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Long‐term projections of sea‐level rise from ice sheets
Author(s) -
Golledge Nicholas R.
Publication year - 2020
Publication title -
wiley interdisciplinary reviews: climate change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.678
H-Index - 75
eISSN - 1757-7799
pISSN - 1757-7780
DOI - 10.1002/wcc.634
Subject(s) - ice sheet model , antarctic ice sheet , ice sheet , climatology , lead (geology) , term (time) , climate change , sea ice , greenland ice sheet , geology , cryosphere , environmental science , drift ice , oceanography , paleontology , physics , quantum mechanics
Abstract Under future climate change scenarios it is virtually certain that global mean sea level will continue to rise. But the rate at which this occurs, and the height and time at which it might stabilize, are uncertain. The largest potential contributors to sea level are the Greenland and Antarctic ice sheets, but these may take thousands of years to fully adjust to environmental changes. Modeled projections of how these ice masses will evolve in the future are numerous, but vary both in complexity and projection timescale. Typically, there is greater agreement between models in the present century than over the next millennium. This reflects uncertainty in the physical processes that dominate ice‐sheet change and also feedbacks in the ice–atmosphere–ocean system, and how these might lead to nonlinear behavior. Satellite observations help constrain short‐term projections of ice‐sheet change but these records are still too short to capture the full ice‐sheet response. Conversely, geological records can be used to inform long‐term ice‐sheet simulations but are prone to large uncertainties, meaning that they are often unable to adequately confirm or refute the operation of particular processes. Because of these limitations there is a clear need to more accurately reconstruct sea level changes during periods of the past, to improve the spatial and temporal extent of current ice sheet observations, and to robustly attribute observed changes to driving mechanisms. Improved future projections will require models that capture a more extensive suite of physical processes than are presently incorporated, and which better quantify the associated uncertainties. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models

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