Journal of the Meteorological Society of Japan. Ser. II
Online ISSN : 2186-9057
Print ISSN : 0026-1165
ISSN-L : 0026-1165
Article: Special Edition on DYAMOND: The DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains
Prediction Skill of the Boreal Summer Intra-Seasonal Oscillation in Global Non-hydrostatic Atmospheric Model Simulations with Explicit Cloud Microphysics
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2021 Volume 99 Issue 4 Pages 973-992


In this study, we assess the prediction skill of the Boreal Summer Intra-Seasonal Oscillation (BSISO) mode of one-month simulations using a global Non-hydrostatic Icosahedral Atmospheric Model (NICAM) with explicit cloud microphysics and a grid spacing of 14 km. The simulations were run as a series of hindcast experiments every day of August from 2000 to 2014. A total of 465 simulations were run with a 13950-day integration. Using forecast skill scores for statistical measurements, it was found that the model showed an overall BSISO prediction skill of approximately 24 days. The prediction skill tended to be slightly higher (∼ 2 days) when BSISO events began in the initial phases 7 to 1, which corresponded to the re-initiation phase of the BSISO, during which a major convective center over the Philippine Sea decayed and a new convective envelope began aggregating over the western Indian Ocean. The phase speed and the evolution of the amplitude of the BSISO were well simulated by the model with a clear northwest-southeastward tilted outgoing longwave radiation (OLR) structure over the Maritime Continent and the western Pacific. However, the propagation speed was slower during phases 6 and 7, and the amplitude of the BSISO largely decayed during phases 8–1, which is likely to have been associated with the stagnant behavior of the convective cells over the Philippines sea. Based on a regression coefficient analysis using the moist static energy, the stagnation of the propagation over the Philippines was found to be largely attributable to the small southerly background bias in the model over the Philippines. The bias in the large-scale circulation was likely to have been associated with the bias in the moisture field and the background monsoonal circulation. We concluded that the model physics controlling the background fields are important factors in improving BSISO prediction skill.

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© The Author(s) 2021. This is an open access article published by the Meteorological Society of Japan under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
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