Seasonal Temperature Predictions Using a Jackknife Approach with an Intraseasonal Variability Index

摘要: Abstract The prediction of seasonal temperatures in the United States farm Pacific sea surface was examined using a jackknifed regression scheme and measure intraseasonal atmospheric circulation variability. Predictions were made both one mouth season lead. Employing methodology when deriving objective equations allowed forecast skill to be better quantified than pan studies, by greatly increasing effective independent sample size. procedures repeated on three data sets for each season: 1) all year period 1930–79 (29 or 30 years); 2) high variability index (VI) years; 3) low VI years. constructed 5-day mean 700 mb heights portion Northern Hemisphere. following results obtained from study: winter summer, significant models found, though is modest (less 60% correct two-cl...