the utility of the Bering Sea Rule (BSR) and the East Asia Rule (EAR) for making forecasts in the two-to-four-week time frame for the central USA region is examined. It is demonstrated using autocorrelation and Fourier transforms that there may be a degree of predictability in this time frame using the PNA, another teleconnection index, or some variation of them. Neither the BSR nor EAR based forecasts showed skill over climatology in the traditional sense, but using signal detection techniques these indexes were skillful at predicting the onset of anomalous temperature conditions (greater than two standard deviations) in the central USA. The BSR generally produced better results that the EAR and formulae for each index are proposed. Three case studies demonstrate the efficacy of these indexes for forecasting temperatures in the central USA. Then, it is proposed that the success of these indexes is likely due to a strong, quasistationary, and persistent Rossby wave train in the Pacific teleconnection region.

The occurrence of severe weather is an annual problem for much of the United States and North America and maximizes from March through June.With the increased interest in subseasonal weather forecasting, there have been attempts to anticipate the occurrence of anomalous weather on the timescale of one to 4 weeks including the occurrence of severe weather. Previous research has shown that teleconnection indices, associated with long period Rossby wave activity, or persistent large-scale flow regimes have been useful tools in this endeavour. Here, abrupt changes over a 24-72-hr period (10 or more units per day or 20 or more units over 3 days) in the Southern Oscillation Index (SOI) time series will be used to demonstrate that these changes can be associated with the possible occurrence of major severe weather event-days defined as; 20 or more tornado, 155 or more wind speed events >25.9 mÁs −1 , or 135 or more hail diameter larger than 25.4 mm, reports over the United States one to 3 weeks in advance, especially during the March through June period.The severe weather events obtained from the archive at the Storm Prediction Center (SPC) from 1991 through 2020 were used. The results here demonstrate that more than 7 in 10 major severe weather occurrences were associated with abrupt positive and negative changes in the daily SOI when using signal detection methods.