Eighty-nine years of monthly surface temperature and precipiation data are categorized as occurring during one of three ENSO phases (El Niño, neutral, La Niña) and one of three PDO states (positive, neutral, negative). Each ENSO/PDO bin is differenced from all ENSO-neutral years to highlight changes in anomaly patterns. These results are compared to anomalies seen when only investigating ENSO U.S. anomaly patterns. The anomaly patterns are then tested for statistical significance. In regions where large and significant changes are identified, cumulative probability distribution functions are created using a resampling technique to determine the underlying distribution of the data.
Key results indicate that positive PDO generally enhances expected ENSO anomaly patterns, while negative PDO interferes with the expected ENSO patterns, making anomaly patterns weaker and more incoherent. Neutral PDO, depending on the strength of the ENSO phase, can exhibit characteristics of both positive and negative PDO. These results indicate that seasonal climate forecasts based on ENSO climate anomalies can by improved by examining the current condition of the PDO.