ENSO Forecasts in the North American Multi-Model Ensemble: Composite Analysis and Verification

Abstract:

In this study, we examine precipitation and temperature forecasts during El Nino/Southern Oscillation (ENSO) events in six models in the North American Multi-Model Ensemble (NMME), including the CFSv2, CanCM3, CanCM4, FLOR, GEOS5, and CCSM4 models, by comparing the model-based ENSO composites to the observed. The composite analysis is conducted using the 1982-2010 hindcasts for each of the six models with selected ENSO episodes based on the seasonal Ocean Nino Index (ONI) just prior to the date the forecasts were initiated. Two sets of composites are constructed over the North American continent: one based on precipitation and temperature anomalies, the other based on their probability of occurrence in a tercile-based system. The composites apply to monthly mean conditions in November, December, January, February, and March, respectively, as well as to the five-month aggregates representing the winter conditions. For the anomaly composites, we use the anomaly correlation coefficient and root-mean-square error against the observed composites for evaluation. For the probability composites, unlike conventional probabilistic forecast verification assuming binary outcomes to the observations, both model and observed composites are expressed in probability terms. Performance metrics for such validation are limited. Therefore, we develop a probability anomaly correlation measure and a probability score for assessment, so the results are comparable to the anomaly composite evaluation. We found that all NMME models predict ENSO precipitation patterns well during wintertime; however, some models have large discrepancies between the model temperature composites and the observed. The skill is higher for the multi-model ensemble, as well as the five-month aggregates. Comparing to the anomaly composites, the probability composites have superior skill in predicting ENSO temperature patterns and are less sensitive to the sample used to construct the composites, suggesting that probability composites are a better tool for predicting ENSO impacts over the North American continent.