Improving Madden–Julian oscillation simulation in atmospheric general circulation models by coupling with a one-dimensional snow–ice–thermocline ocean model

Author:

Tseng Wan-LingORCID,Hsu Huang-Hsiung,Lan Yung-Yao,Lee Wei-LiangORCID,Tu Chia-YingORCID,Kuo Pei-Hsuan,Tsuang Ben-Jei,Liang Hsin-Chien

Abstract

Abstract. A one-column, turbulent, and kinetic-energy-type ocean mixed-layer model (snow–ice–thermocline, SIT), when coupled with three atmospheric general circulation models (AGCMs), yields superior Madden–Julian oscillation (MJO) simulations. SIT is designed to have fine layers similar to those observed near the ocean surface; therefore, it can realistically simulate the diurnal warm layer and cool skin. This refined discretization of the near-surface ocean in SIT provides accurate sea surface temperature (SST) simulation, and thus facilitates realistic air–sea interaction. Coupling SIT with the European Centre/Hamburg Model version 5, the Community Atmosphere Model version 5, and the High-Resolution Atmospheric Model significantly improved MJO simulation in three coupled AGCMs compared to the AGCM driven by a prescribed SST. This study suggests two major improvements to the coupling process. First, during the preconditioning phase of MJO over the Maritime Continent (MC), the often underestimated surface latent heat bias in AGCMs can be corrected. Second, during the phase of strongest convection over the MC, the change in intraseasonal circulation in the meridional circulation enhancing near-surface moisture convergence is the dominant factor in the coupled simulations relative to the uncoupled experiments. The study results show that a fine vertical resolution near the surface, which better captures temperature variations in the upper few meters of the ocean, considerably improves different models with different configurations and physical parameterization schemes; this could be an essential factor for accurate MJO simulation.

Funder

Ministry of Science and Technology, Taiwan

Publisher

Copernicus GmbH

Subject

General Medicine

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