Using equatorial Pacific sea surface temperature anomalies to forecast seasonal energy demand in four US regions: An applied climate research experience for undergraduate meteorology students

The El Nino-Southern Oscillation (ENSO) phenomenon explains some of the int erannual climate variability in many tropical and midlatitude regions. It i s 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 exami ned 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 fo r summers and June-October for winters), and 3) the effects of strong winte r ENSO events on future seasons. All three ENSO-related indices were based on monthly equatorial Pacific SST anomalies in the Nino-3.4 region. Regiona l probabilities of each HDD/CDD category (above, average, and below) were d etermined for each ENSO predictive index. The highest probability of experi encing an HDD/CDD anomaly occurs with strong preseason SST trends. When pre summer SST cooling occurs, the northeast and midcontinent experience above- average CDD (80% and 75%, respectively). Other interesting relationships we re found between strong winter ENSO events and ensuing HDD/CDD anomalies. T hese results suggest that utility-based decision makers who can utilize enh anced climate information may reap benefits during particular years by inte grating the ENSO information into their models. This study was part of a sp ecial student training experiment conducted at Northern Illinois University .