Natural and artificial lakes are a common part of the landscape, and essential for human life, in their multiple uses for recreation, water supply for industry, irrigation and domestic use, energy generation, and so on; they also act as "sentinels" and integrators of terrestrial and atmospheric processes (Williamson et al., 2008), and play an important role in the emission of greenhouse gases to the atmosphere (DelSontro et al., 2018). The latent and sensible heat fluxes (and attendant water vapor mass flux) between the water surface of lakes and the atmosphere are needed as boundary conditions for atmospheric models and to quantify water losses. They are also used as boundary conditions in models for the evolution of the water temperature (see Hostetler & Bartlein, 1990), which plays a fundamental control on all biochemical processes occurring in the lake's body.For well-known hydrological and environmental reasons, therefore, reliable lake evaporation estimates remain at the center stage of water resources management, and even more so in the face of increased water demand and scarcity, and climate change (Veldkamp et al., 2017;Wang et al., 2018). Consequently, the need persists for reliable operational estimates of lake evaporation, that is, estimates than can use readily available environmental data and can be applied as widely as possible, at timescales ranging from daily to yearly.It is in the nature of the underlying physical processes, however, that the best flux measurements or model-based estimates are derived from data collected directly above the water surface: the physical basis for this fact is modernly provided by Monin-Obukhov Similarity Theory (MOST) (