Evaluation of the MJO ENSO Relationship in UFS Forecasts

This study investigates the performance of the Unified Forecast System (UFS) global coupled model to forecast the relationship between the Madden-Julian Oscillation (MJO) and El Nino Southern Oscillation (ENSO) through the calculation of the MaKE and MaKI indices, developed in the ocean-atmosphere energetic framework. The MaKE index describes the covariability of MJO, Kelvin wave activity, and ENSO. The MaKI index characterizes the influence of MJO and Kelvin wave activity on ENSO through the wind power. The indices are calculated through the MJO components of meridional and zonal wind stress, the Kelvin components of meridional and zonal ocean surface currents, and sea surface temperature daily anomalies. UFS reforecasts of April 2011-March 2018 are used. Each reforecast has 35-day forecast leads, which poses challenges for isolating the MJO component of wind stress. To address this limitation, a novel filtering approach using a convolutional neural network (CNN) artificial intelligence model was implemented to capture the intraseasonal variability of the wind stress anomalies. The results show that the UFS reforecasts are able to capture the MJO-ENSO interaction, however the amplitude of the MaKE and MaKI indices are larger than in the observations. The forecast skill of using MaKE as an ENSO predictor will also be compared with the skill based on the Nino3.4 index.