Runoff and flash flood generation are very sen- sitive to rainfall’s spatial and temporal variability. The in- creasing use of radar and satellite data in hydrological ap- plications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowl- edge of the uncertainties of these data. In 2011, a new super- dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4km2 study area near Kibbutz Galed in northern Israel. This net- work was established for a detailed exploration of the un- certainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year’s record collected from this network and from the Shacham weather radar, located 63km from the study area. The gauge–rainfall spatial cor- relation and uncertainty were examined along with the esti- mated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale) and increased as the timescale increased. The variance reduction factor (VRF), representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF<5%) on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total dif- ference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27dB for 3 min timescale to 3.21dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications of the radar data. Rainfall measurements collected with this dense rain gauge network will be used for further examination of small-scale rainfall’s spatial and temporal variability in the coming years.