[A-CG32] Climate Variability and Predictability on Subseasonal to Centennial Timescales

[ACG32-P07] Multidecadal Variability and Predictability of Antarctic Sea Ice in GFDL SPEAR_LO Model

*Yushi Morioka^1,2,3, Liping Zhang^2,4, Thomas L. Delworth², Xiaosong Yang², Fanrong Zeng², Masami Nonaka¹, Swadhin K. Behera¹ (1.JAMSTEC/VAiG/APL, 2.NOAA/GFDL, 3.Princeton University/AOS, 4.UCAR)

Keywords:Antarctic sea ice, Multidecadal variability, Predictability, Coupled general circulation model

Using a state-of-the-art coupled general circulation model (SPEAR_LO), physical processes underlying Antarctic sea ice multidecadal variability and predictability are investigated. 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 a greater role in the SIE variability. Decadal retrospective forecasts started from the above-mentioned constrained model simulations 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.