Distinguishing the roles of natural and anthropogenically forced decadal climate variability: Implications for prediction

Existing methodologies to separate decadal natural variability from anthropogenically forced variability, the degree to which those efforts have succeeded, and the ways in which the methods are limited or challenged by existing data, are described. The methodologies include coupled general circulation models (CGCM) used in climate change projections, signal-to-noise (S/N) maximizing EOF analysis, and linear inverse modeling (LIM). The attribution methods attempt, with uncertainty estimates, to identify the contribution of each external forcing factor to the observed change. It is known that differences in the ocean base state alter the character of natural variability by changing the advective time scale of density/salinity anomalies and pathways between the extratropics and tropics. The rate at which forecast experience will accumulate on the decadal time scale is much slower than the rate at which it accumulates for weather forecasting.