Abstract
The tropical Pacific has begun to experience a new type of El Niño, which has occurred particularly frequently during the last decade, referred to as the central Pacific (CP) El Niño. Various coupled models with different degrees of complexity have been used to make real-time El Niño 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 Niño and how much is common to both this type and the conventional Eastern Pacific (EP)-type El Niño. In this study, the deterministic performance of an El Niño–Southern Oscillation (ENSO) ensemble prediction system is examined for the two types of El Niño. Ensemble hindcasts are run for the nine EP El Niño events and twelve CP El Niño 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 Niño. Further improvements to coupled atmosphere–ocean models in terms of CP El Niño prediction should be recognized as a key and high-priority task for the climate prediction community.
摘要
El Niño作为全球最显著的年际变化信号, 对全球气候和环境均有着重要影响。近年来, 因其最大的年际异常信号主要集中在中太平洋区域, 且出现频率明显增加, 一种新的中太平洋型(CP型)El Niño现象引起了广泛的关注。过去研究主要集中在区分新的CP型El Niño事件与传统的东太平洋型(EP型)El Niño事件对全球各个区域不同的影响, 但是对于两类El Niño事件预测技巧存在的差异及其原因并未给出较好的解释。中国科学院大气物理研究所郑飞研究员和美国加州大学欧文分校Jin-Yi Yu教授, 基于大气所ENSO集合预测系统检验1950年以来的El Niño事件预测水平, 合作发现两类El Niño事件在预测技巧上存在着明显差异, 即系统对CP型El Niño事件的预测能力相比EP型事件明显偏弱。进一步的分析发现, CP型事件预测技巧偏弱有两个可能的原因制约: (1) 模型的预测偏差主要来源于其对CP型El Niño事件的预测; (2) 这一预测偏差主要体现为对CP型El Niño事件预测的春季暖偏差, 同时也与CP型事件的“春季预报障碍”更严重紧密联系。
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Acknowledgements
The authors wish to thank the two anonymous reviewers for their very helpful comments and suggestions. This work was supported by the National Program for Support of Top-notch Young Professionals, and the National Natural Science Foundation of China (Grant No. 41576019). J.-Y. YU was supported by the US National Science Foundation (Grant No. AGS-150514).
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Electronic Supplementary Material to: Contrasting the Skills and Biases of Deterministic Predictions for the Two Types of El Niño
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Zheng, F., Yu, JY. Contrasting the skills and biases of deterministic predictions for the two types of El Niño. Adv. Atmos. Sci. 34, 1395–1403 (2017). https://doi.org/10.1007/s00376-017-6324-y
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DOI: https://doi.org/10.1007/s00376-017-6324-y