The aim of data-impact studies at the UK Met. Office is to investigate how observations affect the accuracy of model forecasts. Results from such experiments provide useful evidence on which to base the design of observational networks. This project, using a case study approach, investigated the relative benefit of different observation types within The Met. Office's Mesoscale Model domain on forecasts of three-hourly precipitation accumulation over the UK up to 12 hours ahead. The method used assesses the impact of assimilating single observation types, or a limited combination of types, where impact is measured against a control forecast obtained after a dummy assimilation using no observations. In experiments for 13 case studies, the observation types that most frequently provided a beneficial impact when presented alone to the assimilation were sonde data, surface data and data from the Moisture Observation Processing System (MOPS).