Assessing the Impact of Ocean In Situ Observations on MJO Propagation Across the Maritime Continent in ECMWF Subseasonal Forecasts.

Despite the well‐recognized initial value nature of the subseasonal forecasts, the role of subsurface ocean initialization in subseasonal forecasts remains underexplored. Using observing system experiments, this study investigates the impact of ocean in situ data assimilation on the propagation of Madden–Julian Oscillation (MJO) events across the Maritime Continent in the European Centre for Medium‐Range Weather Forecasts (ECMWF) subseasonal forecast system. Two sets of twin experiments are analyzed, which only differ on the use or not of in situ ocean observations in the initial conditions. Besides using the Real‐time Multivariate MJO Index (RMMI) to evaluate the forecast performance, we also develop a new MJO tracking method based on outgoing longwave radiation anomalies (OLRa) for forecast evaluation. We find that the ocean initialization with in situ data assimilation, though having an impact on the forecasted ocean mean state, does not improve the relatively low MJO forecast skill across the Maritime Continent. Moist static energy budget analysis further suggests that a significant underestimation in the meridional moisture advection in the model forecast may hinder the potential role played by the ocean state differences associated with data assimilation. Bias of the intraseasonal meridional winds in the model is a more important factor for such underestimation than the mean state moisture biases. This finding suggests that atmospheric model biases dominate the forecast error growth, and the atmospheric circulation bias is one of the major sources of the MJO prediction error and should be a target for improving the ECMWF subseasonal forecast model. Plain Language Summary: Assimilating ocean subsurface observations can provide a better ocean state estimate for initializing weather and climate forecast in models. This study assesses the impact of the ocean subsurface data assimilation on subseasonal forecasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF). For the subseasonal prediction, the Madden–Julian Oscillation (MJO)—the dominant tropical atmospheric variability at the subseasonal time scale—is commonly used to evaluate the model skill. This study specifically focuses on the MJO propagation across the Maritime Continent. By using two quantitative methods, we find ocean in situ observations have no impact on forecasting the MJO propagation. Furthermore, we find the coupled forecast model has atmospheric biases in its meridional wind field, which leads to an underestimation in the meridional moisture advection, thus potentially reducing the MJO prediction skill. Such an atmospheric origin of the model error may hinder the potential impact of ocean subsurface data assimilation. While previous research emphasized the importance of improving the mean state moisture representation in the model for MJO forecast, our findings emphasize the importance of improving the meridional wind representation. Key Points: Ocean in situ data assimilation has an impact on subseasonal sea surface temperature forecasts but has little impact on forecasting Madden–Julian Oscillation (MJO) propagation across Maritime ContinentMoist static energy budget analysis reveals that the MJO forecast errors are likely due to the underestimated meridional moisture advectionThe intraseasonal meridional wind biases contribute more to the underestimated meridional moisture advection than the systematic dry biases [ABSTRACT FROM AUTHOR]