Evaporation estimates are crucial to determine water availability for human use, analyze ecosystem productivity and species richness, and monitor agricultural needs for irrigation (Fisher et al. 2017). Moreover, quantifying the return flow of water from terrestrial surfaces to the atmosphere enables the detection of land use and climate impacts on the hydrological cycle (Dolman et al. 2014). Despite being seldom measured in situ and not directly observed from space, a range of datasets exists today to monitor evaporation at continental scales (McCabe et al. 2016; Miralles et al. 2016; Yo. Zhang et al. 2019). These datasets are hybrids between observations and modeling and have been used to study trends in hydrology and climate (Jung et al. 2010; Zhang et al. 2016; Cheng et al. 2017); impacts of climate oscillations (Miralles et al. 2014b; Martens et al. 2018); irrigation requirements (Anderson et al. 2015); and hydrometeorological extremes (Miralles et al. 2014a; Mu et al. 2013). Only a few of the existing datasets are produced in near-real time and, typically, only for specific continents (Ghilain et al. 2011; Anderson et al. 2011). Data for this analysis were obtained from the Global Land Evaporation Amsterdam Model (GLEAM; Miralles et al. 2011) version v3.2a (Martens et al. 2017), a simple land surface scheme run with satellite data. While not deliberately designed with an operational intent, GLEAM is updated with a few months’ latency and has been widely validated in multiple initiatives over the past few years (McCabe et al. 2016; Miralles et al. 2016).