These issues will be examined in this talk in observations and general circulation model (GCM) simulations of the northern winter season. For the observational analysis, the 40-year (1958-98) global 'reanalysis' data generated at the National Centers for Environmental Prediction (NCEP) were stratified into El Nino, La Nina, and neutral winters. The GCM analysis was based on GCM runs made with prescribed seasonally evolving SSTs for El Nino, La Nina, and neutral winter conditions. A very large number of seasonal integrations, differing only in initial atmospheric states, were made for each of these tropical SST conditions. The ensemble was large enough that the changes of probability even in regions not usually associated with strong El Nino signals could be ascertained.
The results indicate a large asymmetry in the response to El Nino and La Nina conditions, not only in the mean but also the variability. In general the response for El Nino conditions was stronger, but also MORE VARIABLE, than for La Nina conditions. The source of the increased variability was traced to increased variability of precipitation in the central equatorial Pacific. The mean response was also highly nonlinear in the sense that in several regions the El Nino and La Nina probability distributions of lower tropospheric temperature and precipitation were distinguishable from their 'neutral' counterparts, but were indistinguishable from one another. These and other results confirm that the remote signals for individual El Nino and La Nina events can differ substantially from the historical signal obtained by pooling and averaging disparate events in the historical record. They also highlight the importance of understanding and determining the changes to the full probability distribution, and not just shifts of the mean, to extract the full benefit from seasonal predictions of SST in the tropical Pacific basin.