Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM)
- The Parallel Ice Sheet Model (PISM) is applied to the Antarctic Ice Sheet over the last two glacial cycles (approximate to 210 000 years) with a resolution of 16 km. An ensemble of 256 model runs is analyzed in which four relevant model parameters have been systematically varied using full-factorial parameter sampling. Parameters and plausible parameter ranges have been identified in a companion paper (Albrecht et al., 2020) and are associated with ice dynamics, climatic forcing, basal sliding and bed deformation and represent distinct classes of model uncertainties. The model is scored against both modern and geologic data, including reconstructed grounding-line locations, elevation-age data, ice thickness, surface velocities and uplift rates. An aggregated score is computed for each ensemble member that measures the overall model-data misfit, including measurement uncertainty in terms of a Gaussian error model (Briggs and Tarasov, 2013). The statistical method used to analyze the ensemble simulation results follows closely theThe Parallel Ice Sheet Model (PISM) is applied to the Antarctic Ice Sheet over the last two glacial cycles (approximate to 210 000 years) with a resolution of 16 km. An ensemble of 256 model runs is analyzed in which four relevant model parameters have been systematically varied using full-factorial parameter sampling. Parameters and plausible parameter ranges have been identified in a companion paper (Albrecht et al., 2020) and are associated with ice dynamics, climatic forcing, basal sliding and bed deformation and represent distinct classes of model uncertainties. The model is scored against both modern and geologic data, including reconstructed grounding-line locations, elevation-age data, ice thickness, surface velocities and uplift rates. An aggregated score is computed for each ensemble member that measures the overall model-data misfit, including measurement uncertainty in terms of a Gaussian error model (Briggs and Tarasov, 2013). The statistical method used to analyze the ensemble simulation results follows closely the simple averaging method described in Pollard et al. (2016). This analysis reveals clusters of best-fit parameter combinations, and hence a likely range of relevant model and boundary parameters, rather than individual best-fit parameters. The ensemble of reconstructed histories of Antarctic Ice Sheet volumes provides a score-weighted likely range of sea-level contributions since the Last Glacial Maximum (LGM) of 9.4 +/- 4.1m (or 6.5 +/- 2.0 x 10(6) km(3)), which is at the upper range of most previous studies. The last deglaciation occurs in all ensemble simulations after around 12 000 years before present and hence after the meltwater pulse 1A (MWP1a). Our ensemble analysis also provides an estimate of parametric uncertainty bounds for the present-day state that can be used for PISM projections of future sea-level contributions from the Antarctic Ice Sheet.…
Author details: | Torsten AlbrechtORCiDGND, Ricarda WinkelmannORCiDGND, Anders LevermannORCiDGND |
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DOI: | https://doi.org/10.5194/tc-14-633-2020 |
ISSN: | 1994-0416 |
ISSN: | 1994-0424 |
Title of parent work (English): | The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union |
Subtitle (English): | part 2: parameter ensemble analysis |
Publisher: | Copernicus Publ. |
Place of publishing: | Göttingen |
Publication type: | Article |
Language: | English |
Date of first publication: | 2020/02/14 |
Publication year: | 2020 |
Release date: | 2024/01/11 |
Volume: | 14 |
Issue: | 2 |
Number of pages: | 24 |
First page: | 633 |
Last Page: | 656 |
Funding institution: | Deutsche ForschungsgemeinschaftGerman Research Foundation (DFG); [LE1448/6-1, LE1448/7-1, WI14556/4-1]; NASANational Aeronautics & Space; Administration (NASA) [NNX17AG65G]; NSFNational Science Foundation (NSF); [PLR-1603799, PLR-1644277]; Gauss Centre for Supercomputing and Leibniz; Supercomputing Centre [pn69ru, pr94ga] |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie |
DDC classification: | 5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik |
Peer review: | Referiert |
Publishing method: | Open Access / Gold Open-Access |
DOAJ gelistet | |
License (German): | CC-BY - Namensnennung 4.0 International |