Datasets containing time series of fields of precipitation over the globe are vital to studies of seasonal-to-interannual climate variability, the validation of model predictions of such variability, and the identification of longer time-scale trends. Such climatologies cannot be based solely on rain gauges, due to their poor spatial sampling, and must use satellite-derived estimates of precipitation as well. In this paper, we will describe the various estimates of precipitation that can be used to create global climatologies and the methodologies that have been developed to do so. We will present examples of the datasets produced, and illustrate their utility. We will conclude with a discussion of the shortcomings of the present datasets, and describe the developments required to overcome them.