Large sampling uncertainty when diagnosing the ‘eddy feedback parameter’
and its role in the signal-to-noise paradox
Abstract
A too-weak eddy feedback in models has been proposed to explain the
signal-to-noise paradox in seasonal-to-decadal forecasts of the winter
Northern Hemisphere. We show that the “eddy feedback parameter’ (EFP)
used in previous studies is sensitive to sampling and multidecadal
variability. When these uncertainties are accounted for, the EFP
diagnosed from CMIP6 historical simulations generally falls within the
reanalysis uncertainty. We find the EFP is not independent of the
sampled North Atlantic Oscillation (NAO). Within the same dataset, a
sample containing larger NAO variability will show a larger EFP,
suggesting that the link between eddy feedbacks and the signal-to-noise
paradox could be due to sampling effects with the EFP. An alternative
measure of eddy feedback, the barotropic energy generation rate, is less
sensitive to sampling errors and delineates CMIP6 models that have weak,
strong, or unbiased eddy feedbacks, but shows little relation to NAO
variability.