Improved MJO Forecasts Using the Experimental Global‐Nested GFDL SHiELD Model

Sitting at the crossroads of weather and climate, the Madden-Julian Oscillation (MJO) is considered a primary source of subseasonal predictability. Despite its importance, numerical models struggle with MJO prediction as its convection moves through the complex Maritime Continent (MC) environment. Motivated by the ongoing effort to improve MJO prediction, we use the System for High-resolution prediction on Earth-to-Local Domains (SHiELD) model to run two sets of forecasts, one with and one without a nested grid over the MC. By efficiently leveraging high-resolution grid spacing, the nested grid reduces amplitude and phase errors and extends the model's predictive skill by about 10 days. These enhancements are tied to improvements in predicted zonal wind from the Indian Ocean to the Pacific, facilitated by westerly wind bias reduction in the nested grid. Results from this study suggest that minimizing circulation biases over the MC can lead to substantial advancements in skillful MJO prediction.