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Miyakawa T, Satoh M, Miura H, et al. Madden-Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer. Nat Commun. 2014;5:3769doi: 10.1038/ncomms4769.
Miyakawa, T., Satoh, M., Miura, H., Tomita, H., Yashiro, H., Noda, A. T., Yamada, Y., Kodama, C., Kimoto, M., & Yoneyama, K. (2014). Madden-Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer. Nature communications, 53769. https://doi.org/10.1038/ncomms4769
Miyakawa, Tomoki, et al. "Madden-Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer." Nature communications vol. 5 (2014): 3769. doi: https://doi.org/10.1038/ncomms4769
Miyakawa T, Satoh M, Miura H, Tomita H, Yashiro H, Noda AT, Yamada Y, Kodama C, Kimoto M, Yoneyama K. Madden-Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer. Nat Commun. 2014 May 06;5:3769. doi: 10.1038/ncomms4769. PMID: 24801254; PMCID: PMC4024761.
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Nat Commun. 2014 May 06;5:3769. doi: 10.1038/ncomms4769.

Madden-Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer.

Nature communications

Tomoki Miyakawa, Masaki Satoh, Hiroaki Miura, Hirofumi Tomita, Hisashi Yashiro, Akira T Noda, Yohei Yamada, Chihiro Kodama, Masahide Kimoto, Kunio Yoneyama

Affiliations

  1. Japan Agency for Marine-Earth Science and Technology, Yokosuka 237-0061, Japan.
  2. 1] Japan Agency for Marine-Earth Science and Technology, Yokosuka 237-0061, Japan [2] Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa 277-8568, Japan.
  3. 1] Japan Agency for Marine-Earth Science and Technology, Yokosuka 237-0061, Japan [2] Department of Earth and Planetary Science, The University of Tokyo, Tokyo 113-0033, Japan.
  4. 1] Japan Agency for Marine-Earth Science and Technology, Yokosuka 237-0061, Japan [2] Advanced Institute for Computational Science, RIKEN, Kobe 650-0047, Japan.
  5. Advanced Institute for Computational Science, RIKEN, Kobe 650-0047, Japan.
  6. Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa 277-8568, Japan.

PMID: 24801254 PMCID: PMC4024761 DOI: 10.1038/ncomms4769

Abstract

Global cloud/cloud system-resolving models are perceived to perform well in the prediction of the Madden-Julian Oscillation (MJO), a huge eastward -propagating atmospheric pulse that dominates intraseasonal variation of the tropics and affects the entire globe. However, owing to model complexity, detailed analysis is limited by computational power. Here we carry out a simulation series using a recently developed supercomputer, which enables the statistical evaluation of the MJO prediction skill of a costly new-generation model in a manner similar to operational forecast models. We estimate the current MJO predictability of the model as 27 days by conducting simulations including all winter MJO cases identified during 2003-2012. The simulated precipitation patterns associated with different MJO phases compare well with observations. An MJO case captured in a recent intensive observation is also well reproduced. Our results reveal that the global cloud-resolving approach is effective in understanding the MJO and in providing month-long tropical forecasts.

References

  1. Science. 2007 Dec 14;318(5857):1763-5 - PubMed
  2. Nature. 2008 May 15;453(7193):268-9 - PubMed

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