GCM experiments on changes in atmospheric predictability associated with the PNA pattern and tropical SST anomalies

Based on results from a simple three-level quasi-geostrophic model, Lin and Derome suggested that atmospheric predictability is influenced by the Pacific/North American (PNA) pattern. In the present study, predictability experiments are conducted with the Canadian Centre for Climate Modelling and Analysis general circulation model (CCCma GCM). A 47-yr integration of the GCM with specified sea surface temperature (SST) for the years 1948–94 is first performed. Forecasts are initiated whenever the PNA pattern is in a strong positive or strong negative phase during this simulation. For each forecast, an ensemble of six initial conditions is generated with small random perturbations. Forecasts initiated when the PNA is in its positive phase have smaller growth rates of ensemble standard deviation than forecasts initiated when the PNA is in its negative phase. Regional characteristics of the prediction spread are also examined. Similar experiments are conducted to determine the relationship between atmospheric predictability and SST anomalies in the tropical Pacific. Forecasts initiated when tropical SST anomalies are positive have smaller growth rates of ensemble standard deviation than forecasts initiated when tropical SST anomalies are negative. However, cases with positive tropical SST anomalies but without a strong PNA pattern show a similar prediction spread to cases with negative SST anomalies. The results suggest that, in comparison to the PNA pattern, the influence of tropical SST anomalies is only secondary. A set of three-layer diagnostic equations is used to analyze the GCM results. It is speculated that the transient eddies have a stronger influence on the circulation anomalies (and therefore reduce the atmospheric predictability more) in the negative PNA phase than in the positive PNA phase.