Teleconnective Response of the Pacific–North American Region Atmosphere to Large Central Equatorial Pacific SST Anomalies

A prominent year-round ensemble response to a global sea surface temperature (SST) anomaly field fixed to that for January 1992 (near the peak of a major warm El Niño–Southern Oscillation episode) was observed in a 20-yr integration of the general circulation model used for operational seasonal prediction by the U.S. National Weather Service. This motivated a detailed observational reassessment of the teleconnections between strong SST anomalies in the central equatorial Pacific Ocean and Pacific–North America region 700-hPa heights and U.S. surface temperatures and precipitation. The approach used consisted of formation of monthly mean composites formed separately from cases in which the SST anomaly in a key area of the central equatorial Pacific Ocean was either large and positive or large and negative. Extensive permutation tests were conducted to test null hypotheses of no signal in these composites. The results provided a substantial case for the presence of teleconnections to either the positive- or negative-SST anomalies in every month of the year. These signals were seasonally varying (sometimes with substantial month to month changes) and, when present for both SST-anomaly signs in a particular month, usually were not similarly phased patterns of opposite polarity (i.e., the SST–teleconnected variable relationships were most often nonlinear). A suite of 13 45-yr integrations of the same model described above was run with global SST analyses reconstructed from the observational record. Corresponding composites from the model were formed and compared visually and quantitatively with the high-confidence observational signals. The quantitative comparisons included skill analyses utilizing a decomposition that relates the squared differences between two maps to phase correspondence and amplitude and bias error terms and analyses of the variance about composite means. For the latter, in the case of the model runs it was possible to estimate the portions of this variance attributable to case to case variation in SSTs and to internal variability. Comparisons to monthly mean maps and analyses of variance for the 20-yr run with SSTs fixed to January 1992 values were also made. The visual and quantitative comparisons all revealed different aspects of prominent model systematic errors that have important implications for the optimum exploitation of the model for use in prediction. One of these implications was that the current model's ensemble responses to SST forcing will not be optimally useful until after nonlinear correction of SST-field-dependent systematic errors.