Assessing the Impact of Satellite Sea Surface Salinity Assimilation on Predicting the MJO Propagation across Maritime Continent in NASA GEOS-S2S-2 Model

Abstract The assimilation of satellite sea surface salinity (SSS) has been acknowledged to improve the upper-ocean stratification and the relevant oceanic processes. In this study, we focus on assessing the impact of SSS assimilation on predicting the Madden–Julian oscillation (MJO) propagation across the Maritime Continent for eight representative MJO cases using the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System (GEOS) subseasonal to seasonal (S2S) prediction system, version 2 (GEOS-S2S-2). Two sets of forecast experiments are performed: one initialized from the operational ocean analysis without SSS assimilation, referred to as control (CTL), and the other initialized from the ocean analysis with SSS assimilation (SSS). Evaluated with the large-scale precipitation tracking method for these eight MJO events, the SSS forecasts outperform the CTL forecasts, showing better agreement with the observed eastward propagation over the Maritime Continent. In the SSS forecasts, the deeper mixed-layer depth (MLD) and greater upper-ocean heat content (OHC) result in reduced surface cooling during MJO convection. This leads to higher sea surface temperature (SST) compared to the CTL, which enhances latent heat flux anomalies via wind convergence and further supports MJO propagation. Based on the results of these representative MJO cases, this study suggests that improved initialization of ocean stratification and OHC in the upper ocean, enabled by SSS assimilation, can help partially overcome the MJO Maritime Continent prediction barrier and thus strengthen subseasonal forecast skills.