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|Abstract:||The decadal predictability of sea surface temperature (SST) and 2-m air temperature (T2m) in the Geophysical Fluid Dynamics Laboratory (GFDL) decadal hindcasts, which are part of the Fifth Coupled Model Intercomparison Project experiments, has been investigated using an average predictability time (APT) analysis. Comparison of retrospective forecasts initialized using the GFDL Ensemble Coupled Data Assimilation system with uninitialized historical forcing simulations using the same model allows identification of the internal multidecadal pattern (IMP) for SST and T2m. The IMP of SST is characterized by an interhemisphere dipole, with warm anomalies centered in the North Atlantic subpolar gyre region and North Pacific subpolar gyre region, and cold anomalies centered in the Antarctic Circumpolar Current region. The IMP of T2m is characterized by a general bipolar seesaw, with warm anomalies centered in Greenland and cold anomalies centered in Antarctica. The retrospective prediction skill of the initialized system, verified against independent observational datasets, indicates that the IMP of SST may be predictable up to 4 (10) yr lead time at 95% (90%) significance level, and the IMP of T2m may be predictable up to 2 (10) yr at the 95% (90%) significance level. The initialization of multidecadal variations of northward oceanic heat transport in the North Atlantic significantly improves the predictive skill of the IMP. The dominant roles of oceanic internal dynamics in decadal prediction are further elucidated by fixed-forcing experiments in which radiative forcing is returned abruptly to 1961 values. These results point toward the possibility of meaningful decadal climate outlooks using dynamical coupled models if they are appropriately initialized from a sustained climate observing system.|
|Citation:||Yang, Xiaosong, Anthony Rosati, Shaoqing Zhang, Thomas L. Delworth, Rich G. Gudgel, Rong Zhang, Gabriel A. Vecchi et al. "A predictable AMO-like pattern in the GFDL fully coupled ensemble initialization and decadal forecasting system." Journal of Climate 26, no. 2 (2013): 650-661. doi:10.1175/JCLI-D-12-00231.1.|
|Pages:||650 - 661|
|Type of Material:||Journal Article|
|Journal/Proceeding Title:||Journal of Climate|
|Version:||Final published version. Article is made available in OAR by the publisher's permission or policy.|
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