MJO Prediction in the CWA GEPSv3: Model Performance and Physical Processes Underlying Simulation Errors

A multi-scale coupled framework has been implemented in the Central Weather Administration’s Global Ensemble Prediction System Version 3 (CWA GEPSv3) to improve extended-range forecasts over Taiwan. Reforecasts for January from 2001 to 2020 show skillful Madden–Julian Oscillation (MJO) predictions, with an average lead time of 17 days and a maximum of 33 days. The model realistically captures the eastward propagation of the MJO from the Indian Ocean to the Maritime Continent (MC) but fails to sustain its intensity beyond the MC due to a boundary-layer dry bias emerging 5–10 days before the convection center’s arrival.

Event-based analysis reveals that accurate MJO forecasts are more common during La Niña years, whereas poor forecasts occur more often during El Niño years. The low-frequency moisture field mitigates the dry bias over the MC during La Niñas, but amplifies it during El Niños. Ocean–atmosphere coupling enhances forecast skill at 20–30 lead days, and it is only pronounced for the good-prediction cases.

The boundary-layer dry bias over the MC primarily results from weak upward motion linked to insufficient meridional convergence. A modified dynamical core enhances the simulation of horizontal convergence, yielding clearer eastward propagation of MJO signals. These results elucidate the physical processes underlying model biases in GEPSv3 and provide practical guidance for improving subseasonal-to-seasonal forecasting.