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.
Abstract
The article studies the components of the energy balance of an all-wheel drive self-propelled power vehicle, presents and analyzes the results of a practical determination of all the ...components of the energy balance within the field experiment.
Land-surface temperature retrieved from thermal infrared (TIR) remote sensing has proven to be a valuable constraint in surface energy balance models for estimating evapotranspiration (ET). For ...optimal utility in agricultural water management applications, frequent thermal imaging (<4-day revisit) at sub-field (100 m or less) spatial resolution is desired. While, the current suite of Landsat satellites (7 and 8) provides the required spatial resolution, the 8-day combined revisit can be inadequate to capture rapid changes in surface moisture status or crop phenology, particularly in areas of persistent cloud cover. The new ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission, with an average 4-day revisit interval and nominal 70-m resolution, provides a valuable research platform for augmenting Landsat TIR sampling and for investigating TIR-based ET mapping mission requirements more broadly. This study investigates the interoperability of Landsat and ECOSTRESS imaging for developing ET image timeseries with high spatial (30-m) and temporal (daily) resolution. A data fusion algorithm is used to fuse Landsat and ECOSTRESS ET retrievals at 30 m with daily 500-m retrievals using TIR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) over target agricultural sites spanning the United States.The added value of the combined multi-source dataset is quantified in comparison with daily flux tower observations collected within these target domains. In addition, we investigate ET model performance as a function of ECOSTRESS view angle, overpass time, and time separation between TIR and Landsat visible to shortwave infrared (VSWIR) data acquisitions used to generate land-surface temperature, leaf area index, and albedo inputs to the surface energy balance model. The results demonstrate the value of the higher temporal sampling provided by ECOSTRESS, especially in areas that are frequently impacted by cloud cover. Limiting usage to ECOSTRESS scenes collected between 9:00 a.m. to 5:00 p.m. and nadir viewing angles <20° yielded daily (24-h) ET retrievals of comparable quality to the well-tested Landsat baseline. We also discuss challenges in using land-surface temperature from a thermal free-flyer system for ET retrieval, which may have ramifications for future TIR water-use mapping missions.
•Landsat thermal infrared constrains field-scale evapotranspiration (ET) retrievals.•ECOSTRESS thermal imaging effectively augments Landsat sampling.•Extra sampling improves ET timeseries in areas of high cloud cover frequency.•Lack of shortwave bands on ECOSTRESS limits accuracy of ET retrievals.•These findings have ramifications for design of future water use mapping missions.
Land surface temperature (LST) has been effectively retrieved from thermal infrared (TIR) satellite measurements under clear-sky conditions. However, TIR satellite data are often severely ...contaminated by clouds, which cause spatiotemporal discontinuities and low retrieval accuracy in the LST products. Several solutions have been proposed to fill the “gaps”; however, a majority of these possess constraints. For example, fusion methods with microwave data suffer from coarse spatial resolution and diverse land cover types while spatial-temporal interpolation methods neglect cloudy cooling effects. We developed a novel method to estimate cloudy-sky LST from polar-orbiting satellite data based on the surface energy balance (SEB) principle. First, the hypothetical clear-sky LST of missing or likely cloud-contaminated pixels was reconstructed by assimilating high-quality satellite retrievals into a time-evolving model built from reanalysis data using a Kalman filter data assimilation algorithm. Second, clear-sky LST was hypothetically corrected by accounting for cloud cooling based on SEB theory. The proposed method was applied to Visible Infrared Imaging Radiometer Suite (VIIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) data, and further validated using ground measurements of fourteen sites from SURFRAD, BSRN, and AmeriFlux in 2013. VIIRS LST recovered from cloud gaps exhibited a root mean square error (RMSE) of 3.54 K, a bias of −0.36 K, R2 of 0.94, and sample size (N) of 2411, comparable to the accuracy of clear-sky LST products and cloudy-sky LST estimation from MODIS (RMSE of 3.69 K, bias of −0.45 K, R2 of 0.93, and N of 2398). Thus, the proposed method performs well across different sensors, seasons, and land cover types. The abnormal retrieval values caused by cloud contamination were also corrected in the proposed method. The overall accuracy was better than the downscaled cloudy-sky LST retrieved from passive microwave (PMW) observations and former SEB-based cloudy-sky LST estimation methods. Validation using time-series measurements showed that the all-sky LST time series, including both clear- and cloudy-sky retrievals, can capture realistic variability without sudden abruptions or discontinuities. RMSE values for the all-sky LST varied from 2.54 to 4.15 K at the fourteen sites. Spatially continuous LST maps over the Contiguous United States were compared with corresponding maps from PMW data in the winter and summer of 2018, exhibiting similar spatial patterns but with additional spatial details. Moreover, sensitivity analysis suggested that the reconstruction of clear-sky LST dominantly impacts the accuracy of cloudy-sky LST estimation. The proposed method can be potentially implemented in similar satellite sensors for global real-time production.
•A novel surface energy budget-based method for estimating cloudy-sky LST.•Highly accurate estimations from MODIS and VIIRS based on extensive validation.•Consistency of cloudy-sky LST estimation for different seasons and land covers.•Feasibility for removing cloud contamination and fill the gaps over large regions.
We investigate the impact of trilemma energy balance and clean energy transitions on economic expansion and environmental sustainability while moderating the role of clean energy and natural ...resources rents of the three trilemma leaders from 1990 to 2016. Through this study, we have developed a comprehensive empirical analysis, applied advanced econometric methodologies. Westerlund's panel co-integration suggests long-run relationships within the variables. Our long-run random effect generalized least squares (GLS), generalized least square mixed effect models (GLMM), and robust correlated panel corrected standard errors (PCSEs) findings indicate trilemma energy balance, clean energy transition, and natural resource depletion enhance economic growth while clean energy discourages this growth. Moreover, trilemma energy balance, clean energy transitions, and clean energy improve while natural resources depletion deteriorates environmental sustainability in the trilemma energy leadership. Increasing the trilemma energy balance by 1% boosts economic growth by 0.3874223%. By increasing the trilemma energy balance by 1%, the ecological footprint is reduced by −0.5901441%. A 1% acceleration in the clean energy transitions boosts economic growth by 0.1208461%. By accelerating the transition to clean energy by 1%, the environmental footprint would decrease by 0.0273685%. Crucial policy implications and study limitations are discussed.
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•Energy trilemma and transition nexus checked for environment and economic growth.•Trilemma energy balance encourages economic growth and environmental sustainability.•Clean energy transitions improve economic growth and environmental sustainability.•Individually clean energy improves the environment and declining economic growth.•Natural resources depletion deteriorates environmental sustainability.
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
The increase in atmospheric CO
concentration and the release of nutrients from wastewater treatment plants (WWTPs) are environmental issues linked to several impacts on ecosystems. Numerous ...technologies have been employed to resolves these issues, nonetheless, the cost and sustainability are still a concern. Recently, the use of microalgae appears as a cost-effective and sustainable solution because they can effectively uptake CO
and nutrients resulting in biomass production that can be processed into valuable products. In this study single (Spirulina platensis (SP.PL) and mixed indigenous microalgae (MIMA) strains were employed, over a 20-month period, for simultaneous removal of CO
from flue gases and nutrient from wastewater under ambient conditions of solar irradiation and temperature. The study was performed at a pilot scale photo-bioreactor and the effect of feed CO
gas concentration in the range (2.5-20%) on microalgae growth and biomass production, carbon dioxide bio-fixation rate, and the removal of nutrients and organic matters from wastewater was assessed. The MIMA culture performed significantly better than the monoculture, especially with respect to growth and CO
bio-fixation, during the mild season; against this, the performance was comparable during the hot season. Optimum performance was observed at 10% CO
feed gas concentration, though MIMA was more temperature and CO
concentration sensitive. MIMA also provided greater removal of COD and nutrients (~83% and >99%) than SP.PL under all conditions studied. The high biomass productivities and carbon bio-fixation rates (0.796-0.950 g
·L
·d
and 0.542-1.075 g
·L
·d
contribute to the economic sustainability of microalgae as CO
removal process. Consideration of operational energy revealed that there is a significant energy benefit from cooling to sustain the highest productivities on the basis of operating energy alone, particularly if the indigenous culture is used.
Anthropogenic heat flux (AHF) is a main contributor to the formation of surface urban heat islands (SUHI). Megacities in particular are facing severe problems due to excessive population growth, ...urban area expansion, human activity, increased energy consumption, and increased anthropogenic heat. In this study, a physical modeling approach based on a triple-source surface energy balance (triple-SEB) model was developed to uncover the effect of AHF on land surface temperature (LST) and surface anthropogenic heat island (SAHI) intensity. For this purpose, satellite imagery along with climatic and meteorological data from 1985 to 2019 were studied for six selected megacities: Los Angeles, Atlanta, Athens, Istanbul, Tehran, and Beijing. First, LST and the fraction of different surface covers were calculated by using a single-channel algorithm and a normalized spectral mixture analysis model, respectively. In the second step, impervious surface cover (ISC) and the urban main boundary area (UMBA) of each city were extracted based on the biophysical composite index and city clustering algorithm, respectively. In the third step, anthropogenic LST (ALST) was modeled using a triple-SEB model. In the fourth step, the ALST and UMBA were used together to model SAHI intensity at different dates. Finally, the relationship between the estimated ALST and ISC, as well as between SAHI and ISC, was examined. Results show that the average value of estimated ALST for the megacities increased from 2.02, 0.55, 0.61, 0.64, 0.58, and 0.72 to 2.99, 1.73, 1.66, 1.19, 2.32, and 2.76 °C, respectively. The coefficient of determination between the mean value of ISC and the estimated ALST for all megacities yielded 0.8, which was higher than that between ISC and satellite-derived LST. Moreover, the SAHI intensity for these megacities was found to have increased to 0.73, 0.92, 0.95, 0.98, 0.95 and 1.32 °C, respectively, which can be predicted by ISC with a coefficient of determination of 0.78, 0.79, 0.79, 0.73, 0.71 and 0.52, respectively. This suggests that the triple-SEB model proposed by this study allowed for independent modeling of AHF's influence on SUHI and a better determination of the effect of ISC on LST and SUHI intensity. This approach facilitated comparative analysis of LST and SAHI for a city at different times as well as SAHIs in different cities with different geographic and climate settings.
•A novel method based on triple-source energy balance model developed for LST•LST due to anthropogenic heat flux used to model surface anthropogenic heat island•SAHI and the effect of ISC on SUHI in five global megacities were investigated.•Better determination and modeling of the effect of ISC on LST and SUHI intensity•New method for comparative analysis of LST and SAHI at different times and cities
A simple and robust satellite‐based method for estimating agricultural field to regional surface energy fluxes at a high spatial resolution is important for many applications. We developed a simple ...temperature domain two‐source energy balance (TD‐TSEB) model within a hybrid two‐source model scheme by coupling “layer” and “patch” models to estimate surface heat fluxes from Landsat thematic mapper/Enhanced Thematic Mapper Plus (TM/ETM+) imagery. For estimating latent heat flux (LE) of full soil, we proposed a temperature domain residual of the energy balance equation based on a simplified framework of total aerodynamic resistances, which provides a key link between thermal satellite temperature and subsurface moisture status. Additionally, we used a modified Priestley‐Taylor model for estimating LE of full vegetation. The proposed method was applied to TM/ETM+ imagery and was validated using the ground‐measured data at five crop eddy‐covariance tower sites in China. The results show that TD‐TSEB yielded root‐mean‐square‐error values between 24.9 (8.9) and 78.2 (21.4) W/m2 and squared correlation coefficient (R2) values between 0.60 (0.51) and 0.97 (0.90), for the estimated instantaneous (daily) surface net radiation, soil, latent, and sensible heat fluxes at all five sites. The TD‐TSEB model shows good accuracy for partitioning LE into soil (LEsoil) and canopy (LEcanopy) components with an average bias of 11.1% for the estimated LEsoil/LE ratio at the Daman site. Importantly, the TD‐TSEB model produced comparable accuracy but requires fewer forcing data (i.e., no wind speed and roughness length are needed) when compared with two other widely used surface energy balance models. Sensitivity analyses demonstrated that this accurate operational model provides an alternative method for mapping field surface heat fluxes with satisfactory performance.
Key Points
A simple temperature domain two‐source energy balance model has been developed
This model produced comparable accuracy when compared with two other models
This model provides an alternative method for mapping field surface heat fluxes
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