antarctic region, indicating that the uncertatinties of the sea ice formation and dissipation are still considerable in these state-of-the-art climate models. The largest uncertainties appear in the snowice formation, the basal melting and the top melting terms, whose spread among different models is of the same order of magnitude as the multi-model mean. In some models, large positive bias in the snowice terms may neutralize the strong negative bias of the-basal/top melting terms, resulting in a reasonable value of the total Antarctic sea ice cover, yet with an inaccurate physical process. The uncertainties in these Antarctic sea ice formation/dissipation terms highlight the importance of further improving the sea ice dynamical and parameterization processes in the state-of-the-art models.