Changes in Seasonal Mean Atmospheric Internal Variability Associated with ENSO

The observed seasonal atmospheric state in the extratropical latitudes and its interannual variability can be characterized in terms of probability distribution functions. Predictability of the seasonal anomalies related to interannual variation in the SSTs, therefore, entails understanding the influence of SST forcing on various moments of the probability distribution which characterize the seasonal atmospheric variability. Such an understanding for changes in the atmospheric mean state with SSTs is well documented. In this paper we extend the analysis to also include the impact of SST forcing on the atmospheric variability which can exist irrespective of any changes in SSTs, i.e., atmospheric internal variability.

Our analysis is primarily based on ensemble atmospheric general circulation model (AGCM) simulations forced with observed SSTs for the period 1950-94. To establish the robustness of our results and to ensure that they are not unduly affected by biases in a particular AGCM, the analysis is based on simulations from four different AGCMs.

The analysis of AGCM simulations indicates that over the Pacific North American region, the impact of interannual variations in SSTs on the internal component of the variability of seasonal means may not be significant. This is in contrast to their well defined impact on the seasonal atmospheric mean state itself which is manifested as an anomalous wave train over this region. For seasonal predictions, results imply that the dominant contribution to seasonal predictability comes from the impact of SSTs on the atmospheric mean state (or the first moment), with the impact of SSTs on the atmospheric internal variability (or the second moment) playing an insignificant role.