Dixon, K. W., and R. P. Harnack, 1986: Effect of intraseasonal circulation variability on winter temperature forecast skill. Monthly Weather Review, 114 (1), 208-214.

Abstract: The prediction of winter temperatures in the U.S. from Pacific sea surface temperatures was examined by using a jackknifed regression scheme and a measure of intraseasonal atmospheric circulation variability. Using a jackknifed regression methodology when deriving objective prediction equations permitted forecast skill to be better quantified than in past studies by greatly increasing the effective independent sample size. The procedures were repeated on three data sets: 1) all winters in the period 1950-1979 (30 winters), 2) the 15 winters having the highest Variability Index (VI), and 3) the 15 winters having the lowest VI. The VI was constructed to measure the intraseasonal variability of five-day-period mean 700-mb heights for a portion of the Northern Hemisphere. Verification results showed that statistically significant skill was achieved in the complete sample (overall mean percent correct of 39 and 59 for three- and two-category forecasts, respectively), but improved somewhat for the low VI sample. In that case, corresponding scores were 44 and 64% correct. In contrast, the high VI sample scores were lower (34 and 58% correct) than for the complete sample, indicating that skill is probably dependent upon the degree of intraseasonal circulation variability.