Rainfall is highly variable in space and time, depending on the synoptic, mesoscale and storm-scale forcing. This variability affects our capability to measure rainfall from in-situ as well as remote-sensing perspectives. The lack of continuous observations in space and time requires a merging of information obtained from various sources. The variability of rainfall within the range of sensor resolution differences, however, has a significant effect on the comparison between observations made by instruments with differing resolutions in space and time. For example, a radar and rain gauge may both measure rainfall perfectly and accurately, from an instrument and retrieval perspective, yet they do not record the same phenomena. The rainfall amounts estimated by both types of instruments will likly be burdened by measurement limitations and uncertainties. One key question is how much of the observed variance between radar and gauge observations can be explained simply by sensor resolution differences combined with space-time variability of rainfall?

Detailed observations of rainfall at high resolution in space and time have been carried out for the 21 km^2 Goodwin Creek research watershed in northern Mississippi. The comprehensive setup of instrumentation includes more than 30 rain gauges (above ground and buried), two disdrometers, and observations of the wind profile at the climate station in the center of the catchment. In addition, very-high resolution radar observations (50 m by 1 degree in space, tens of seconds in time) have been made for a selection of storms passing over this area. These data will be used to evaluate measurement issues from the rain gauge catch (wind exposure) to radar rainfall estimation (Z-R, hail). The rainfall variability observed at very small space and time scales will show how this variability affects the radar-gauge comparison and thus provide guidance for effectively merging that information to yield the best surface rainfall estimates.