An assessment is presented on the relative forecast impact on the performance of a numerical weather prediction (NWP) model from eight different observation data types (aircraft, profiler, radiosonde, VAD (velocity azimuth display), GPS precipitable water, METAR (surface), surface mesonet, and satellite-based AMVs (atmospheric motion vectors). A series of observation sensitivity experiments (OSEs) was conducted using the Rapid Update Cycle (RUC) model/assimilation system in which various data sources were denied to assess the relative importance of the different data types for short-range (3-12h) wind, temperature, and relative humidity forecasts at different vertical levels and at the surface. These experiments were conducted for two 10-day periods, one in November-December 2006 and one in August 2007. These experiments show positive short-range forecast impacts from most of the contributors to the heterogeneous observing system over the RUC domain. In particular, aircraft observations had the largest overall impact for forecasts initialized 3-6 h before 0000 or 1200 UTC, considered over the full depth (1000-100 hPa), followed by radiosonde observations, even though the latter are available only every 12h. Profiler data, GPS-precipitable water estimates, and surface observations also led to significant improvements in short-range forecast skill.