Abstract
North Pacific and North Atlantic SST (sea surface temperature) were used separately and in combination to specify seasonal-mean North American 700 mb heights. One of the goals was to quantify these relationships so that the importance of North Atlantic versus North Pacific SST could be assessed. Sea surface temperature predictors were in the form of EOF (empirical orthogonal function) amplitudes while the predictands consisted of seasonal-mean 700 mb heights at each of 25 locations over North America. Linear regression analysis was used in the data period 1949–77 to build three kinds of models: 1) using the first five North Pacific SST EOFs, 2) using the fist five North Atlantic SST EOFs and 3) using five EOFs from each field, but screening to produce the best five predictor models.
The principal findings can be summarized as:
1) Based on area-averaged skill and percent area of significant skill, North Pacific SST is a better specifier of 700 mb height than North Atlantic SST.
2) Pacific SST models have significant overall skill for all seasons except spring, with area-averaged true skill being greatest in winter (¯S = 0.247) and least in spring (¯S = 0.061).
3) Atlantic SST models do not attain field significance in any season, but perform best overall in winter (¯S = 0.095).
4) A portion of the region studied for winter and summer contained grid point locations where testing indicated that Atlantic SST adds significant information to that of Pacific SST in explaining variations of 700 mb height. This amounted to 13 and 15% of the total area, respectively, which was not enough to declare field significance.