Jet Latitude Regimes and the Predictability of the North Atlantic Oscillation

TL;DR

This study analyzes how the predictability of the North Atlantic Oscillation (NAO) is linked to jet latitude regimes and their persistence, explaining the signal-to-noise paradox in weather prediction models.

Contribution

It introduces a statistical model connecting jet regime persistence to NAO predictability, revealing the IFS model's skill in capturing regime dynamics and explaining the signal-to-noise paradox.

Findings

IFS predicts jet regime persistence, leading to NAO predictability.

Model underestimates regime persistence, explaining low signal-to-noise ratio.

External forcing and eddy feedbacks influence jet regime variability.

Abstract

In recent years, numerical weather prediction models have begun to show notable levels of skill at predicting the average winter North Atlantic Oscillation (NAO) when initialised one month ahead. At the same time, these model predictions exhibit unusually low signal-to-noise ratios, in what has been dubbed a `signal-to-noise paradox'. We analyse both the skill and signal-to-noise ratio of the Integrated Forecast System (IFS), the European Center for Medium-range Weather Forecasts (ECMWF) model, in an ensemble hindcast experiment. Specifically, we examine the contribution to both from the regime dynamics of the North Atlantic eddy-driven jet. This is done by constructing a statistical model which captures the predictability inherent to to the trimodal jet latitude system, and fitting its parameters to reanalysis and IFS data. Predictability in this regime system is driven by interannual variations in the persistence of the jet latitude regimes, which determine the preferred state of the jet. We show that the IFS has skill at predicting such variations in persistence: because the position of the jet strongly influences the NAO, this automatically generates skill at predicting the NAO. We show that all of the skill the IFS has at predicting the winter NAO over the period 1980-2010 can be attributed to its skill at predicting regime persistence in this way. Similarly, the tendency of the IFS to underestimate regime persistence can account for the low signal-to-noise ratio, giving a possible explanation for the signal-to-noise paradox. Finally, we examine how external forcing drives variability in jet persistence, as well as highlight the role played by transient baroclinic eddy feedbacks to modulate regime persistence.