As a dominant climate variability mode of the tropical atmosphere, the Madden-Julian Oscillation (MJO) plays a crucial role in the Earth’s hydrological and energy cycles. However, the MJO remains poorly represented in our state-of-the-art climate models, largely due to their inability to represent multi-scale convective interactions within the MJO envelope. These processes are further complicated by a barrier effect of the tropical landmass over the Maritime Continent (MC) on the eastward propagation of MJO convection. Large model uncertainties in representing MJO evolution over the MC region significantly limit our subseasonal-to-seasonal (S2S) predictive skill for global high-impact weather and environmental extremes.

By capitalizing on the newly developed global convection-permitting model at DOE, i.e., the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM), the main objectives of this proposed study include: 1) to comprehensively characterize the representation of multi-scale convective activity over the MC, including the diurnal cycle, mesoscale convective systems, and synoptic-scale equatorial waves, and their interactions with the MJO in the regionally-refined SCREAM at various horizontal resolutions; 2) to investigate how the two-way interactions between the MJO and multi-scale convective systems affect MJO maintenance and propagation over the MC. In addition to the lower-tropospheric moisture, a particular focus will be placed on possible roles of the lower-tropospheric temperature and boundary layer moist enthalpy perturbations for the MC barrier effect on MJO propagation based on the recently developed convection-buoyancy framework.

This project will contribute to the development of SCREAM by providing critical validation of SCREAM in representing multi-scale tropical convection. This project is also expected to advance our understanding of key processes underlying the MC barrier effect on MJO propagation, thus improve our S2S prediction skill for global extreme events. The proposed study is highly relevant to RGMA’s science topic on improved understanding and model representation of “modes of variability and extreme events."