Abstract
The tropical Pacific has begun to experience a new type of El Nino, which has occurred particularly frequently during the last decade, referred to as the central Pacific (CP) El Nino. Various coupled models with different degrees of complexity have been used to make real-time El Nino predictions, but high uncertainty still exists in their forecasts. It remains unknown as to how much of this uncertainty is specifically related to the new CP-type El Nino and how much is common to both this type and the conventional Eastern Pacific (EP)-type El Nino. In this study, the deterministic performance of an El Nino–Southern Oscillation (ENSO) ensemble prediction system is examined for the two types of El Nino. Ensemble hindcasts are run for the nine EP El Nino events and twelve CP El Nino events that have occurred since 1950. The results show that (1) the skill scores for the EP events are significantly better than those for the CP events, at all lead times; (2) the systematic forecast biases come mostly from the prediction of the CP events; and (3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Nino. Further improvements to coupled atmosphere–ocean models in terms of CP El Nino prediction should be recognized as a key and high-priority task for the climate prediction community.
Highlights
As the most striking interannual variability in the tropical Pacific, El Nino–Southern Oscillation (ENSO) has been intensively studied for several decades
It has been noticed that central Pacific (CP)-type El Nino events have occurred more frequently in recent decades, and that this type of El Nino may be generated by a mechanism distinct from that of the traditional Eastern Pacific (EP)-type El Nino (Yu et al, 2010, 2017)
Beyond a three-month lead time, the prediction skill is consistently higher for predicting EP events (0.1–0.2 higher in terms of the correlation coefficient) than CP events
Summary
As the most striking interannual variability in the tropical Pacific, El Nino–Southern Oscillation (ENSO) has been intensively studied for several decades. One possible reason for the shift in the ENSO prediction skill is because a different type of El Nino—as compared to the canonical eastern Pacific (EP) El Nino (McPhaden et al, 2011; Yu et al, 2012)—emerged in the 2000s. A systematic examination of climate models’ performances in predicting the two types of El Nino has been less well explored, and it remains controversial as to whether their predictabilities are distinct in different state-of-the-art climate models (e.g., Jeong et al, 2012; Yang and Jiang, 2014; Imada et al, 2015; Luo et al, 2016). Based on version 2 of the National Centers for Environmental Prediction Climate Forecast System, Yang and Jiang (2014) compared the model skill in using the El Nino Modoki index (EMI) and Nino index to predict the two types of El Nino, and showed that the EMI was more persistent and predictable than the Nino index during boreal summer and autumn. The common forecast biases for the two types of El Nino are identified and contrasted throughout the different phases of the El Nino lifecycle
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
