• A comprehensive review and analysis of IMERG validation studies from 2016 to 2019. • There is robust representation of spatio-temporal patterns of precipitation. • Discrepancies can be found in extreme and light precipitation, and the winter season. • The 30-min scale has not yet been sufficiently evaluated. • Using IMERG in hydrological simulation results to high variance in their performance. Accurate, reliable, and high spatio-temporal resolution precipitation data are vital for many applications, including the study of extreme events, hydrological modeling, water resource management, and hydroclimatic research in general. In this study, we performed a systematic review of the available literature to assess the performance of the Integrated Multi-Satellite Retrievals for GPM (IMERG) products across different geographical locations and climatic conditions around the globe. Asia, and in particular China, are the subject of the largest number of IMERG evaluation studies on the continental and country level. When compared to ground observational records, IMERG is found to vary with seasons, as well as precipitation type, structure, and intensity. It is shown to appropriately estimate and detect regional precipitation patterns, and their spatial mean, while its performance can be improved over mountainous regions characterized by orographic precipitation, complex terrains, and for winter precipitation. Furthermore, despite IMERG's better performance compared to other satellite products in reproducing spatio-temporal patterns and variability of extreme precipitation, some limitations were found regarding the precipitation intensity. At the temporal scales, IMERG performs better at monthly and annual time steps than the daily and sub-daily ones. Finally, in terms of hydrological application, the use of IMERG has resulted in significant discrepancies in streamflow simulation. However, and most importantly, we find that each new version that replaces the previous one, shows substantial improvement in almost every spatiotemporal scale and climatic condition. Thus, despite its limitations, IMERG evolution reveals a promising path for current and future applications.

Like civilization and technology, our understanding of the global water cycle has been continuously evolving, and we have adapted our quantification methods to better exploit new technological resources. The accurate quantification of global water fluxes and storages is crucial in studying the global water cycle. These fluxes and storages physically interact with each other, are related through the water budget, and are constrained by it. First attempts to quantify them date back to the early 1900s, and during the past few decades, they have received an increasing research interest, which is reflected in the vast amount of data sources available nowadays. However, these data have not been comprehensive enough due to the high spatiotemporal variability of the global water cycle. Herein, we provide a comprehensive review of the chronological evolution of global water cycle quantification, the distinct data sources and methods used, and a critical assessment of their contribution to improving the spatiotemporal monitoring of the global water cycle. The chronology of global water cycle components shows that the uncertainty of flux estimates over oceans remains higher than that over land. Comparing the standard deviation and the interquartile range of the estimates from the 2000s onward with those from all the estimates (1905-2019), we can affirm that statistical variability has diminished in recent years. Moreover, the variability of ocean precipitation and evaporation estimates from the 2000 onward was reduced by more than 70% compared with earlier studies. These findings advocate that the consistency of global water cycle quantification has been improved.