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Tropical intraseasonal oscillation simulated in an AMIP-type experiment by NICAM

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Abstract

It is the first time for the non-hydrostatic icosahedral atmospheric model (NICAM), at a horizontal mesh size of approximately 14-km, to conduct a continuous long-term Atmospheric Model Intercomparison Project-type simulation. This study examines the performance of NICAM in simulating the tropical intraseasonal oscillation (ISO) from a statistical point of view using 30-year data (1979–2008) in the context of the bimodal ISO representation concept proposed by Kikuchi et al., which allows us to examine the seasonally varying behavior of the ISO in great detail, in addition to the MJO working group level 2 diagnostics. It is found that many of the fundamental features of the ISO are well captured by NICAM. The evolution of the ISO convection as well as large-scale circulation over the course of its life cycle is reasonably well reproduced throughout the year. As in the observation, the Madden–Julian oscillation (MJO) mode, characterized by prominent eastward propagation of convection, is predominant during boreal winter, whereas the boreal summer ISO (BSISO) mode, by a combination of pronounced eastward and northward propagation, during summer. The overall shape of the seasonal cycle as measured by the numbers of significant MJO and BSISO days in a month is relatively well captured. Two major biases, however, are also identified. The amplitude of the simulated ISO is weaker by a factor of ~2. Significant BSISO events sometimes appear even during winter (December–April), amounting to ~30 % of the total significant ISO days as opposed to ~2 % in the observation. The results here warrant further studies using the simulation dataset to understand not only many aspects of the dynamics and physics of the ISO but also its role in weather and climate. It is also demonstrated that the concept of the bimodal ISO representation provides a useful framework for assessing model’s capability to simulate, and illuminating model’s deficiencies in reproducing, the ISO. The nature and causes of the two major biases are also discussed.

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Notes

  1. “K” stands for a Japanese word “Kei” meaning ten peta.

  2. The bimodal ISO index data as well as plots is available at http://iprc.soest.hawaii.edu/users/kazuyosh/Bimodal_ISO.html.

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Acknowledgments

We thank anonymous reviewers for their valuable comments that helped improve the quality of the original manuscript. KK acknowledge the support of NOAA Grant NA13OAR4310165 and NSF Grant AGS-1005599. Additional support was provided by the JAMSTEC through its sponsorship of research activities at the IPRC (JICS). The NICAM simulation was performed on the K computer at the RIKEN Advanced Institute for Computational Science (Proposal number hp120279, hp130010 and hp140219) and supported by Strategic Programs for Innovative Research (SPIRE) Field 3 (Projection of Planet Earth Variations for Mitigating Natural Disasters), which is promoted by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.

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Authors and Affiliations

  1. International Pacific Research Center, University of Hawai‘i, 1680 East West Road, POST Bldg. 401, Honolulu, HI, 96822, USA

    Kazuyoshi Kikuchi

  2. Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan

    Chihiro Kodama, Tomoe Nasuno, Masuo Nakano, Masaki Satoh, Akira T. Noda & Yohei Yamada

  3. University of Tokyo, Tokyo, Japan

    Hiroaki Miura

  4. Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan

    Masaki Satoh

Authors
  1. Kazuyoshi Kikuchi
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  2. Chihiro Kodama
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  3. Tomoe Nasuno
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  4. Masuo Nakano
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  5. Hiroaki Miura
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  6. Masaki Satoh
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  7. Akira T. Noda
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  8. Yohei Yamada
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Corresponding author

Correspondence to Kazuyoshi Kikuchi.

Additional information

School of Ocean and Earth Science and Technology Contribution Number 9646 and International Pacific Research Center Contribution Number 1201.

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Kikuchi, K., Kodama, C., Nasuno, T. et al. Tropical intraseasonal oscillation simulated in an AMIP-type experiment by NICAM. Clim Dyn 48, 2507–2528 (2017). https://doi.org/10.1007/s00382-016-3219-z

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  • DOI: https://doi.org/10.1007/s00382-016-3219-z

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