Search for: All records

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 Surface moisture heterogeneity degrades temperature‐humidity (‐) similarity in the atmospheric surface layer, yet the underlying physical mechanisms driving this dissimilarity remain underexplored. This study employs large‐eddy simulations coupled with a land‐surface model to investigate ‐ similarity in the convective boundary layer (CBL) over surfaces with varying scales of surface moisture heterogeneity. Results reveal that as the heterogeneity scale increases, patch‐scale thermally induced circulations develop and interact with cellular turbulent organized structures, significantly altering scalar transport and turbulence dynamics. The patch‐scale thermally induced circulations enhance horizontal advection, modify the production and transport of scalar variances, and lead to a disproportionate increase in the standard deviations of temperature () and humidity (), accompanied by a reduction in ‐ covariance (). As a result, ‐ similarity is substantially reduced throughout the CBL. Spectral analysis reveals that ‐ dissimilarity is most strongly influenced by turbulent motions at scales corresponding to patch lengths. The findings offer insights into the role of surface heterogeneity in shaping scalar similarity in the CBL, with implications for land‐atmosphere interactions and parameterization in numerical models. 

The attached-eddy model (AEM) predicts that the mean streamwise velocity and streamwise velocity variance profiles follow a logarithmic shape, while the vertical velocity variance remains invariant with height in the overlap region of high Reynolds number wall-bounded turbulent flows. Moreover, the AEM coefficients are presumed to attain asymptotically constant values at very high Reynolds numbers. Here, the AEM predictions are examined using sonic anemometer measurements in the near-neutral atmospheric surface layer, with a focus on the logarithmic behaviour of the streamwise velocity variance. Utilizing an extensive 210-day dataset collected from a 62 m meteorological tower located in the Eastern Snake River Plain, Idaho, USA, the inertial sublayer is first identified by analysing the measured momentum flux and mean velocity profiles. The logarithmic behaviour of the streamwise velocity variance and the associated ‘$$-1$$’ scaling of the streamwise velocity energy spectra are then investigated. The findings indicate that the Townsend–Perry coefficient ($$A_1$$) is influenced by mild non-stationarity that manifests itself as a Reynolds number dependence. After excluding non-stationary runs, and requiring the bulk Reynolds number defined using the atmospheric boundary layer height to be larger than$$4 \times 10^{7}$$, the inferred$$A_1$$converges to values ranging between 1 and 1.25, consistent with laboratory experiments. Furthermore, nine benchmark cases selected through a restrictive quality control reveal a close relation between the ‘$$-1$$’ scaling in the streamwise velocity energy spectrum and the logarithmic behaviour of streamwise velocity variance. However, additional data are required to determine whether the plateau value of the pre-multiplied streamwise velocity energy spectrum is identical to$$A_1$$. 

Abstract In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity , where overline indicates time or ensemble averaging. The micro‐eddy surface renewal model predicts , where is the molecular Schmidt number, is the water kinematic viscosity, and is the waterside mean turbulent kinetic energy dissipation rate at or near the interface. While has been reported across a number of data sets, others report large scatter or variability around this value range. It is shown here that this scatter can be partly explained by high temporal variability in instantaneous around , a mechanism that was not previously considered. As the coefficient of variation in increases, must be adjusted by a multiplier that was derived from a log‐normal model for the probability density function of . Reported variations in with a macro‐scale Reynolds number can also be partly attributed to intermittency effects in . Such intermittency is characterized by the long‐range (i.e., power‐law decay) spatial auto‐correlation function of . That varies with a macro‐scale Reynolds number does not necessarily violate the micro‐eddy model. Instead, it points to a coordination between the macro‐ and micro‐scales arising from the transfer of energy across scales in the energy cascade. 

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. Accurate air temperature measurements are essential in eddy covariance systems, not only for determining sensible heat flux but also for applying density effect corrections (DECs) to water vapor and CO2 fluxes. However, the influence of wind-induced vibrations of mounting structures on temperature fluctuations remains a subject of investigation. This study examines 30 min average temperature variances and fluxes using eddy covariance systems, combining Campbell Scientific sonic anemometers with closely co-located fine-wire thermocouples alongside LI-COR CO2–H2O gas analyzers at multiple heights above a sagebrush ecosystem. The variances of sonic temperature after humidity corrections (Ts) and sensible heat fluxes derived from Ts are underestimated (e.g., by approximately 5 % for temperature variances and 4 % for sensible heat fluxes at 40.2 m, respectively) as compared with those measured by a fine-wire thermocouple (Tc). Spectral analysis illustrates that these underestimated variances and fluxes are caused by the lower energy levels in the Ts spectra than the Tc spectra in the low-frequency range (natural frequency < 0.02 Hz). These underestimated Ts spectra in the low-frequency range become more pronounced with increasing wind speeds, especially when wind speed exceeds 10 m s−1. Moreover, the underestimated temperature variances and fluxes cause overestimated water vapor and CO2 fluxes through DEC. Our analysis suggests that these underestimations when using Ts are likely due to wind-induced vibrations affecting the tower and mounting arms, altering the time of flight of ultrasonic signals along three sonic measurement paths. This study underscores the importance of further investigations to develop corrections for these errors. 

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 It is well‐established that large eddies significantly influence the turbulent transport of heat and scalars in the atmospheric surface layer. However, the mechanistic understanding of how large eddies originating from both the ground (updrafts) and aloft (downdrafts) regulate flux convergence (FC) and divergence (FD) remains relatively unexplored. Based on turbulence data measured at 12 levels, spanning from 1.2 to 60.5 m above the ground, we observe a notable increase in the variability of sensible heat flux magnitudes with height. Our results show that FC and FD of sensible heat are primarily linked to variations in the respective transport efficiencies () at different heights. Using the cross‐wavelet transform, we find that in FC cases, the regions with high wavelet coherence expand with height, resulting in higher at higher levels compared to low ones. Conversely, in FD cases, the regions with high wavelet coherence decrease with height, leading to lower at higher levels. Large eddies with length scales of approximately 120–500 m have a significant impact on amplifying or attenuating at higher levels compared to lower levels. Using conditional sampling to extract the updrafts and downdrafts of large eddies, distinct patterns are observed in the characteristics of updrafts and downdrafts between FC and FD groups especially in their flux contribution and transport efficiencies. This work emphasizes the significant contribution of asymmetric turbulent transport by updrafts and downdrafts to the discrepancy between the observed turbulent fluxes and those predicted by the Monin‐Obukhov similarity theory. 

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.