Despite numerous efforts that have been undertaken to improve rainfall forecasts it still remains the most poorly forecasted meteorological variable. Errors in simulated rainfall arise as a result of errors in both initial conditions and numerical models. To compensate for these limitations, in recent years ensemble forecasting has been increasingly used. At first, ensembles were designed based on perturbed initial conditions, while recently use of mixed-physics and mixed-model ensembles for rainfall forecasting have been extensively investigated;The main objective of the present study was to help optimizing a mixed physics ensemble for warm season MCS rainfall forecasting by evaluating the impact that various physical schemes as well as their interactions have on rainfall forecasts. In addition, the work investigated how the impact of the physical schemes and their interaction changed when different initial conditions were used. For this purpose, high resolution (12-km grid spacing, 34 vertical levels) simulations from the Weather Research and Forecasting (WRF) model of 8 International H2O Project events were examined. For each event a matrix of 18 WRF model configurations was created by varying the convective parameterization scheme, the PBL scheme, and microphysical schemes. In order to quantify the impact of varying two different model physical schemes on the simulated rainfall field, the factor separation methodology was used.