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

Tomoki Miyakawa (), Masaki Satoh, Hiroaki Miura, Hirofumi Tomita, Hisashi Yashiro, Akira T. Noda, Yohei Yamada, Chihiro Kodama, Masahide Kimoto and Kunio Yoneyama
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Tomoki Miyakawa: Japan Agency for Marine-Earth Science and Technology
Masaki Satoh: Japan Agency for Marine-Earth Science and Technology
Hiroaki Miura: Japan Agency for Marine-Earth Science and Technology
Hirofumi Tomita: Japan Agency for Marine-Earth Science and Technology
Hisashi Yashiro: Advanced Institute for Computational Science, RIKEN
Akira T. Noda: Japan Agency for Marine-Earth Science and Technology
Yohei Yamada: Japan Agency for Marine-Earth Science and Technology
Chihiro Kodama: Japan Agency for Marine-Earth Science and Technology
Masahide Kimoto: Atmosphere and Ocean Research Institute, The University of Tokyo
Kunio Yoneyama: Japan Agency for Marine-Earth Science and Technology

Nature Communications, 2014, vol. 5, issue 1, 1-6

Abstract: 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.

Date: 2014
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DOI: 10.1038/ncomms4769

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