An Extratropical Contribution to the Signal-to-Noise Paradox in Seasonal Climate Prediction

Ensemble winter seasonal predictions show appreciable skill in parts of the northern hemisphere mid-latitudes, but their utility is hampered by the “signal-to-noise paradox”, in which the amplitude of ensemble mean signals is smaller - often by a factor of 2 or more - than expected from the relatively high levels of correlation between the ensemble mean and observations. The inconsistency calls into question the assumption that ensemble members are “exchangeable” with observations, and thereby implies shortcomings in the underlying climate models. A number of hypotheses have been proposed to explain the origin of the paradox, but currently there is no consensus on its ultimate cause.

Wintertime climate variability in mid-latitudes is strongly influenced by atmospheric circulation, which, in turn, is affected by dynamical teleconnections to remote regions of the globe such as the tropics. Given the importance of tropical teleconnections, we consider here whether removal of tropical errors can eliminate the signal-to-noise paradox. This is achieved by imposing relaxation of winds and temperatures to reanalysed values throughout the tropics in a seasonal hindcast ensemble. By construction in this experiment, we expect the ratio of predicable components (RPC; the most common metric of the paradox) for mid-latitude variables to reduce. However, we find that for mean sea level pressure over large parts of the northern extratropics, as well as the indices of the Arctic and North Atlantic Oscillations (AO and NAO), RPC remains significantly greater than 1. This implies that at least part of the origin of the paradox must arise from errors in the extratropics.

Using a larger set of hindcast ensembles, AO and NAO RPC are shown to be approximately proportional to anomaly correlation. Ensemble simulations with low correlation skill, therefore, tend to have a low RPC. Such ensembles can be misleading, suggesting that the ensemble prediction system does not exhibit the signal-to-noise paradox when in fact the RPC is suppressed by low levels of skill. In such systems, improvements in skill may reveal the paradox. Our results suggest that the paradox is a generic feature of winter atmospheric circulation in the North Atlantic-European region, which is likely to have a detrimental effect on mid-latitude predictions across seasonal to decadal timescales. Furthermore, it is apparent that confident estimates of the anomaly correlation and RPC require larger hindcast ensembles than those used in current operational prediction systems. This emphasises the importance of using large ensembles in the next generation of seasonal predictions.