Explore the vast range of titles available.

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.

Utility-scale solar power plants are a rapidly growing component of the renewable energy sector. While most agree that solar power can decrease greenhouse gas emissions, the effects of photovoltaic (PV) systems on surface energy exchanges and near-surface meteorology are not well understood. This study presents data from two eddy covariance observational towers, placed within and adjacent to a utility-scale PV array in southern Arizona. The observational period (October 2017–July 2018) includes the full range of annual temperature variation. Average daily maximum 1.5-m air temperature at the PV array was 1.3°C warmer than the reference (i.e., non-PV) site, whereas no significant difference in 1.5-m nocturnal air temperature was observed. PV modules captured the majority of solar radiation and were the primary energetically active surface during the day. Despite the removal of energy by electricity production, the modules increased daytime net radiation Q* available for partitioning by reducing surface albedo. The PV modules shift surface energy balance partitioning away from upward longwave radiation and heat storage and toward sensible heat flux QH because of their low emissivity, low heat capacity, and increased surface area and roughness, which facilitates more efficient QH from the surface. The PV modules significantly reduce ground heat flux QG storage and nocturnal release, as the soil beneath the modules is well shaded. Our work demonstrates the importance of targeted observational campaigns to inform process-based understanding associated with PV systems. It further establishes a basis for observationally based PV energy balance models that may be used to examine climatic effects due to large-scale deployment.

This review examines the metabolic adaptations that occur in response to negative energy balance and their potential putative or functional impact on appetite and food intake. Sustained negative energy balance will result in weight loss, with body composition changes similar for different dietary interventions if total energy and protein intake are equated. During periods of underfeeding, compensatory metabolic and behavioural responses occur that attenuate the prescribed energy deficit. While losses of metabolically active tissue during energy deficit result in reduced energy expenditure, an additional down-regulation in expenditure has been noted that cannot be explained by changes in body tissue (e.g. adaptive thermogenesis). Sustained negative energy balance is also associated with an increase in orexigenic drive and changes in appetite-related peptides during weight loss that may act as cues for increased hunger and food intake. It has also been suggested that losses of fat-free mass (FFM) could also act as an orexigenic signal during weight loss, but more data are needed to support these findings and the signalling pathways linking FFM and energy intake remain unclear. Taken together, these metabolic and behavioural responses to weight loss point to a highly complex and dynamic energy balance system in which perturbations to individual components can cause co-ordinated and inter-related compensatory responses elsewhere. The strength of these compensatory responses is individually subtle, and early identification of this variability may help identify individuals that respond well or poorly to an intervention.

Background The twelve-item Self-Report Habit Index (SRHI) is the most popular measure of energy-balance related habits. This measure characterises habit by automatic activation, behavioural frequency, and relevance to self-identity. Previous empirical research suggests that the SRHI may be abbreviated with no losses in reliability or predictive utility. Drawing on recent theorising suggesting that automaticity is the ‘active ingredient’ of habit-behaviour relationships, we tested whether an automaticity-specific SRHI subscale could capture habit-based behaviour patterns in self-report data. Methods A content validity task was undertaken to identify a subset of automaticity indicators within the SRHI. The reliability, convergent validity and predictive validity of the automaticity item subset was subsequently tested in secondary analyses of all previous SRHI applications, identified via systematic review, and in primary analyses of four raw datasets relating to energy‐balance relevant behaviours (inactive travel, active travel, snacking, and alcohol consumption). Results A four-item automaticity subscale (the ‘Self-Report Behavioural Automaticity Index’; ‘SRBAI’) was found to be reliable and sensitive to two hypothesised effects of habit on behaviour: a habit-behaviour correlation, and a moderating effect of habit on the intention-behaviour relationship. Conclusion The SRBAI offers a parsimonious measure that adequately captures habitual behaviour patterns. The SRBAI may be of particular utility in predicting future behaviour and in studies tracking habit formation or disruption.

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

This review presents mechanistic studies performed in vitro and in animal models, as well as data obtained in patients that contribute to a better understanding of the impact of nutrients interacting with the gut microbiota on metabolic and behavioural alterations linked to obesity. The gut microbiota composition and function are altered in several pathological conditions including obesity and related diseases i.e. non-alcoholic fatty liver diseases (NAFLD). The gut–liver axis is clearly influenced by alterations of the gut barrier that drives inflammation. In addition, recent papers propose that specific metabolites issued from the metabolic cooperation between the gut microbes and host enzymes, modulate inflammation and gene expression in the liver. This review illustrates how dietary intervention with prebiotics or probiotics influences host energy metabolism and inflammation. Indeed, intervention studies are currently underway in obese and NAFLD patients to unravel the relevance of the changes in gut microbiota composition in the management of metabolic and behavioural disorders by nutrients interacting with the gut microbiota. In conclusion, diet is among the main triggers of NAFLD and the gut microbiota is modified accordingly, underlining the importance of the concomitant study of the nutrients and microbial impact on liver health and metabolism, in order to propose innovative, clinically relevant, therapeutic approaches.

Reforestation and afforestation is expected to achieve a quarter of all emission reduction pledged under the Paris Agreement. Trees store carbon in biomass and soil but also alter the surface energy balance, warming or cooling the local climate. Mitigation scenarios and policies often neglect these biogeophysical (BGP) effects. Here we combine observational BGP datasets with carbon uptake or emission data to assess the end-of-century mitigation potential of forestation. Forestation and conservation of tropical forests achieve the highest climate benefit at 732.12 tCO2e ha–1. Higher-latitude forests warm the local winter climate, affecting 73.7% of temperate forests. Almost a third (29.8%) of forests above 56° N induce net winter warming if only their biomass is considered. Including soil carbon reduces the net warming area to 6.8% but comes with high uncertainty (2.9–42.0%). Our findings emphasize the necessity to conserve and re-establish tropical forests and consider BGP effects in policy scenarios.Forests take up carbon from the atmosphere but also change Earth’s surface energy balance through biophysical effects. Accounting for these shows that tropical forests have the highest mitigation potential; the climate benefit of higher-latitude forests is offset by their warming effects in winter.

Reduced evaporation due to dry soils can affect the land surface energy balance, with implications for local and downwind precipitation. When evaporation is constrained by soil moisture, the atmospheric supply of water is depleted, and this deficit may propagate in time and space. This mechanism could theoretically result in the self-propagation of droughts, but the extent to which this process occurs is unknown. Here we isolate the influence of soil moisture drought on downwind precipitation using Lagrangian moisture tracking constrained by observations from the 40 largest recent droughts worldwide. We show that dryland droughts are particularly prone to self-propagating because evaporation tends to respond strongly to enhanced soil water stress. In drylands, precipitation can decline by more than 15% due to upwind drought during a single event and up to 30% during individual months. In light of projected widespread reductions in water availability, this feedback may further exacerbate future droughts. Dryland droughts are prone to self-propagation due to the enhanced soil water stress, according to atmospheric moisture-tracking analysis of recent major droughts around the world.

In the framework of the global energy balance, the radiative energy exchanges between Sun, Earth and space are now accurately quantified from new satellite missions. Much less is known about the magnitude of the energy flows within the climate system and at the Earth surface, which cannot be directly measured by satellites. In addition to satellite observations, here we make extensive use of the growing number of surface observations to constrain the global energy balance not only from space, but also from the surface. We combine these observations with the latest modeling efforts performed for the 5th IPCC assessment report to infer best estimates for the global mean surface radiative components. Our analyses favor global mean downward surface solar and thermal radiation values near 185 and 342 Wm −2 , respectively, which are most compatible with surface observations. Combined with an estimated surface absorbed solar radiation and thermal emission of 161 and 397 Wm −2 , respectively, this leaves 106 Wm −2 of surface net radiation available globally for distribution amongst the non-radiative surface energy balance components. The climate models overestimate the downward solar and underestimate the downward thermal radiation, thereby simulating nevertheless an adequate global mean surface net radiation by error compensation. This also suggests that, globally, the simulated surface sensible and latent heat fluxes, around 20 and 85 Wm −2 on average, state realistic values. The findings of this study are compiled into a new global energy balance diagram, which may be able to reconcile currently disputed inconsistencies between energy and water cycle estimates.

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.