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Projecting Future Greenland Ice Sheet Loss
A major indicator of climate change is sea level rise, which is impacted by melting of glaciers and ice sheets. The Greenland Ice Sheet (GrIS) is one of the two major bodies of ice in our present climate system. It contains the equivalent of almost 7m of sea level rise, and is being increasingly impacted by human-induced warming. In the hopes of understanding future sea level rise, climate and glaciology research efforts are increasingly focusing on improved modelling of ice sheet dynamics and ice sheet/climate interactions. Coupled ice-sheet/climate modelling is critical for this task due to the strong coupling effects between the climate and ice sheets. For example, changes to ice sheets directly affect sea level and oceanic and atmospheric circulation patterns, which in turn affect the subsequent rates of ice sheet evolution.
Scientific advances and improved computing resources have recently allowed for use of computationally expensive new models, which couple ice sheet models with climate models, to better project ice sheet behaviour and resulting climate change. However, a complication of this coupled-model approach is the presence of significant uncertainty in fully coupled ice-sheet/climate simulations. This uncertainty is practically important to understand, since it relates directly to uncertainty in predictions of ice-sheet-derived sea level rise.
Jeremy Fyke, currently working at Los Alamos National Laboratory (LANL), completed his PhD at the University of Victoria (UVic) under the direction of Professor Andrew Weaver. Using the UVic Earth System Climate Model-Penn State University Ice Sheet model, and critically supported by access to WestGrid’s Bugaboo and Hermes high performance computing (HPC) systems, Fyke undertook research to better understand uncertainty in coupled ice-sheet/climate simulations of the GrIS response to increased carbon dioxide (CO2) concentrations. In particular, he assessed the impact current scientific uncertainties in climate sensitivity (the amount of global average surface warming that occurs in response to CO2 increases) and polar amplification of climate change (the relative amplification of warming in the Arctic region) have on GrIS deglaciation.
“WestGrid's HPC resources were absolutely critical for carrying out these simulations. To explore the effects of climate sensitivity and polar amplification on GrIS deglaciation, we needed to carry out more than 150 simulations in our 'ensemble' experiment to sufficiently explore model parameter space,” says Fyke.
Fyke’s team developed a coupled ice-sheet/climate model to simulate the future rate of GrIS deglaciation while also controlling climate sensitivity and polar amplification in a controlled and consistent manner. They found that realistic variations in these two aspects of climate change resulted in GrIS ice volume loss ranging from 5 to 40% of the original ice volume (<1 to 3m sea level rise) after 500 years under tripled CO2 conditions, thus identifying polar ampliﬁcation and climate sensitivity as major controls on GrIS behavior under elevated CO2. They concluded that future projections of sea level rise will depend critically on understanding these aspects of the global climate system response to human-induced climate change.
“This research highlights that predicting future sea level rise will depend critically on understanding the global coupled climate system response to human forcing,” says Fyke.
The research was facilitated by advances in HPC systems which have resulted in improved climate modelling capabilities. Increases in resolution, which better resolve Earth system processes (e.g. clouds, ocean eddies, or ice sheet streams), require exponential increases in computing power. As well, understanding climate system response to change requires ever-larger ensembles of model simulations with increasing complexity, which also requires exponentially-increased computing and data storage requirements. Fyke is grateful to have had access to the necessary HPC resources and facilities supported by WestGrid and Compute Canada.
“Even 10 years ago, the type of study that we carried out to understand the future response of the Greenland Ice Sheet, would have been simply impossible given the lack of access to large WestGrid-style computing resources, “ says Fyke. “More broadly, the ability to model at higher resolutions and with larger ensembles is dramatically accelerating our understanding of the climate system, and the impact of human forcing on the climate system, through numerical climate modelling.”
“Combined with the computational cost of the ice-sheet/climate model, developing and carrying out this exercise would have been very difficult without the ability to run on WestGrid resources.”
Fyke continues his work through his involvement with the Climate, Ocean and Sea Ice Modelling Group (COSIM) at LANL, which is working to develop, test and apply climate models in support of the United States Department Of Energy’s Climate Change Research. Long term, the group aims to deliver improved models for evaluating the role of ocean and land and sea ice in high-latitude climate change, and project the impacts of high-latitude change on regions throughout the globe.
For more information on this research you can read Fyke’s paper ‘Impact of climate sensitivity and polar amplification on projections of Greenland Ice Sheet loss’ published in the January 2014 edition of the international journal Climate Dynamics.