ABSTRACT

Emerging science based on observations and numerical modeling of the polar ice sheets on Greenland and Antarctica suggests that current projections of future sea-level rise could be significantly underestimated. Physically plausible mechanisms have been identified that could produce a rise in global mean sea level of 2 meters (> 6 feet) or more by 2100. This amount is roughly twice the "likely" sea-level rise assessed by the most recent (2013) report of the Intergovernmental Panel on Climate Change. Sea-level rise of this magnitude would soon transform the potential for extreme flood risk in many coastal cities and communities, with the potential for devastating economic consequences and severe impacts on strategic infrastructure. While progress has recently been made in modeling the future response of the polar ice sheets to a warming atmosphere and ocean, substantial uncertainty remains and more work is needed to verify the potential for such extreme rates of sea-level rise. This project will use state-of-the-art glaciological theory, modeling, and observations of past and present ice sheet behavior to better characterize this uncertainty stemming from complex ice-sheet physics and interactions among the ice sheets, ocean, atmosphere, and the underlying solid Earth. It will produce new projections of the Greenland and Antarctic ice sheets' response to a range of plausible future greenhouse gas emissions scenarios. Advanced statistical techniques will be used to combine the new ice-sheet projections with other factors contributing to global and local sea-level change and associated coastal flooding, in order to produce both sea-level projections and time-evolving water-level probabilities along inhabited coastlines around the globe. The project will provide national and local policy makers and stakeholders with: 1) an assessment of possible levels of future sea-level rise, 2) the frequency (probability in any given year) of specific flood heights being exceeded, 3) an assessment of how those frequencies and storm-surge heights might evolve in the future, and 4) quantified measures of the uncertainty in the projections. The results will be disseminated widely through the development of easily interpretable and universally accessible web-based tools, in close cooperation with Climate Central, an established organization linking climate science and public communication. The goal is to provide the best possible toolkit for informed decision making in terms of coastal resilience and preparedness.

Predicting the future of the polar ice sheets remains one of the grand interdisciplinary challenges in geoscientific modeling. Previously underappreciated glaciological processes (hydrofracturing of ice shelves and ice-cliff collapse) have recently been incorporated into ice-sheet models, but further work is needed to quantify and calibrate these mechanisms, establish ranges of structural and parametric uncertainty, and identify climatic thresholds capable of triggering drastic and possibly irreversible ice-sheet retreat, particularly in the marine-based sectors of Greenland and Antarctica. Technical aspects of this project include extending a numerical ice sheet-shelf model with new processes (water enhanced crevassing, firn influence on supraglacial and englacial hydrology and hydrofracturing, ice-cliff collapse, mélange influence), more direct linkages among ice, ocean, and atmospheric model components, and two-way coupling with solid Earth-gravitational-sea-level models. Large-ensemble methods will be used to identify climatically driven instability thresholds and envelopes in the Greenland and Antarctic ice sheets, and the ensembles will be statistically integrated with other global and local relative sea-level contributors including both non-climatic processes (glacio-isostatic adjustment, gravitational/rotational effects, subsidence/compaction, tectonics, land water storage) and climatic processes (mountain glacier loss, ocean thermal expansion, ocean dynamics, land water storage) to "downscale" the polar ice sheet results to the global network of existing tide gauge locations. Blending extreme value statistics of individual tide gauge time series with our new local relative sea level projections will provide a probabilistic assessment of time-evolving changes in storm-flood frequencies and return periods along global coastlines.

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