When performing forecast verification, the observed values are commonly treated as "truth", and differences between the forecast and observed fields are generally attributed to model error. However, observational uncertainty can be large, particularly in complexly-derived fields such as the Quantitative Precipitation Estimates (QPE) from radar. These are typically used for computing the FSS. In this study, we make use of a new radar ensemble product that has been developed for the UK radar network, which accounts for the effects of random errors in the vertical profile of reflectivity (VPR) on the QPE derivation, yielding an ensemble of estimated rainfall rates. We use this radar ensemble in the precipitation verification of the operational Met Office UKV model, which provides deterministic forecasts for the UK at 1.5 km resolution. The range in FSS (rFSS) across the ensemble varies with the spatial scale and accumulation threshold considered, but early estimates indicate that it may be ~10% of the traditional single radar field score, and substantially larger at high accumulation thresholds. This evidence suggests that the (usually unaccounted for) effect of radar observational uncertainty on NWP verification metrics can be relatively large, and should be taken into account when assessing the relative performance of forecasts from different modelling systems, especially when using absolute accumulation thresholds.