Abstract: The primary effect of El Niño–Southern Oscillation (ENSO) sea surface temperature (SST) anomalies is to force distinct midlatitude patterns, and not only to modify the probability of the internal variability patterns [such as the Pacific–North American (PNA) pattern of Wallace and Gutzler]. Both the spatial structure and probability distribution of the external ENSO pattern are distinct from the PNA pattern. Ensemble general circulation model (GCM) integrations for 30 winters have been analyzed in the Pacific–North America region. These winters span the recent period of 1981/82 through 1998/99, plus 12 earlier winters; the entire dataset includes six El Niño (warm) and seven La Niña (cold) events. The ensemble size is nine simulations. Empirical orthogonal function (EOF) analysis is carried out for all GCMs and observed seasonal means, for the GCM ensemble means, and for the GCM deviations about the ensemble means. EOF-1 of the GCM 200-hPa height (Z) ensemble mean agrees well with EOF-1 of all GCM seasonal means, and with the pattern that optimally filters out the internal variability. This ENSO pattern agrees with EOF-1 of reanalysis data, although the latter is modified in the Atlantic sector by the presence of the North Atlantic Oscillation pattern. An internal pattern closely resembling the PNA pattern is obtained here from reanalyses as EOF-2 of Z for 37 normal winters (winters that are neither warm nor cold). The GCM version of the PNA pattern can be seen in EOF-2 of the deviation of the GCM means about the ensemble mean, EOF-3 of all GCM seasonal means, and EOF-2 of a GCM integration made with climatologically varying SST. Projections of all GCM seasonal means in a low-dimensional space indicate a segregation of the warm winter seasonal means from those of normal winters along the axis representing the external pattern. There is no support for the hypothesis that the probability distribution functions (pdfs) of internal and external variability are similar. There is clear evidence of shifts in the probability of occurrence of internal patterns in warm and cold winters compared to normal winters. This has been analyzed in terms of only one set of characteristic patterns based on all winters. A more detailed investigation of the dependence of internal variability on SST forcing requires a larger ensemble size. Intraseasonal variability is examined by projecting all individual pentad means on both the ENSO pattern and the PNA pattern (represented by the EOF-1 and EOF-3 of all seasonal means). For five out of the six warm winters, the pdfs of the time series of the coefficient of the ENSO pattern are shifted significantly toward more positive values, with very little probability of having a negative coefficient. For the cold events, the ENSO pattern has greater variability than the PNA pattern. The pdf of the projections of pentads on the seasonal mean anomaly for the same year are sharply peaked. The GCM tropical heating maps show similar patterns for cold and normal winters, while the warm winter pattern is clearly different, especially along the equator. The heating anomalies have larger magnitude in warm than in cold winters. Linearity of the leading ensemble mean principal component (PC) with respect to the Niño-3 index of SST is seen only for positive SST anomalies. When Niño-3 is replaced by heating averaged over the central Pacific, there is a consistent relationship between the ENSO PCs and both positive and negative heating. Niño-3 depends on heating in a linear way for positive heating anomalies, but is independent of heating for negative anomalies.