Multidecadal Variability and Predictability of Antarctic Sea Ice in GFDL SPEAR_LO Model
Using a state-of-the-art coupled general circulation model, physical processes underlying Antarctic sea ice multidecadal variability and predictability are investigated. Our model simulations constrained with atmospheric reanalysis and observed sea surface temperature broadly capture the observed se...
Main Authors: | , , , , , , |
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Format: | Text |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://doi.org/10.5194/tc-2023-18 https://tc.copernicus.org/preprints/tc-2023-18/ |
Summary: | Using a state-of-the-art coupled general circulation model, physical processes underlying Antarctic sea ice multidecadal variability and predictability are investigated. Our model simulations constrained with atmospheric reanalysis and observed sea surface temperature broadly capture the observed sea ice extent (SIE) variability with a low sea ice state (late 1970s–1990s) and a high sea ice state (2000s–early 2010s), although the model overestimates the SIE decrease over the Weddell Sea around the 1980s. The low sea ice state is largely due to an occurrence of strong deep convection in the Southern Ocean that subsequently induces anomalous warming of the upper ocean. During the high sea ice period (post-2000s), the deep convection substantially weakens, so that surface wind variability plays greater roles in the SIE variability. Decadal retrospective forecasts started from the above-mentioned constrained model results demonstrate that the Antarctic sea ice multidecadal variability can be skillfully predicted 6–10 years in advance, showing a moderate correlation with the observation (0.4). Ensemble members with a stronger deep convection tend to predict a larger sea ice decrease in the 1980s, whereas the members with a larger surface wind variability tend to predict a larger sea ice increase after the 2000s. Therefore, skillful simulation and prediction of the Antarctic sea ice multidecadal variability require accurate simulation and prediction of both the Southern Ocean deep convection and surface wind variability in the model. |
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