In traditional practice, weather forecasts typically span up to two weeks, while climate forecasts begin at the seasonal timescale and extend further. Consequently, there exists a gap between weather and climate predictions in the subseasonal to seasonal (S2S) range. There is a growing demand within operational prediction and application communities for forecasts that bridge this gap, providing predictions between daily weather forecasts and seasonal climate outlooks. A global model with an unstructured grid mesh is utilized for this study to examine the forecast skill. Additionally, ensemble forecasting is taken into account, which involves running multiple simulations with slightly different initial conditions to capture uncertainties in the forecast. These ensemble forecasts are integrated for a period of 23 to 27 days, allowing for an extended prediction window beyond the typical forecast horizon. Results indicate that the model can give reasonable predictions on the development of a super Typhoon at lead times up to 10 days ahead of its peak intensity. Signal of a heat wave in southern China associated with the subsidence heating from TC outflow was also predicted reasonably well, despite variability among members existed due to disparity in the predicted TC tracks. Additionally, we carried out sensitivity tests on the use of radiation schemes on model cloud fraction. It is also found that the use of Xu and Randall generates more realistic cloud cover than Sundqvist, and resulting in greatly improving the evolution of synoptic scale weather systems over the western North Pacific consequentially.