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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 The inverse temperature layer (ITL) beneath water‐atmosphere interface within which temperature increases with depth has been observed from measurement of water temperature profile at an inland lake. Strong solar radiation combined with moderate wind‐driven near‐surface turbulence leads to the formation of a pronounced diurnal cycle of the ITL predicted by a physical heat transfer model. The ITL only forms during daytime when solar radiation intensity exceeds a threshold while consistently occurs during nighttime. The largest depth of the ITL is comparable to thee‐fold penetration depth of solar radiation during daytime and at least one order of magnitude deeper during nighttime. The dynamics of the ITL depth variation simulated by a physical model forced by observed water surface solar radiation and temperature is confirmed by the observed water temperature profile in the lake. 

Abstract Microbes are known to shape topographies; however, mechanisms of biofilm‐sediment interactions and the dynamic evolution of biofilm‐covered bedforms remain poorly understood. Here, we explore the effects of synthetic biofilms on the geometry and temporal evolution of underwater bedforms through flume experiments. Our results demonstrate that synthetic biofilms can produce sedimentary structures similar to those formed by natural microbes, including wrinkles, pits, flip‐overs, roll‐ups, mat chips, and erosional edges. We observed the formation of wrinkles, a common geological feature, due to the accumulation of sand grains on the biofilms. Furthermore, we demonstrated that biofilms can reduce bed roughness by an order of magnitude in the low flow regime. However, the subsequent biofilm‐sediment interactions can increase local bedform size, forming multi‐scale geometries of bedforms. Our study improves the fundamental understanding of the landscape dynamics of bedforms covered by natural biofilms. 

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. 

Abstract An “inverse‐temperature layer” (ITL) of water temperature increasing with depth is predicted based on physical principles and confirmed by in situ observations. Water temperature and other meteorological data were collected from a fixed platform in the middle of a shallow inland lake. The ITL persists year‐around with its depth on the order of one m varying diurnally and seasonally and shallower during daytimes than nighttimes. Water surface heat flux derived from the ITL temperature distribution follows the diurnal cycle of solar radiation up to 300 W m⁻²during daytime and down to 50 W m⁻²during nighttime. Solar radiation attenuation in water strongly influences the ITL dynamics and water surface heat flux. Water surface heat flux simulated by two non‐gradient models independent of temperature gradient, wind speed and surface roughness using the data of surface temperature and solar radiation is in close agreement with the ITL based estimates.