Statistical Generation of Ocean Forcing with Spatiotemporal Variability for Ice Sheet Models

Statistical Generation of Ocean Forcing with Spatiotemporal Variability for Ice Sheet Models

Melting of ice at the base of floating ice shelves that fringe the Antarctic ice sheet has been identified as a significant source of uncertainty in sea level rise projections. Part of this uncertainty derives from chaotic internal variability of the coupled ocean-atmosphere system. For numerical ic...

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Bibliographic Details
Published in:Computing in science & engineering Vol. 25; no. 3; pp. 1 - 12
Main Authors: Muruganandham, S., Robel, A.A., Hoffman, M.J., Price, S.
Format: Journal Article
Language:English
Published: New York IEEE 01-05-2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
IEEE Computer Society
Subjects:
Atmospheric models
Climate change
Climate models
Computational modeling
ENVIRONMENTAL SCIENCES
Floating ice
GEOSCIENCES
Ice sheets
Land ice
Meteorology
Numerical models
Oceans
Orthogonal functions
Sheet modelling
Spatiotemporal phenomena
Uncertainty
Variability
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Summary:Melting of ice at the base of floating ice shelves that fringe the Antarctic ice sheet has been identified as a significant source of uncertainty in sea level rise projections. Part of this uncertainty derives from chaotic internal variability of the coupled ocean-atmosphere system. For numerical ice sheet model projections, this uncertainty has not previously been quantified because of the prohibitive computational expense of running large climate model ensembles. Here, we develop and demonstrate a technique that generates independent realizations of internal climate variability from a single climate model simulation. Building on prior developments in model emulation, this technique uses empirical orthogonal function decomposition and Fourier-phase randomization to generate statistically consistent realizations of spatiotemporal variability fields for the target climate variable. The method facilitates efficient sampling of a wide range of climate trajectories, which can also be incorporated within ice sheet or other physical models to represent feedback processes.
Bibliography:89233218CNA000001; NSF-1947882
USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth And Environmental Systems Science (EESS)
ISSN:1521-9615
1558-366X
DOI:10.1109/MCSE.2023.3300908