Energy Balance Parameters Research Articles

Comparison of Multiple Methods for Supraglacial Melt-Lake Volume Estimation in Western Greenland During the 2021 Summer Melt Season

Supraglacial melt-lakes form and evolve along the western edge of the Greenland Ice Sheet and have proven to play a significant role in ice sheet surface hydrology and mass balance. Prior methods to quantify melt-lake volume have relied upon Landsat-8 optical imagery, available at 30 m spatial resolution but with temporal resolution limited by satellite overpass times and cloud cover. We propose two novel methods to quantify the volume of meltwater stored in these lakes, including a high-resolution surface DEM (ArcticDEM) and an ablation model using daily averaged automated weather station data. We compare our methods to the depth-reflectance method for five supraglacial melt-lakes during the 2021 summer melt season. We find agreement between the depth-reflectance and DEM lake infilling methods, within +/−15% for most cases, but our ablation model underproduces by 0.5–2 orders of magnitude the volumetric melt needed to match our other methods, and with a significant lag in meltwater onset for routing into the lake basin. Further information regarding energy balance parameters, including insolation and liquid precipitation amounts, is needed for adequate ablation modelling. Despite the differences in melt-lake volume estimates, our approach in combining remote sensing and meteorological methods provides a framework for analysis of seasonal melt-lake evolution at significantly higher spatial and temporal scales, to understand the drivers of meltwater production and its influence on the spatial distribution and extent of meltwater volume stored on the ice sheet surface.

A First Exploration of the Ts/VI “Analytical Triangle” Technique with UAV Imagery for Deriving Key Surface Energy Balance Parameters at Very High Spatial Resolution

Knowledge on the spatiotemporal patterns of surface energy balance parameters is crucial for understanding climate system processes. To this end, the assimilation of Earth Observation data with land biosphere models has shown promising results, but they are still hampered by several limitations related to the spatiotemporal resolution of EO sensors and cloud contamination. With the recent developments on Unmanned Aerial Vehicles (UAVs), there is a great opportunity to overcome these challenges and gain knowledge of surface energy balance parameters at unprecedented resolutions. The present study examines, for the first time, the ability of an inversion-modeling scheme, the so-called “analytical triangle” method, to retrieve estimates of surface energy fluxes and soil surface moisture (SSM) at high spatial resolution using UAV data. A further aim of our study was to examine the representativeness of the SSM estimates for the SM measurements taken at different depths. The selected experimental site is an agricultural site of citrus trees located near the city of Palermo on 30 July 2019. The results of comparisons showed that the sensible and latent heat fluxes from UAV were consistent with those measured from the ground, with absolute differences in comparison to ground measurements being 5.00 Wm−2 for the latent heat (LE) flux and 65.02 Wm−2 for H flux, whereas for the daytime fluxes H/Rn and LE/Rn were 0.161 and 0.012, respectively. When comparing analytical triangle SSM estimates with SM measurements made at different depths, it was found that there was a gradual increase in underestimation with increasing measurement depth. All in all, this study’s results provide a credible demonstration of the significant potential of the technique investigated herein as a cost-effective and rapid solution for estimating key parameters characterizing land surface processes. As those parameters are required by a wide range of disciplines and applications, utilization of the investigated technique in research and practical applications is expected to be seen in the future.

Weight loss in adult male Wistar rats by Roux-en-Y gastric bypass is primarily explained by caloric intake reduction and presurgery body weight.

Diets varying in macronutrient composition, energy density, and/or palatability may cause differences in outcome of bariatric surgery. In the present study, rats feeding a healthy low-fat (LF) diet or an obesogenic high-fat/sucrose diet (HF/S) were either subjected to Roux-en-Y gastric bypass surgery (RYGB) or sham surgery, and weight loss trajectories and various energy balance parameters were assessed. Before RYGB, rats eating an HF/S (n = 14) diet increased body weight relative to rats eating an LF diet (n = 20; P < 0.01). After RYGB, absolute weight loss was larger in HF/S (n = 6) relative to LF feeding (n = 6) rats, and this was associated with reduced cumulative energy intake (EI; P < 0.05) and increased locomotor activity (LA; P < 0.05-0.001), finally leading to similar levels of reduced body fat content in HF/S and LF rats 3 wk after surgery. Regression analysis revealed that variation in RYGB-induced body weight loss was best explained by models including 1) postoperative cumulative EI and preoperative body weight (R2 = 0.87) and 2) postoperative cumulative EI and diet (R2 = 0.79), each without significant contribution of LA. Particularly rats on the LF diet became transiently more hypothermic and circadianally arrhythmic following RYGB (i.e., indicators of surgery-associated malaise) than HF/S feeding rats. Our data suggest that relative to feeding an LF diet, continued feeding an HF/S diet does not negatively impact recovery from RYGB surgery, yet it promotes RYGB-induced weight loss. The RYGB-induced weight loss is primarily explained by reduced cumulative EI and higher preoperative body weight, leading to comparably low levels of body fat content in HF/S and LF feeding rats.NEW & NOTEWORTHY Relative to feeding an LF diet, continued feeding an HF/S diet does not negatively impact recovery from RYGB surgery in rats. Relative to feeding an LF diet, continued feeding an HF/S diet promotes RYGB-induced weight loss. The RYGB-induced weight loss is primarily explained by reduced cumulative EI and higher preoperative body weight, leading to comparably low levels of body fat content in HF/S and LF feeding rats.

Geospatial Insights into Aridity Conditions: MODIS Products and GIS Modeling in Northeast Brazil

Northeast Brazil (NEB), particularly its semiarid region, represents an area highly susceptible to the impacts of climate change, including severe droughts, and intense anthropogenic activities. These stresses may be accelerating environmental degradation and desertification of soil in NEB. The main aim of this study was to gain geospatial insights into the biophysical parameters of surface energy balance and actual evapotranspiration on a multi-temporal scale, aiming to detect and analyze the spectral behavioral patterns of areas vulnerable to degradation processes, based on thematic maps at the surface, for NEB and mainly the semiarid region of NEB from 2000 to 2019. Geospatial data from 8-day MODIS sensor products were used, such as surface reflectance (Terra/MOD09A1 and Aqua/MYD09A1), surface temperature (Terra/MOD11A2 and Aqua/MYD11A2), and actual evapotranspiration (Terra/MOD16A2 and Aqua/MYD16A2), version 6. Therefore, in this study, pixel-to-pixel values were processed by calculating the average pixel statistics for each year. From the reflectance product, digital processing of the surface albedo and spectral vegetation indices was also carried out, using computational programming scripts and machine learning algorithms developed via the Google Earth Engine (GEE) platform. The study also presents a seasonal analysis of these components and their relationships over 20 years. Through vegetation indices and statistical correlations, a new predictive model of actual evapotranspiration was developed. The quantitative and spatiotemporal spectral patterns of the parameters were assessed through descriptive statistics, measures of central tendency and dispersion, and statistical error analyses and correlation indices. Thematic maps highlighted the pixel-to-pixel results, with patterns of high temperature distribution mainly in the central and northeastern part of NEB and the semiarid region of NEB, highlighting the formation of persistent heat islands over time. Meanwhile, in these areas, the maps of actual evapotranspiration showed a drastic reduction due to the lesser availability of energy. Over time, the semiarid region of NEB presented areas with little and/or no vegetation cover, which were highly well-defined between the years 2012 and 2019, confirming that these areas are extremely vulnerable to degradation and desertification processes due to significant loss of vegetative and water resilience. The components of energy balance were highly interconnected to climatological and environmental conditions, showing the severe results of drought and accentuation of the water deficit in NEB, presenting a greater condition of aridity in the semiarid region of NEB over time.

Techno-economic analysis of solanesol production from tobacco leaves using ultrasound-assisted extraction

Solanesol has high antioxidant activity and strong free radical absorption and is an intermediate raw material for coenzyme Q10. Tobacco leaves are the highest source of solanesol. Ultrasonic-assisted extraction (UAE) increases the extract yield through reduced process time, low temperature, and safe solvents. The CAGR for solanesol demands in the Asia Pacific is growing 10.5% in 2021-2027, with market values of USD 575 million. Therefore, developing a solanesol plant in Indonesia is required to increase high-added value derivative products from tobacco leaves. Based on that necessity, this study provides a preliminary study and simulation of solanesol production from tobacco leaves in the UAE. The simulation uses SuperPro Designer v9.0 to get the plant’s mass, energy balance, and economic parameters. The plant will be built in Kawasan Industri Kupen, Temanggung, Central Java. Then, assuming 7920 hours annual operation time, 153 kg tobacco leaves/batch input rate, and solanesol selling price of USD 2.100/kg. The simulations showed that solanesol production in the UAE is feasible economically, with conversion rates at 2.3%. The value of profitability parameters is as follows: Internal Rate of Return (IRR) = 33,90%, Net Present Value (NPV) at I = 7% = USD 39,437,000, and payback time = 2.95 years.

Influences of the window size and reflectivity on surrounding thermal environment

Relevant researches on windows mainly focused on the influence on indoor lighting, thermal environment and energy consumption. And previous numerical simulation studies related to the effects of buildings on microclimate and thermal comfort have always simplified the building façade as a homogenized envelope, neglecting the impacts of windows' size and reflectivity on local thermal environment outdoors, which might affect the accuracy of the results. In this context, to determine and evaluate the relationship between window size/reflectivity and local climate, the ENVI-met model was employed and 40 scenarios were established and simulated in current study. This study quantified the impact of windows on the surrounding thermal environment, and revealed its spatiotemporal characteristics: windows' impact was time-dependent both in diurnal and seasonal dimension and varied with the distance from the building. Two parameters of earth-atmosphere energy balance, sensible heat flux and shortwave reflected flux, were selected and analyzed to better understand the functioning mechanisms of windows' impact. The interaction between window size and reflectivity was also figured out in current study. The findings could enhance our further understanding on the effects of buildings on local environment in urban areas and provide useful insights to architects and urban planners on how to create a more livable urban environment.

Effect of floating balls on evaporation inhibition, surface energy balance and biological water quality parameters at different coverage fractions

Effect of floating balls on evaporation inhibition, surface energy balance and biological water quality parameters at different coverage fractions

Role of the Beta and Gamma Isoforms of the Adapter Protein SH2B1 in Regulating Energy Balance.

Human variants of the adapter protein SH2B1 are associated with severe childhood obesity, hyperphagia, and insulin resistance-phenotypes mimicked by mice lacking Sh2b1. SH2B1β and γ isoforms are expressed ubiquitously, whereas SH2B1α and δ isoforms are expressed primarily in the brain. Restoring SH2B1β driven by the neuron-specific enolase promoter largely reverses the metabolic phenotype of Sh2b1-null mice, suggesting crucial roles for neuronal SH2B1β in energy balance control. Here we test this hypothesis by using CRISPR/Cas9 gene editing to delete the β and γ isoforms from the neurons of mice (SH2B1βγ neuron-specific knockout [NKO] mice) or throughout the body (SH2B1βγ knockout [KO] mice). While parameters of energy balance were normal in both male and female SH2B1βγ NKO mice, food intake, body weight, and adiposity were increased in male (but not female) SH2B1βγ KO mice. Analysis of long-read single-cell RNA seq data from wild-type mouse brain revealed that neurons express almost exclusively the α and δ isoforms, whereas neuroglial cells express almost exclusively the β and γ isoforms. Our work suggests that neuronal SH2B1β and γ are not primary regulators of energy balance. Rather, non-neuronal SH2B1β and γ in combination with neuronal SH2B1α and δ suffice for body weight maintenance. While SH2B1β/γ and SH2B1α/δ share some functionality, SH2B1β/γ appears to play a larger role in promoting leanness.

Analysis of Daytime Cloud Fraction Spatiotemporal Variation over the Arctic from 2000 to 2019 from Multiple Satellite Products

Abstract Insufficient understanding of complex Arctic cloud properties introduced large errors in estimating radiant energy balance parameters at the regional and global scales. Comprehensive and reliable cloud information is necessary for improving the accuracy of flux inversion. This study evaluated daytime cloud fraction (CF) uncertainties from 16 available satellite products and estimated the spatiotemporal distributions of Arctic daytime CF during 2000–19. Our results show that the differences among multiple products had significant temporal and spatial heterogeneities. Temporally, the maximum and minimum interproduct discrepancies occurred in April and the summer months, respectively. Spatially, the largest uncertainties were seen over Greenland. Substantial inconsistency also occurred on the central and Pacific sides of the Arctic Ocean. The active satellite product tended to capture more clouds in these two regions. We found that the inconsistencies caused by sensor differences were smaller than those caused by algorithm differences; that is, for MODIS based CF products, the inconsistencies caused by different sensors and different algorithms are ±2% and ±5%, while for AVHRR-based products, these inconsistencies are ±6% and ±15%, respectively. The annual average daytime CF in sunlit months was 70.9% ± 2.93% and increased over the Arctic during study periods. These upward trends might cool the Arctic by approximately 0.05–0.5 W m−2 decade−1. In terms of the spatiotemporal distributions, the CF over the ocean is higher than that over the land, and the former increased significantly while the latter decreased; the CF trends of most products are positive in June and July but are opposite in other months. From this study, the findings based on multiple products would be more robust than that based on a single or few datasets. Significance Statement This study aimed to comprehensively understand and obtain more robust general characteristics of the temporal and spatial distributions of Arctic daytime cloud fraction by comparing and analyzing the consistencies and discrepancies of multisource satellite products. It is important because the cloud fraction is a nonnegligible modulator of Earth’s energy budget and climate change. Although the Arctic is the most climate-sensitive region, existing studies lack a comprehensive assessment of the cloud fraction over the entire Arctic. We analyzed 16 different cloud products and found that although the inconsistencies were inevitable, most products showed similar spatiotemporal distribution and trend distribution of daytime CF. This study provided a new idea for Arctic CF research under the existing conditions.

Irisin concentration in infant formulas and breast milk.

Irisin is a newly discovered myokine with antiobesity properties. The delivery of irisin with the breast milk or formula is an emerging concept that myokine present at human milk influences postnatal energy balance and developmental parameters. The aim of the study was to evaluate irisin concentration in breast milk of mothers with term and preterm babies and in infant formulas. A total of 49 lactating mothers were enrolled in the study: 31 mothers of very low birth weight preterm infants and 18 mothers of term infants. Milk samples were collected twice: during the first week after delivery and after 4 weeks of delivery. Irisin concentration was determined using ELISA kits both in human milk and in samples of 14 different infant formulas. There were no differences in milk irisin levels between preterm and full-term milk samples during both the 1st and the 4th week after delivery. There were also no differences in irisin concentration between transitional milk and mature milk in both tested groups. Irisin concentrations in preterm and full-term milk were significantly higher than in formulas for 30 days period after delivery. A significant increase of irisin concentration in natural milk 4 weeks postdelivery in comparison to 1st week after delivery was observed (mean difference 0.362 µg/mL; P=0.0063). This study provides evidence that irisin is present in infant formulas, although in less amount than in human milk. Further research is needed to assess, if children fed with infant formulas may disadvantage from lower irisin supply.

Comparative analysis of a dual Kalina cycle configuration for heat recovery from boiler stack in a steam power plant

AbstractThis study proposes a dual configuration of the Kalina cycle for heat recovery from a boiler stack in a steam power plant, consisting of two basic Kalina cycles; a top and a bottom one. Thermoeconomic modeling was done using mass and energy balance and economic parameters such as internal rate of return (IRR) and net present value (NPV). The proposed configuration was evaluated by comparing it with the basic Kalina cycle (KSC1) and other modified Kalina cycles configurations KSC11, KSC34, and KSC34G. The flue gas from the stack of the steam boiler (Tarasht Steam Power Plant‐Tehran‐Iran), a stable low‐temperature heat source, was used in the analysis. The temperature range of the heat source, between 172°C and 190°C, was obtained from operational data of the steam power plant, collected for 5 years, using temperature sensors in the exhaust of the stack. The results show that the proposed configuration's output power varies from 591.74 to 755.74 kW and 6.2%–11.2% more than the KSC34 configuration. Accordingly, the thermal efficiency is about 4.56%–6.25% higher than the other studied configurations, and the natural gas saved is 0.7765 to 1.02 Mm3.year−1. Also, the results indicate that the reduction in CO2 emission for the proposed configuration is about 2786–3661 tons.year−1, which is more than the other configurations.

Dietary administration of D-chiro-inositol attenuates sex-specific metabolic imbalances in the 5xFAD mouse model of Alzheimer's disease.

Increasing evidence shows that hypothalamic dysfunction, insulin resistance, and weight loss precede and progress along with the cognitive decline in sporadic Alzheimer's Disease (AD) with sex differences. This study aimed to determine the effect of oral dietary administration of D-Chiro-inositol (DCI), an inositol used against insulin resistance associated with polycystic ovary, on the occurrence of metabolic disorders in the transgenic 5xFAD mouse model of AD (FAD: Family Alzheimer's Disease). DCI was administered from 6 to 10 months of age to male and female 5xFAD mice and control (non-Tg) littermates. Energy balance and multiple metabolic and inflammatory parameters in the hypothalamus, liver and plasma were evaluated to assess the central and peripheral effects of DCI. Results indicated that weight loss and reduced food intake in 5xFAD mice were associated with decreased neuropeptides controlling food intake and the appearance of a pro-inflammatory state in the hypothalamus. Oral administration of DCI partially restored energy balance and hypothalamic parameters, highlighting an increased expression of Npy and Agrp and female-specific downregulation of Gfap and Igf1. DCI also partially normalized impaired insulin signaling and circulating insulin, GLP-1, and GIP deficiencies in 5xFAD mice. Principal component analysis of metabolic parameters indicated the presence of a female-specific fatty liver in 5xFAD mice: DCI administration reversed hepatic fat accumulation, β-oxidation, inflammation and increased GOT and GPT levels. Our study depicts that metabolic impairment along with the cognitive decline in a mouse model of AD, which is exacerbated in females, can be ameliorated by oral supplementation with insulin-sensitizing DCI.

ESTIMATION OF DAILY GLOBAL SOLAR IRRADIANCE FROM HIMAWARI-8 PRODUCTS OVER CHINA

Abstract. Daily global surface solar irradiance (SSI) is of great importance parameter in the surface energy balance, climate modelling, and solar energy utilization. However, it is still challenging to extend the estimated instantaneous solar radiation to the daily global SSI from either geostationary satellites or polar-orbiting satellites. In this study, a method for estimating the daily global SSI is proposed based on the Himawari-8 hourly SSI products using pixel-by-pixel Gaussian fitting to simulate the diurnal SSI variation. Compared with ground-based observations, the daily global SSI estimated by Gaussian fitting have higher accuracy under various weather conditions than by the simple accumulation or quadratic polynomials, and the coefficient of determination (R2) between the estimated and observed values exceeds 0.86. The verification results also show different estimation accuracies under different weather conditions. The root-mean-square errors (RMSEs) under clear-sky and all-sky conditions are 2.36 MJ/m2 and 3.06 MJ/m2, respectively. In addition, experimental results show that the daily global SSI in China has high spatial heterogeneity. For higherelevation areas with low cloud cover, such as the Qinghai-Tibet Plateau, Inner Mongolia, and Northwest China, the daily global SSI is higher than other areas. In contrast, the values of daily global SSI is relatively low in the eastern regions of Southwest and Northeast China.

Impact of urbanization on surface energy balance components over metropolitan cities of India during 2000–2018 winter seasons

The present study attempts to evaluate the urban energy balance components concerning increasing urbanization and artificial surfaces over Indian metropolitan cities during the 2000–2018 winter seasons by using Landsat 7 and 8 satellite imageries. The results indicate that the estimated ranges of the energy fluxes are in the typical values reported in the earlier literature over global cities. The sensible heat flux (SHF) increased considerably, and the latent heat flux (LHF) slightly decreased during the study period. The mean SHF over the built-up areas (BA) and the dry lands (DL) of Delhi record a maximum increase of 28.2 Wm−2and 39.7 Wm−2 during the study period. The inland cities have high values of SHF over DL than the coastal cities, and the LHF is high over all the land use classes for the west coast cities. The SHF (LHF) shows a positive (negative) correlation with the land surface temperature. The SHF (LHF) is about 19–33% (1.9–15%) of the net radiation flux, and the residual heat flux is about 60 to 80% of the net radiation flux. The present study advocates that the substantial changes of the surface energy balance parameters have a profound influence on the energy exchange mechanism and could affect regional climatic change.

Obesity and its associated inflammatory cytokines pose significant risk factors for COVID-19 outcomes

The incidence of overweight, obesity and non-alcoholic fatty liver disease (NAFLD) in Western society have increased to epidemic proportions in the past decade and are now recognized as significant progressive comorbidities contributing to complications of COVID-19. Adiposity reflects an imbalance in energy homeostasis, where cumulative energy intake chronically exceeds net energy expenditure often associated with Insulin resistance (IR) and other endocrinopathies which further impairs parameters of energy balance and expenditure. A primary function of white adipose tissues (WAT) is nutritionally and hormonally mediated lipogenesis and lipid storage in the form of triglycerides, derived from dietary or de novo substrates. Central adiposity, including visceral adipose depots is typically associated with chronic inflammation and endocrine dysregulation including elevations in plasma insulin, amylin, and hyperlipidemia, a suppressed immune response, and elevations in markers of inflammation in peripheral tissues, which are contributory to the progression of the cardiovascular, renal, and other significant comorbid sequela that often follow. Multiple mechanisms are operative in obesity that contribute to the magnitude of severity of COVID-19 illness. 1: The SARS-CoV-1 can infect multiple organ systems that contain ACE2 receptors, including WAT; 2. The SARS-CoV-2 virus contains abundant viral spike proteins compatible with the ACE2 receptors of WAT, enabling the efficient uptake of COVID-19 viral particles; 3: WAT secretes the inflammatory cytokines TNF, IL-6, and others, augmented by adipocytokines leptin and resistin, which together facilitate the creation of an enhanced inflammatory state combined in concert with the suppressed immune state; 4: WAT secretes leptin, TNFα, CXCL-10 and other inflammatory adipokines that are common factors in central obesity have been correlated with the severity of COVID-19 in obese individuals, and 5: the cytokine IL-6 from WAT acts as a primary mediator of the cytokine storm inflammatory response which typically leads to the development of an acute respiratory distress syndrome (ARDS) often with dire consequences in later stages of COVID-19. NAFLD also correlates with hyperlipidemia and the severity of COVID-19 in a similar manner. Thus, the inflammatory markers and the lipogenic characteristics of IR, excess adiposity, chronic inflammation, and related sequelae are significant opportunistic contributors to the magnitude of severity and outcome of the morbidity and mortality observed in COVID-19 illness. The purpose of this editorial review is to present an overview of the contributions of obesity and its endocrinologic and inflammatory pathophysiologic sequelae on COVID-19 illness.

Techno-economic modeling to produce biodiesel from marine microalgae in sub-Saharan countries: An exploratory study in Guinea-Bissau

Commercial production and academic research on microalgae for biodiesel are in their infancy. This research explores the case of a sub-Saharan country that has limited resources (land) to produce biodiesel from first-generation feedstock (oilseed or animal fat) but has abundant availability of coastal sea areas and solar irradiation to produce microalgae (feedstock for third-generation biofuels). This article deals with the technoeconomic analysis of biodiesel production from microalgae in Guinea-Bissau. The Aspen Plus® V12 simulator was used to model the flowsheet of chemical conversion processes from microalgae oil to biodiesel production and to widen the technoeconomic assessment. Simulations revealed that for a production of 5.47 m³ d-1 of biodiesel (incorporating 3% of biodiesel into the conventional diesel), the estimated cost is 0.9 US$ kg-1 and the cultivated area is 1.5 × 102 ha. This cost is promisingly competitive with the diesel in the service station in Guinea-Bissau. Sensitivity analyses of predictive scenarios allowed us to identify significant gains in the scale of production. The widening of the scope of the feasibility simulations, including chemical processes, technological alternatives, mass and energy balance, environmental impacts, and productive and economic parameters, is a relevant contribution to the advancement of the techno-economic analysis of microalgae bioenergy production on a commercial scale. Although Guinea-Bissau has a small biodiesel demand, the scenarios are encouraging and may be explored as a bottom line to support the policy and investment decision-making processes to design a biodiesel from microalgae program in Guinea-Bissau and other coastal sub-Saharan countries.

Multi-decadal analysis of high-resolution albedo changes induced by urbanization over contrasted Chinese cities based on Landsat data

Surface albedo is a key parameter in the surface energy balance and has been identified as a primary essential climate variable (ECV). Variations in surface albedo can be used as a diagnostic tool for local climate change. This is particularly true in urban areas, where the impacts of land cover conversion due to increasing anthropogenic demands can be examined using surface albedo changes. Most of the previous studies of albedo in cities have relied on coarse-resolution datasets with short time spans and have disregarded continuous monitoring. In addition, it is still unclear which urbanization processes are involved and what effects they have on surface albedo over long time periods. This study aimed to identify the contribution of increasing urbanization to the regional climate by analyzing spatial and temporal changes in surface albedo. Assigning albedo values to land cover types is useful for determining the level of transformation and their impacts in various Chinese cities that underwent specific evolutions between 1986 and 2018. The Direct Estimation (DE) approach was modified to estimate the daily mean surface albedo at 30 m based on Landsat observations. It resulted root-mean-square errors (RMSEs) of less than 0.044 and bias about 0.006 between observations and model estimations. Such accuracy obtained after correcting the orbital drift of the Landsat satellite, was deemed satisfactory for detecting potential changes in albedo. Major findings are: 1) A notable trend was found over the past 33 years of 11 major Chinese cities, i.e. population about 10 million and more, with a general albedo increase from satellite observations. The higher resolution Landsat dataset showed a trend 3 times larger than the Global Land Surface Satellites (GLASS) product, which outlines the need for analyzing high resolution imagery in priority for reliable estimate of albedo over heterogeneous urban landscapes. 2) An increase in albedo infers a negative radiative forcing at an average rate of −2.771 W/m2 per decade, thereby indicating a cooling effect for most Chinese cities. 3) Changes in surface albedo were also closely linked to landscape transformation, clearly observed using the 30 m resolution of the Landsat data. 4) Throughout the study period, surface albedo exhibited a temporal U-shaped curve in built-up areas under development, with albedo peaks in old and newly built districts and a decrease in albedo between the two eras.

Retrieval of Outgoing Longwave Radiation from the Fengyun-3D Satellite and Its Climate Applications

The Fengyun-3D (FY-3D) satellite is a Chinese Earth observation satellite with high spectral resolution that can provide multi-spectral observations under all weather conditions. Outgoing longwave radiation (OLR) is an important parameter in the earth radiation energy balance and can reflect changes in atmospheric circulation and convective activity in response to incoming solar radiation. To apply the OLR data of the FY-3D satellite (F_OLR) to weather and climate analyses, the traditional single-channel OLR inversion algorithm for the NOAA (National Oceanic and Atmospheric Administration) satellite was used to calculate F_OLR, and the difference between F_OLR and the OLR data of the NOAA 18 satellite (N_OLR) was analyzed. A correction algorithm was proposed to correct F_OLR to match N_OLR; the spatiotemporal consistency of the corrected F_OLR and N_OLR was evaluated, and the two types of OLR data were used to analyze the onset of the South China Sea Summer Monsoon (SCSSM) and typhoon precipitation in China. The results showed that the corrected F_OLR and N_OLR were consistent in both temporal variation and spatial distribution and that the monitoring of the SCSSM and typhoon precipitation by the two types of OLR data was also in agreement, showing their equivalent quality. Finally, the N_OLR (2006–2019) and the corrected F_OLR (2020-present) were combined to form a long time series OLR dataset that was used in the Beijing Climate Center climate monitoring system in China to monitor abnormal changes in the global convective activity. This study can provide a reference method for future weather and climate applications of Chinese satellites.

The impact of yoga on components of energy balance in adults with overweight or obesity: A systematic review.

BackgroundYoga may reduce body weight in individuals with overweight or obesity, but whether this occurs through decreased energy intake (EI) or increased energy expenditure (EE)/physical activity (PA) is unclear.MethodsA systematic search of PubMed, Web of Science, Embase, and PsychINFO was conducted from inception until April 26, 2021. Eligible studies included randomized controlled trials or single‐arm pre‐post studies with any type and duration of yoga intervention in adults with overweight or obesity. Studies with measures related to EI , EE, or PA were eligible. The review initially identified 1,373 articles.ResultsOf the 10 included studies, one used indirect calorimeter measures of resting EE, while nine used self‐reported measures of EI and PA. Of the seven studies measuring parameters related to EI, only one found greater decreases in EI relative to the control group, although three other investigations reported trends toward improved dietary intake. Of the eight studies measuring PA, two reported greater increases in resting EE or PA in the yoga group relative to the control group. Two reported significant within‐group increases in PA from pre‐post intervention, and four studies reported a trend for increased PA with no p‐values reported.ConclusionsLimited evidence suggests yoga may reduce EI and increase PA in adults with overweight or obesity. Additional studies that investigate the effects of yoga interventions on energy balance parameters using objective techniques are warranted.

Evaluation of satellite land surface albedo products over China using ground-measurements

ABSTRACT Land surface albedo (LSA) is an important parameter in surface energy balance and global climate change. It has been used in the fields of energy budgets, climate dynamics, and land surface processes. To apply satellite LSA products more widely, the product accuracy needs to be evaluated at different scales and under atmospheric and surface conditions. This study validates and analyzes the errors of the LSA datasets from the Global LAnd Surface Satellites (GLASS) product, the European Space Agency’s Earth Observation Envelope Programme (GlobAlbedo), the Quality Assurance for Essential Climate Variables (QA4ECV) project, the Gap-filled Snow-free Bidirectional Reflectance Distribution Function (BRDF) parameters product (MCD43GF), and the Satellite Application Facility on Climate Monitoring (CM SAF) Albedo dataset from the AVHRR data (CLARA-SAL) against the Chinese Ecosystem Research Network (CERN) measurements at different spatiotemporal scales over China from 2005 to 2015. The results show that LSA estimated by GLASS agrees well with the CERN measurements on a continental scale. The GLASS product is characterized by a correlation coefficient of 0.80, a root-mean-square error of 0.09, and a mean absolute error of 0.06. The consistency between GLASS, GlobAlbedo, and CLARA-SAL is slightly lower over the regions with high aerosol optical depth (AOD) (e.g. Sichuan Basin, northern China) and high cloud cover compared with that in regions with lower AOD and low cloud cover. The estimation errors are related to varying atmospheric and surface conditions and increase with increasing AOD and cloud cover and decreasing enhanced vegetation index. Therefore, algorithms under complex atmospheric and surface conditions (e.g. high AOD, sparse vegetation) should be optimized to improve the accuracy of LSA products.