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.

Automated summary

Despite the well-recognized initial value nature of subseasonal forecasts, the impact of subsurface ocean initialization in subseasonal forecasts has not been fully explored. This study investigates the role of ocean in situ data assimilation on the propagation of MJO events across the Maritime Continent in the ECMWF subseasonal forecast system. The results show that ocean initialization with in situ data assimilation does not improve the relatively low MJO forecast skill across the Maritime Continent. Bias in the atmospheric model is found to be a major factor contributing to the forecast error, suggesting that improving the atmospheric circulation bias should be a target for enhancing the ECMWF subseasonal forecast model.