The last several years have seen the development of a number of new satellite-derived, globally complete, high resolution precipitation products with a spatial resolution of at least 0.25° and a temporal resolution of at least three-hourly. These products generally merge geostationary infra-red data and polar-orbiting passive microwave data to take advantage of the high sampling of the infra-red and the superior quality of the microwave. The Project to Evaluate High Resolution Precipitation Products (PEHRPP) was established to evaluate and inter-compare these 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.

As part of this project, we have performed a sub daily inter-comparison of five high resolution datasets (commonly known as CMORPH, TMPA, NRL-Blended, the Hydro-Estimator and PERSIANN) with existing sub-daily gauge data over the US and the Pacific Ocean. The results show that these datasets are surprisingly good at representing high resolution precipitation, with correlations against three-hourly gauge data as high 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.