Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model: Part I. Effect on the maximum prediction error

PENG Yuehua; SONG Junqiang; XIANG Jie; SUN Chengzhi

doi:10.1007/s13131-015-0665-0

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Article Navigation > Acta Oceanologica Sinica > 2015 > 34(5): 39-45

PENG Yuehua, SONG Junqiang, XIANG Jie, SUN Chengzhi. Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model: Part I. Effect on the maximum prediction error[J]. Acta Oceanologica Sinica, 2015, 34(5): 39-45. doi: 10.1007/s13131-015-0665-0

Citation:

PENG Yuehua, SONG Junqiang, XIANG Jie, SUN Chengzhi. Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model: Part I. Effect on the maximum prediction error[J]. Acta Oceanologica Sinica, 2015, 34(5): 39-45. doi: 10.1007/s13131-015-0665-0

Citation:

PENG Yuehua, SONG Junqiang, XIANG Jie, SUN Chengzhi. Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model: Part I. Effect on the maximum prediction error[J]. Acta Oceanologica Sinica, 2015, 34(5): 39-45. doi: 10.1007/s13131-015-0665-0

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Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model: Part I. Effect on the maximum prediction error

doi: 10.1007/s13131-015-0665-0

1.
Dalian Naval Academy, Dalian 116018, China;Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
2.
College of Computer, National University of Defense Technology, Changsha 410073, China
3.
College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China
4.
Dalian Naval Academy, Dalian 116018, China

Received Date: 2013-09-06
Rev Recd Date: 2014-12-25

Abstract

Abstract

With the observational wind data and the Zebiak-Cane model, the impact of Madden-Julian Oscillation (MJO) as external forcing on El Niño-Southern Oscillation (ENSO) predictability is studied. The observational data are analyzed with Continuous Wavelet Transform (CWT) and then used to extract MJO signals, which are added into the model to get a new model. After the Conditional Nonlinear Optimal Perturbation (CNOP) method has been used, the initial errors which can evolve into maximum prediction error, model errors and their join errors are gained and then the Niño 3 indices and spatial structures of three kinds of errors are investigated. The results mainly show that the observational MJO has little impact on the maximum prediction error of ENSO events and the initial error affects much greater than model error caused by MJO forcing. These demonstrate that the initial error might be the main error source that produces uncertainty in ENSO prediction, which could provide a theoretical foundation for the adaptive data assimilation of the ENSO forecast and contribute to the ENSO target observation.
- El Niñ,
- o-Southern Oscillation (ENSO),
- Madden-Julian Oscillation (MJO),
- maximum prediction error

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References(25)

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