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Sea level rise(SLR) is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet(GrIS) will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS(SImulation COde for POLythermal Ice Sheets) driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project(CMIP5) to estimate the GrIS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0–16(0–27) cm to global SLR by 2100 under the Representative Concentration Pathways(RCP) 4.5(RCP 8.5) scenarios. The projected SLR increases further to 7–22(7–33) cm with 2×basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm(10 cm and 13 cm with 2×basal sliding) under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.
Sea level rise (SLR) is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet (GrIS) will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. used the ice sheet model SICOPOLIS (SImulation COde for POLythermal Ice Sheets) driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) to estimate the GrIS contribution to global SLR. Based on the outputs of the 20 (RCP 8.5) scenarios. The projected SLR increases further to 7-22 (7) -33) cm with 2 × basal sliding included. The response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm (10 cm and 13 cm with 2 × basal sliding) under the RCP 4.5 and RCP 8.5 scenari os, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.