Evaluating SST Forcing Effects on Extended-Range Forecast Skills of CMA-GEPS

Madden–Julian Oscillation (MJO) is one of the dominant source of extended-range atmospheric predictability. However, many atmospheric numerical models fail to predict MJO owing to limitations in representing air–sea interaction processes. This study investigated the role of sea surface temperature (SST) forcing in improving MJO predictability using the China Meteorological Administration uncoupled Global Ensemble Prediction System (CMA-GEPS), extending forecasts from 16 to 35 days for the first time by applying different SST forcing schemes. Three SST forcing schemes were examined: (1) CTL SST, which uses fixed SST forcing, (2) E-Folding SST, which adjusts initial analyses toward observed climatology, relying primarily on the historical observations, and (3) Two-Tiered SST, which combines the bias-corrected SST analysis and predictions from the CMA coupled prediction system. The results confirmed that each SST forcing scheme is reasonably designed, with the Two-Tiered scheme providing better SST forcing information and more realistic equatorial wave features. For MJO prediction, the Two-Tiered scheme exhibits superior skill, particularly with strong MJO initialization, extending predictability to 20.6 days, i.e., 4.7 days longer than the CTL run and 3.4 days longer than the E-Folding test. Furthermore, the Two-Tiered scheme outperforms CTL and E-Folding over the western Indian Ocean, but it underperforms over the Maritime Continent, exhibiting poorer eastward propagation characteristics and larger MJO errors, owing to larger SST forcing errors mainly from the analysis-related errors of the coupled model. Larger SST forcing errors increase the water vapor biases and amplify MJO prediction errors, indicating the need for optimized SST forcing. Additionally, the Two-Tiered scheme significantly enhances anomaly correlation coefficient (ACC) skills for 500-hPa geopotential height, with the improvement closely linked to the improvement in MJO forecast skill. Overall, even the one-way SST forcing that includes multi-faceted information of the coupled model can provide guidance for extended-range prediction with atmospheric only numerical models.