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Advances in Atmospheric Sciences

, Volume 35, Issue 5, pp 495–506 | Cite as

ENSO Frequency Asymmetry and the Pacific Decadal Oscillation in Observations and 19 CMIP5 Models

  • Renping Lin
  • Fei Zheng
  • Xiao Dong
Original Paper

Abstract

Using observational data and the pre-industrial simulations of 19 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), the El Niño (EN) and La Niña (LN) events in positive and negative Pacific Decadal Oscillation (PDO) phases are examined. In the observational data, with EN (LN) events the positive (negative) SST anomaly in the equatorial eastern Pacific is much stronger in positive (negative) PDO phases than in negative (positive) phases. Meanwhile, the models cannot reasonably reproduce this difference. Besides, the modulation of ENSO frequency asymmetry by the PDO is explored. Results show that, in the observational data, EN is 300% more (58% less) frequent than LN in positive (negative) PDO phases, which is significant at the 99% confidence level using the Monte Carlo test. Most of the CMIP5 models exhibit results that are consistent with the observational data.

Keywords

ENSO frequency asymmetry Pacific Decadal Oscillation decadal variation Monte Carlo method CMIP5 

摘要

本文利用观测资料和CMIP5多模式比较计划的19个模式的工业革命前参照试验数据, 分析了耦合模式对北太平洋年代际振荡(PDO)正负位相下El Niño和La Niña的模拟, 以及ENSO发生频率和PDO位相的关系. 观测中El Niño(La Niña)导致的赤道中东太平洋增温(降温)在PDO正(负)位相下强于负(正)位相, 模式并不能很好地模拟出这种差异. 对于ENSO发生频率在正负PDO位相下的不对称性, 观测显示在PDO正(负)位相下El Niño比La Niña多300%(少58%), 这个结果超过了99%的蒙特卡洛显著性检验. 多模式结果一致反映了观测中的这种现象, 也表明该结果是可信的.

关键词

ENSO发生频率的不对称性 北太平洋年代际振荡 年代际变化 蒙特卡罗方法 CMIP5模式 

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Notes

Acknowledgements

We appreciate the suggestions and comments from the two anonymous reviewers and the Editor, which helped to improve the quality of the original paper. This work was jointly supported by the National Key R&D Program of China (Grant No. 2017YFA0604201), the National Natural Science Foundation of China (Grant Nos. 41576019, 41606027 and 41706028), and the China Postdoctoral Science Foundation (Grant No. 2015M571095).

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Copyright information

© Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.International Center for Climate and Environment Sciences, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjingChina

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