Abstract: This study adopts the GEOS-5 Nature Run (G5NR) dataset released by the Global Modeling and Assimilation Office (GMAO) of the National Aeronautics and Space Administration (NASA). Using the Weather Research and Forecasting (WRF) model and Gridpoint Statistical Interpolation (GSI) assimilation system, we design observing system simulation experiment (OSSE) for the vertical observation network composed of wind profiler radars and ground-based microwave radiometers over the Yangtze River Delta. A typical precipitation event forecast is analyzed and evaluated with two layouts of observation networks featuring different station densities for the above two instruments. The results show that assimilating wind profiler radar data yields positive effects on wind field forecasts, with effective improvement limited to within 12 h. The assimilation of microwave radiometer data remarkably improves temperature and humidity field forecasts. Its favorable effects on humidity fields extend from the surface to above 400 hPa and last up to 24 h. In terms of precipitation verification, assimilating microwave radiometer data increases the Threat Score (TS) for light to moderate rain, while no noticeable improvement is found for heavy rain and above. The conclusions can provide references for the assessment of current observation networks and the design of future network layouts.