Greenland Ice Sheet Contribution to Future Global Sea Level Rise based on CMIP5 Models

• Published in: Advances in atmospheric sciences Vol. 31; no. 1; pp. 8 - 16
• Main Authors: Yan, Qing, Wang, Huijun, Johannessen, Ola M., Zhang, Zhongshi
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2014; Springer Nature B.V; University of the Chinese Academy of Sciences, Beijing 100049%Nansen-Zhu International Research Centre, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029; Climate Change Research Center, Chinese Academy of Sciences, Beijing 100029%Nansen Environmental and Remote Sensing Center, Bergen 5006, Norway; Nansen Environmental and Remote Sensing Center, Bergen 5006, Norway; Nansen Scientific Society, Bergen 5006, Norway%Bjerknes Centre for Climate Research, Uni Research, Bergen 5007, Norway; Nansen-Zhu International Research Centre, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029
• Subjects: Atmospheric Sciences; Climate; Climate change; Climate models; Earth and Environmental Science; Earth Sciences; Geophysics/Geodesy; Global warming; Ice; Ice sheets; Icebergs; Marine; Meteorology; Projection; Sea level; Sea level rise; Sliding; Socioeconomic factors; Spreads; Studies; Uncertainty; 使用模型; 冰盖; 基础; 格陵兰岛; 气候预测; 海平面上升; 确定性建模; 经济风险; Greenland; PN, Greenland, Greenland Ice Sheet; Greenland ice sheet; ice sheet modeling; model evaluation; sea level rise
• ISSN: 0256-1530; 1861-9533
• DOI: 10.1007/s00376-013-3002-6

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 GrlS 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.