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Abstract Modeling evaporationEfrom inland water bodies is challenging largely due to the uncertainties of input data, particularly surface water temperature that plays a key role in the available energy, i.e., net radiationR_nminus rate of water heat storage changeG. The equilibrium temperature approach (ETA) for estimating water surface temperature offers an alternative method to calculateR_nandGusing standard meteorological data. This study evaluates the global lakeEestimates from the widely used Penman model (PM) coupled with the ETA (PM-ETA) against field observations and model simulations from the Lake, Ice, Snow, and Sediment Simulator (LISSS). Our analysis reveals that the PM-ETA tends to overestimateEby approximately 36% and 24% compared to observations and the LISSS simulations, respectively, despite being driven by the same input data. The biases of the PM-ETAEare more pronounced in the cold and polar regions with distinct seasonality ofR_nandG. Furthermore, theEtrends from the PM-ETA deviate from the LISSS simulations over the period of 2001–16 due to the bias trends in the available energy. By incorporating the LISSS-simulatedR_nandGinto the PM, the bias inEis reduced to less than ±5% compared to the LISSS results. This study highlights the need to improve the available energy input of the PM to improve the estimates of global lakeEfor better water resource management and planning. Significance StatementThis study addresses a crucial challenge in modeling evaporationEfrom inland water bodies—uncertainties in surface water temperature and available energy inputs, particularly net radiationR_nand rate of heat storage changeG. By evaluating the widely used Penman model (PM) coupled with the equilibrium temperature approach (ETA), we reveal a tendency for the PM-ETA to overestimateEglobally, with the largest biases observed in cold and polar regions. Incorporating higher-qualityR_nandGestimates from the Lake, Ice, Snow, and Sediment Simulator (LISSS) significantly reduces these biases. These findings highlight the importance of alternative higher-quality data products for available energy inputs for improvingEestimates by the PM. 

Abstract How convective boundary‐layer (CBL) processes modify fluxes of sensible (SH) and latent (LH) heat and CO₂(F_c) in the atmospheric surface layer (ASL) remains a recalcitrant problem. Here, large eddy simulations for the CBL show that whileSHin the ASL decreases linearly with height regardless of soil moisture conditions,LHandF_cdecrease linearly with height over wet soils but increase with height over dry soils. This varying flux divergence/convergence is regulated by changes in asymmetric flux transport between top‐down and bottom‐up processes. Such flux divergence and convergence indicate that turbulent fluxes measured in the ASL underestimate and overestimate the “true” surface interfacial fluxes, respectively. While the non‐closure of the surface energy balance persists across all soil moisture states, it improves over drier soils due to overestimatedLH. The non‐closure does not imply thatF_cis always underestimated;F_ccan be overestimated over dry soils despite the non‐closure issue. 

Abstract Top‐down entrainment shapes the vertical gradients of sensible heat, latent heat, and CO₂fluxes, influencing the interpretation of eddy covariance (EC) measurements in the unstable atmospheric surface layer (ASL). Using large eddy simulations for convective boundary layer flows, we demonstrate that decreased temperature gradients across the entrainment zone increase entrainment fluxes by enhancing the entrainment velocity, amplifying the asymmetry between top‐down and bottom‐up flux contributions. These changes alter scalar flux profiles, causing flux divergence or convergence and leading to the breakdown of the constant flux layer assumption (CFLA) in the ASL. As a result, EC‐measured fluxes either underestimate or overestimate “true” surface fluxes during divergence or convergence phases, contributing to energy balance non‐closure. The varying degrees of the CFLA breakdown are a fundamental cause for the non‐closure issue. These findings highlight the underappreciated role of entrainment in interpreting EC fluxes, addressing non‐closure, and understanding site‐to‐site variability in flux measurements. 

Abstract Evaporation ( E ) from about 300 million lakes worldwide without plant physiological constraints directly reflects hydrological response to atmospheric forcings. However, it remains inadequately understood about what regulate spatial variability of global lake E across seasons. Here we show that vertical vapor pressure difference ( e D ) accounts for 66% of the spatial variability of annual E , followed by wind speed (16%). The e D is also the predominant factor modulating diurnal variability in E and causing greater E at night than during the daytime. As a consequence, spatial variability in nighttime E strongly regulates that in global E across seasons. Therefore, the observed widespread, heterogeneous changes in lake surface temperature that imply spatial variability in e D may have contributed to changes in global E variability.