The Project to Evaluate High Resolution Precipitation Products (PEHRPP) was established to evaluate and inter-compare high-resolution satellite datasets at a variety of spatial and temporal resolutions with the intent of guiding dataset developers and informing the user-community as to the most useful products. Here, we show a summary of recent results from a sub-daily comparison against gauge data and a large-scale comparison against existing monthly products. The sub-daily inter-comparison of five high resolution datasets (commonly known as CMORPH, TMPA, NRL-Blended, the Hydro-Estimator and PERSIANN) with sub-daily gauge data over the US and the Pacific Ocean shows that the products have considerable skill at sub-daily time-scales, with correlations against three-hourly gauge data as high as 0.7 for some datasets. In general, CMORPH yields the highest correlations against the gauges used, although the TMPA yields the lowest biases due to the gauge correction applied as part of the algorithm. For the large-scale comparison, the same high resolution datasets (plus GSMaP) were aggregated to monthly, 2.5 degree means and compared with GPCP, CMAP and other datasets at this time/space scale. Preliminary results show that some of the high-resolution datasets are in surprisingly good agreement with more established datasets at this coarse resolution and that they are capable of reproducing modes seen in large-scale datasets such as ENSO. Unsurprisingly, discontinuities remain in varying degrees in each product that make some unsuitable for studies of longer-term climate, such as trends in extremes.