title: Decadal predictability without ocean dynamics.
abstract: This paper shows that the most predictable components of internal variability in coupled atmosphere-ocean models are remarkably similar to the most predictable components of climate models without interactive ocean dynamics (i.e., models whose ocean is represented by a 50-m-deep slab ocean mixed layer with no interactive currents). Furthermore, a linear regression model derived solely from dynamical model output can skillfully predict observed anomalies in these components at least a year or two in advance, indicating that these model-derived components and associated linear dynamics are realistic. These results suggest that interactive ocean circulation is not essential for the existence of multiyear predictability previously identified in coupled models and observations.
authors.affiliation: Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA 22030; asrivas3@gmu.edu.
authors.forename: Abhishekh
authors.initials: A
authors.lastname: Srivastava
authors.affiliation: Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA 22030.|Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, VA 22030.
authors.forename: Timothy
authors.initials: T
authors.lastname: DelSole
keywords: CMIP; average predictability time; decadal predictability; decadal prediction