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How convective boundary‐layer (CBL) processes modify fluxes of sensible (SH) and latent (LH) heat and CO2 (Fc) in the atmospheric surface layer (ASL) remains a recalcitrant problem. Here, large eddy simulations for the CBL show that while SH in the ASL decreases linearly with height regardless of soil moisture conditions, LH and Fc decrease 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 overestimated LH. The non‐closure does not imply that Fc is always underestimated; Fc can be overestimated over dry soils despite the non‐closure issue. Plain Language Summary Large swirling motions, called large turbulent eddies, efficiently transport water vapor, carbon dioxide, and heat up and down throughout the convective boundary layer (CBL). To what extent scalar fluxes in the atmospheric surface layer (ASL) are modulated by large turbulent eddies from the top of the CBL (i.e., top‐down eddies) remains a recalcitrant problem in many fields spanning atmospheric sciences, hydrology, ecology, and climate change. Here, high‐resolution computational simulations of the CBL show that scalar fluxes in the ASL linearly change with height across soil wetness conditions largely due to changes in the interactions of top‐down processes and bottom‐up surface exchange. Such linear height‐dependence of the fluxes indicates that reported fluxes from direct turbulent measurements in the ASL are not identical to their sought surface values. As a result, the non‐closure of the surface energy balance occurs across all soil moisture conditions but improves as soil becomes dry. CO2 measured fluxes are underestimated over wet soils and overestimated over dry soils, which has its implication when interpreting CO2 exchanges from global flux measuring networks utilizing turbulence theories. Height dependence of fluxes, which confirms that the constant flux layer assumption is not routinely satisfied, is a fundamental reason for the non‐closure. Key Points Asymmetric flux transport by bottom‐up and top‐down processes leads to varying flux divergence/convergence (FDC) in the surface layer Latent heat and CO2 fluxes are underestimated when soil is wet and overestimated when dry, but sensible heat flux is always underestimated Non‐closure of the surface energy balance is regulated by varying FDC and improves for dry soils due to overestimated latent heat flux

Top‐down entrainment shapes the vertical gradients of sensible heat, latent heat, and CO2 fluxes, 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. Plain Language Summary In the atmosphere over a heated surface, water vapor, carbon dioxide, and heat are transported from both the ground (bottom‐up) and the top of the air column (top‐down). The swirling motion of air within the column helps to even out the distribution of these quantities, known as “scalars.” Scalar fluxes measure how many molecules of these substances cross a unit area over time. At the surface, energy balance and plant processes control heat, water vapor, and carbon dioxide fluxes. However, fluxes at the top of the air column do not follow the same rules and abide by the same constraints as their ground counterpart. This study uses numerical simulations to show that when the temperature difference across a layer at the top of the boundary layer decreases, the boundary layer becomes deeper, increasing the transport of heat from the top. This causes changes in the slopes of flux profiles, disrupting the assumption that fluxes remain constant with height even close to the ground surface. As a result, measurements near the surface often underestimate or overestimate true surface fluxes, contributing to the much‐debated surface energy balance non‐closure problem. Key Points Entrainment‐modulated top‐down transport influences the slopes of the scalar flux profiles in the unstable atmospheric surface layer Variations in scalar flux profiles lead to differing degrees of failure in the constant flux layer assumption (CFLA) for different scalars The failure of the CFLA explains the non‐closure issue in the surface energy balance

To manage inland water resources, surveying the performance of remote sensing models for estimating the actual evaporation in arid regions is so important. Hence, this study aimed to assess the performance of two energy balance algorithms including surface energy balance algorithm for land (SEBAL) and operational simplified surface energy balance (SSEBop) in freshwater and saline water bodies. Another purpose of the present study was efficiency improvement in hypersaline lakes. In this regard, a practical salinity correction coefficient was used to overcome shortcomings of the selected models over saline Lake. The analysis of yearly lake water budget was used to assess the selected energy balance algorithms’ performance with a novel approach. These algorithms were investigated at Shahid Kazemi Dam Reservoir (as a freshwater body) and Urmia Lake (as a hypersaline water body) in Iran. The results showed that two selected algorithms estimated the evaporation rate at the selected freshwater body with a proper accuracy. The results showed the root mean square error for SEBAL result (RMSESEBAL) as 2.0 mm/day, correlation coefficient for SEBAL result (RSEBAL) as 0.80 mm/day, and RMSESSEBop and RSSEBop as 1.7 and 0.80 mm/day, respectively. However, these models overestimated evaporation over the hypersaline water body (RMSESEBAL = 88.4 mm/month, RSEBAL = 0.90 and RMSESSEBop = 39.9 mm/month, RSSEBop = 0.94). Salinity correction coefficient improved the results as RMSESEBAL = 19.8 mm/month, RSEBAL = 0.90 and RMSESSEBop = 13.4 mm/month, and RSSEBop = 0.94. In general, the algorithm performance was improved using the salinity correction coefficient in the chosen hypersaline water body.

The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project has compiled a forcing data set covering the period 2005–2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run four established ET algorithms: the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman–Monteith algorithm from the MODerate resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in situ meteorological data from 24 FLUXNET towers were used to force the models, with results from both forcing sets compared to tower-based flux observations. Model performance was assessed on several timescales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement with the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements (R2  =  0.67), the agreement of the satellite-based ET estimates is only marginally lower (R2  =  0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. An extension of the evaluation to a larger selection of 85 towers (model inputs resampled to a common grid to facilitate global estimates) confirmed the original findings.

The Model for Urban Surface Temperature, a three-dimensional approach, is developed for a realistically complex city with considerations of the energy exchange processes at the urban surface. The discrete transfer method and Gebhart absorption factor method are used for the shape factor estimation and multiple reflection calculation, respectively. The surface energy balance model is evaluated against existing field measurements that pertain to idealized urban geometry. It performs well in terms of predicting surface temperature and heat fluxes by allowing for detailed urban surface properties and meteorological conditions. The compressed row storage scheme is applied to calculate the transfer of surface thermal radiation, which dramatically reduces the computational requirements. This strategy permits the rigorous consideration of multiple reflections in a realistic urban area with hundreds of buildings. The result illustrates that considering only the first reflection is a good approach when the urban area is comprised of typical urban materials, e.g. materials with high emissivity and low albedo, because relatively accurate computational results can be obtained rapidly by avoiding the multiple reflection calculation.

Estimating actual evapotranspiration (AET) in agricultural semi-arid regions is important for crop yield and drought assessment. The Surface Energy Balance System (SEBS) model, a physically based energy balance model using satellite information is used to estimate AET at the 10 d scale, with a 3 km resolution. The bucket bottom hole (BBH) model, a conceptual daily water balance model is calibrated using the equifinality approach and run for simulating daily AET. Five watersheds located in northern Tunisia with areas varying between 56 and 448 km2 were calibrated using daily rainfall and potential evapotranspiration data as entry and river discharge as output data. Sets of model parameters fulfilling both absolute relative errors of simulated discharge less than 20 % and Nash–Sutcliffe coefficients greater than 0.75 were selected. Three years were selected for the comparison (2010, 2017, and 2018). For every year, six subperiods of 10 d are considered belonging to January, March, April, May, July, and September. Boxplots of AET-BBH estimations are plotted to achieve a comparison with AET-SEBS estimates. It is found that AET comparisons are well favorable for January, March, and April while less satisfactory for May and September. They do not match for July. AET-SEBS are much higher in comparison with AET-BBH estimates with an RMSE and MAE equal respectively to 17 and 19 mm 10 d−1. These results may help stakeholders to assess AET coming from different data sources and models.

Net radiation is an important component of the earth’s surface energy balance, which plays a vital role in the evolution of regional climate or climate change. The estimation of this component at regional or global scales is critical and challenging due to the sparse and limited ground-based observations. This paper made an attempt to analyze the feasibility of a remote sensing-based surface energy balance model using satellite (TERRA/MODIS) data to derive the net radiation (Rn). In the present study, MODIS data at 15 different days of the year (DOY) were utilized to visualize the spatial pattern of net radiation flux over three versatile and heterogeneous ecohydrological land surfaces (upstream, midstream, and downstream) of northwest China (Heihe river basin). The results revealed that the estimated net radiation from the satellite data agrees well with the ground-based measurements over three different surfaces, with a mean relative error of 9.33% over the upstream superstation (grasslands), 13.95% over the middle stream superstation (croplands), and 11.63% over the downstream superstation (mixed forests), where the overall relative error was 11.64% with an overall rmse of 29.36 W/m2 in the study area. The regional distribution of net radiation over the versatile land surfaces was validated well at a large scale during the five-month period and over different land surfaces. It was also observed that the spatial pattern of net radiation varies spatially over three different landscape regions during four different days of the year, which might be associated with different climatic conditions and landscape features in these regions. The overall findings of this study concluded that satellite-derived net radiation can rationally be obtained using a single-source remote sensing model over different land surfaces.

Impervious surface temperature is a key parameter in impervious surface energy balance. Urban canopy models are now widely used to simulate impervious surface temperatures, but the physical assimilation method for the urban canopy model is still under development and the use of high temporal resolution observation data are limited. In this paper, a physical assimilation method was used to improve the simulation of the impervious surface temperature for the first time. A variational assimilation method was developed and coupled with the integrated urban land model, using the impervious surface energy balance equation as the adjoint physical constraint. The results showed that when the observed impervious surface temperature data of every timestep were assimilated into the integrated urban land model, the bias of the impervious surface temperature was reduced about 86 %. For the operational run, the observed data were assimilated twice per day, and the bias of the impervious surface temperature was reduced by about 78%.

Calculation of actual evapotranspiration (AET) is of vital importance for the study of climate change, ecosystem carbon cycling, flooding, drought, and agricultural water demand. It is one of the more important components in the hydrological cycle and surface energy balance (SEB). How to accurately estimate AET especially for the Tibetan Plateau (TP) with complex terrain remains a challenge for the scientific community. Using multi-sensor remote sensing data, meteorological forcing data, and field observations, AET was derived for the Nagqu river basin of the Northern Tibetan Plateau from a surface energy balance system (SEBS) model. As inputs for SEBS, improved algorithms and datasets for land surface albedo and a cloud-free normalized difference vegetation index (NDVI) were also constructed. The model-estimated AET were compared with results by using the combinatory method (CM). The validation indicated that the model estimates of AET agreed well with the correlation coefficient, the root mean square error, and the mean percentage error of 0.972, 0.052 mm/h, and −10.4%, respectively. The comparison between SEBS estimation and CM results also proved the feasibility of parameterization schemes for land surface parameters and AET.

Quantitative knowledge of the surface energy balance is essential for the prediction of weather and climate. However, a multitude of studies from around the world indicate that the turbulent heat fluxes are generally underestimated using eddy-covariance measurements, and hence, the energy balance is not closed. This energy-balance-closure problem, which has been heavily covered in the literature for more than 25 years, is the topic of the present review, in which we provide an overview of the potential reason for the lack of closure. We demonstrate the effects of the diurnal cycle on the energy balance closure, and address questions with regard to the partitioning of the energy balance residual between the sensible and the latent fluxes, and whether the magnitude of the flux underestimation can be predicted based on other variables typically measured at micrometeorological stations. Remaining open questions are discussed and potential avenues for future research on this topic are laid out. Integrated studies, combining multi-tower experiments and scale-crossing, spatially-resolving lidar and airborne measurements with high-resolution large-eddy simulations, are considered to be of critical importance for enhancing our understanding of the underlying transport processes in the atmospheric boundary layer.