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The El Niño-Southern Oscillation (ENSO) phenomenon explains some of the interannual climate variability in many tropical and midlatitude regions. It is important in developing more accurate seasonal climate forecasts and thus in aiding long-range weather-sensitive decision making in various sectors. The degree to which ENSO information could forecast one of three classes of seasonal cooling degree days (CDD) and heating degree days (HDD) was examined using 1) the magnitude of the ENSO event during a given season, 2) the preseason rate of change of sea surface temperature (SSTs) (December–May for summers and June–October for winters), and 3) the effects of strong winter ENSO events on future seasons. All three ENSO-related indices were based on monthly equatorial Pacific SST anomalies in the Niño-3.4 region. Regional probabilities of each HDD/CDD category (above, average, and below) were determined for each ENSO predictive index. The highest probability of experiencing an HDD/CDD anomaly occurs with strong preseason SST trends. When presummer SST cooling occurs, the northeast and midcontinent experience above-average CDD (80% and 75%, respectively). Other interesting relationships were found between strong winter ENSO events and ensuing HDD/CDD anomalies. These results suggest that utility-based decision makers who can utilize enhanced climate information may reap benefits during particular years by integrating the ENSO information into their models. This study was part of a special student training experiment conducted at Northern Illinois University.

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Using Equatorial Pacific Sea Surface Temperature Anomalies to Forecast Seasonal Energy Demand in Four U.S. Regions: An Applied Climate Research Experience for Undergraduate Meteorology Students