Energy Balance Fluxes Research Articles

Assessing the impact of artificial geotextile covers on glacier mass balance and energy fluxes

As global warming accelerates, leading to the retreat of glaciers, the effectiveness of artificial coverings, in particular geotextiles, in reducing glacier ablation has emerged as a topic of increasing concern. Nevertheless, a critical gap in knowledge persists regarding the specific physical processes involved in the mitigation provided by these coverings. This study explores the underlying mechanisms that govern the interaction through field observations and COSIPY model simulations at Bailanghe Glacier No. 21 in the Qilian Mountains from 26 June to 17 September 2023. It compares covered and uncovered areas to evaluate differences in mass and energy balance fluxes. It was discovered that geotextiles could decrease ice melt by up to 1000 mm w.e. in comparison to the surface of glaciers without cover, primarily because of a 23% increase in albedo compared to ice, leading to a decrease in net short-wave radiation and available melt energy. The effect of covering the entire glacier with a geotextile, which has varying albedo properties, was also simulated. It was found that, with every 5% increase in the albedo of the geotextile, ablation was reduced by 10%‒25%, resulting in a decrease in ice volume loss of approximately 2.5 × 105 m3. While artificially covering glaciers can reduce ablation rates, it faces challenges such as high costs, environmental risks, and issues with replicability. Ultimately, this study aims to analyze the feasibility of glacier coverage from a mechanistic perspective for glacier management amidst ongoing climate change.

Characterizing the seasonal relationships between urban heat island and surface energy balance fluxes considering the impact of three-dimensional urban morphology

Urbanization has disrupted the energy balance of natural surfaces, leading to the formation and intensification of urban heat island (UHI) phenomenon. Current research on the relationship between surface energy balance (SEB) and UHI mainly focuses on either a macro perspective of large-scale regions or a micro perspective based on numerical microclimate simulations. However, there are still relatively few studies conducted on the local scale of cities. Here, we investigated the relationships between seasonal SEB and land surface temperature (LST) based on local climate zones (LCZ) and explored the impact of three-dimensional (3D) urban morphology on SEB. Our results revealed that: (1) urban building spaces have relatively higher LST, sensible heat flux, and storage heat flux, but lower net radiation and latent heat flux, compared to urban blue and green spaces; (2) among LCZ built types, the compact and large low-rise buildings have high LST and heat-inducing energy fluxes, while the compact and open high-rise buildings exhibit the opposite situation; (3) the component proportions of SEB fluxes exhibit a more significant linear correlation with UHI intensity compared to the relative differences between SEB fluxes; and (4) 3D building morphology has a higher relative importance in influencing the variations of surface energy balance ratio (SEBR) components than 3D vegetation morphology. Specifically, building height has the greatest impact on the seasonal variations of SEBR components, while the 3D urban greening ratio has relatively high importance among vegetation morphology. These findings enable us to better consider local UHI effect from the perspective of SEB.

Evaluation of a single-layer urban energy balance model using measured energy fluxes by scaled outdoor experiments in humid subtropical climate

Urban energy balance models can simulate the localized climate and fluxes in urban areas. They are often evaluated using real urban site observations. However, uncertainties in anthropogenic emission, geometry and materials can hinder interpretation. These uncertainties can be eliminated by scaled outdoor models. We assess the performance of a single-layer urban canopy model (SLUCM) offline in predicting surface energy balance (SEB) fluxes within a street canyon-like urban configuration using field measurements from a scaled outdoor setup in Guangzhou, China. We utilize observations of SEB fluxes and surface temperature from a homogenous scaled urban site characterized by street canyons. The scaled observations in June–December 2020 in a dense urban environment with a height-to-width ratio (H/W) of 2 are employed to assess seasonal variations in model performance. Additionally, the December data from two distinct urban scenarios (H/W = 2(2020) and 0.5(2019)) are utilized to compare model performance in deep and shallow street canyon settings. Results show that QS(R2 = ∼0.47, RMSE = ∼46.0) is the most challenging to predict, followed by QH (R2 = ∼0.92, RMSE = ∼65.5), Q*(R2 = ∼0.99, RMSE = ∼39.5), L↑(R2 = ∼0.95, RMSE = ∼33.7), and K↑(R2 = ∼0.99, RMSE = ∼6.2). SLUCM faces difficulties simulating L↑ particularly during nighttime and cloudy conditions. It also tends to underestimate daytime net radiation (Q*), especially during hot, humid months. Moreover, H/W ratio slightly affects SLUCM's performance in simulating SEB fluxes under dry cool conditions denser urban settings (H/W = 2) show better model performance in K↑, QH, and QS but worse performance in L↑ and Q*.

Surface energy balance fluxes in a suburban area of Beijing: energy partitioning variability

Abstract. Measurements of radiative and turbulent heat fluxes for 16 months in suburban Miyun with a mix of buildings and agriculture allows the changing role of these fluxes to be assessed. Daytime turbulent latent heat fluxes (QE) are largest in summer and smaller in winter, consistent with the net all-wave radiation (Q*), whereas the daytime sensible heat flux (QH) is greatest in spring but smallest in summer rather than in winter, as commonly observed in suburban areas. The results have larger seasonal variability in energy partitioning compared to previous suburban studies. Daytime energy partitioning is between 0.15–0.57 for QH/Q* (mean summer = 0.16; winter = 0.46), 0.06–0.56 for QE/Q* (mean summer = 0.52; winter = 0.10), and 0.26–7.40 for QH/QE (mean summer = 0.32; winter = 4.60). Compared to the literature for suburban areas, these are amongst the lowest and highest values. Results indicate that precipitation, irrigation, vegetation growth activity, and land use and land cover all play critical roles in the energy partitioning. These results will help to enhance our understanding of surface–atmosphere energy exchanges over cities and are critical to improving and evaluating urban canopy models needed to support integrated urban services that include urban planning to mitigate the adverse effects of urban climate change.

Influence of the biochar application on the thermal properties of soddy-podzolic soil and on the energy balance fluxes of spring wheat in the Leningrad region under various soil moisture conditions

The article presents the results of a field experiment to assess the effect of pre-sowing application of the biochar on the thermal properties of the arable horizon of soddy-podzolic sandy loam soil, on the energy balance components, on the crop surface temperature and on the leaves temperature of spring wheat (variety “Daria”) under various conditions of soil moisture in 2022. The experiment took place at the Menkovo Experimental Station of the Agrophysical Research Institute, located in the Gatchinsky District of the Leningrad Region. The experiment included the plot with the biochar application at the dose of 21.9 t ha-1 and the control plot. The soil thermal properties were measured by the heat pulse method. The components of the energy balance were determined using agrometeorological measurements, radiation balance measurements, crop surface temperature, and phenological measurements. The crop surface temperature was measured by a non-contact method using pyrometers. The soil moisture conditions and available water for wheat were characterized by volumetric soil moisture and evapotranspiration. The volumetric soil moisture was measured using a capacitive soil moisture sensor. The evapotranspiration was determined using the residual term of the energy balance equation through the latent heat flux. According to the results of field experiments, a significant effect (p < 0.05) of the biochar application on the soil thermal properties was found, however, under different moisture conditions, the effect was multidirectional. At zero soil moisture, the biochar application reduced thermal conductivity by 29.7%, reduced volumetric heat capacity by 18.5%, reduced diffusivity by 13.7%, and reduced thermal inertia by 24.3%. Under the conditions of field capacity, the biochar application increased thermal conductivity by 9.4%, reduced volumetric heat capacity by 2.6%, increased diffusivity by 12.3%, and increased thermal inertia by 3.2%. The biochar application significantly (p < 0.05) increased the turbulent heat flux – by 35.5%, which is due to an increase in the crop surface temperature (by 6.4%). Resulting from the decrease in soil evaporation, the biochar application reduced the latent heat flux by 17.0%, and the evapotranspiration by 13.9%. Leaf temperature is related to transpiration. Transpiration can increase when biochar is applied on light-textured soils due to an increase in soil water capacity. The biochar application did not result in significant changes of leaf temperature. The study results are confirmed by numerous articles of both foreign and Russian researchers.

Assessment of urban green areas towards changing surface energy balance fluxes in tropical study sites, Central Thailand

The surface energy balance is broadly accepted as the interaction of the available energy fluxes that leads to the evaporation of surface water and an increase or decrease in the temperature of the surface and pertinent environment. This concept is widely utilized, shifting the increasing urbanization towards sustainable cities on a scientific basis for the planning and management of urban areas. Understanding the ambient factors governing energy fluxes will help mitigate the environmental burden linked to climate change by optimizing the layout of sustainable townships. For a quantitative description, we applied the eddy covariance method, which is one of the most widely accepted methods of monitoring flux changes, at different land-usage and surface-cover locations in an urban area (Kasetsart University (KU) tower), a rural natural mangrove forest environmental system (LERD project), and a spacious urban park estate (Bangkok, Bangkajao District). The results suggested that urban land usage has led to a shift in the ratios of energy fluxes, in which the proportion of latent heat in the mangrove forest area, Bangkajao Green Urban Park, and KU tower were 41%, 29%, and 22%, respectively. However, sensible heat at the KU tower, which is located in the denser urban areas of Bangkok, was predominant at 39% of the heat flux, whereas the transfer of energy into sensible heat in the LERD project and Bangkajao was 17% and 26%, respectively. This study reveals an increase in sensible heat in urban areas and a decrease in latent heat fluxes. Measurements linked to land-use classification showed that changes in the urban structure significantly contributed to heat in the spatial and temporal scales and indicated necessary avenues for the management of urban heat islands and mitigation of related adverse effects.

Development of High-Resolution Soil Hydraulic Parameters with Use of Earth Observations for Enhancing Root Zone Soil Moisture Product

Regional quantification of energy and water balance fluxes depends inevitably on the estimation of surface and rootzone soil moisture. The simulation of soil moisture depends on the soil retention characteristics, which are difficult to estimate at a regional scale. Thus, the present study proposes a new method to estimate high-resolution Soil Hydraulic Parameters (SHPs) which in turn help to provide high-resolution (spatial and temporal) rootzone soil moisture (RZSM) products. The study is divided into three phases—(I) involves the estimation of finer surface soil moisture (1 km) from the coarse resolution satellite soil moisture. The algorithm utilizes MODIS 1 km Land Surface Temperature (LST) and 1 km Normalized difference vegetation Index (NDVI) for downscaling 25 km C-band derived soil moisture from AMSR-2 to 1 km surface soil moisture product. At one of the test sites, soil moisture is continuously monitored at 5, 20, and 50 cm depth, while at 44 test sites data were collected randomly for validation. The temporal and spatial correlation for the downscaled product was 70% and 83%, respectively. (II) In the second phase, downscaled soil moisture product is utilized to inversely estimate the SHPs for the van Genuchten model (1980) at 1 km resolution. The numerical experiments were conducted to understand the impact of homogeneous SHPs as compared to the three-layered parameterization of the soil profile. It was seen that the SHPs estimated using the downscaled soil moisture (I-d experiment) performed with similar efficiency as compared to SHPs estimated from the in-situ soil moisture data (I-b experiment) in simulating the soil moisture. The normalized root mean square error (nRMSE) for the two treatments was 0.37 and 0.34, respectively. It was also noted that nRMSE for the treatment with the utilization of default SHPs (I-a) and AMSR-2 soil moisture (I-c) were found to be 0.50 and 0.43, respectively. (III) Finally, the derived SHPs were used to simulate both surface soil moisture and RZSM. The final product, RZSM which is the daily 1 km product also showed a nearly 80% correlation at the test site. The estimated SHPs are seen to improve the mean NSE from 0.10 (I-a experiment) to 0.50 (I-d experiment) for the surface soil moisture simulation. The mean nRMSE for the same was found to improve from 0.50 to 0.31.

Seasonal peak photosynthesis is hindered by late canopy development in northern ecosystems.

The seasonal dynamics of the vegetation canopy strongly regulate the surface energy balance and terrestrial carbon fluxes, providing feedbacks to climate change. Whether the seasonal timing of maximum canopy structure was optimized to achieve a maximum photosynthetic carbon uptake is still not clear due to the complex interactions between abiotic and biotic factors. We used two solar-induced chlorophyll fluorescence datasets as proxies for photosynthesis and the normalized difference vegetation index and leaf area index products derived from the moderate resolution imaging spectroradiometer as proxies for canopy structure, to characterize the connection between their seasonal peak timings from 2000 to 2018. We found that the seasonal peak was earlier for photosynthesis than for canopy structure in >87.5% of the northern vegetated area, probably leading to a suboptimal maximum seasonal photosynthesis. This mismatch in peak timing significantly increased during the study period, mainly due to the increasing atmospheric CO2, and its spatial variation was mainly explained by climatic variables (43.7%) and nutrient limitations (29.6%). State-of-the-art ecosystem models overestimated this mismatch in peak timing by simulating a delayed seasonal peak of canopy development. These results highlight the importance of incorporating the mechanisms of vegetation canopy dynamics to accurately predict the maximum potential terrestrial uptake of carbon under global environmental change.

A coupled ground heat flux–surface energy balance model of evaporation using thermal remote sensing observations

Abstract. One of the major undetermined problems in evaporation (ET) retrieval using thermal infrared remote sensing is the lack of a physically based ground heat flux (G) model and its integration within the surface energy balance (SEB) equation. Here, we present a novel approach based on coupling a thermal inertia (TI)-based mechanistic G model with an analytical surface energy balance model, Surface Temperature Initiated Closure (STIC, version STIC1.2). The coupled model is named STIC-TI. The model is driven by noon–night (13:30 and 01:30 local time) land surface temperature, surface albedo, and a vegetation index from MODIS Aqua in conjunction with a clear-sky net radiation sub-model and ancillary meteorological information. SEB flux estimates from STIC-TI were evaluated with respect to the in situ fluxes from eddy covariance measurements in diverse ecosystems of contrasting aridity in both the Northern Hemisphere and Southern Hemisphere. Sensitivity analysis revealed substantial sensitivity of STIC-TI-derived fluxes due to the land surface temperature uncertainty. An evaluation of noontime G (Gi) estimates showed 12 %–21 % error across six flux tower sites, and a comparison between STIC-TI versus empirical G models also revealed the substantially better performance of the former. While the instantaneous noontime net radiation (RNi) and latent heat flux (LEi) were overestimated (15 % and 25 %), sensible heat flux (Hi) was underestimated (22 %). Overestimation (underestimation) of LEi (Hi) was associated with the overestimation of net available energy (RNi−Gi) and use of unclosed surface energy balance flux measurements in LEi (Hi) validation. The mean percent deviations in Gi and Hi estimates were found to be strongly correlated with satellite day–night view angle difference in parabolic and linear pattern, and a relatively weak correlation was found between day–night view angle difference versus LEi deviation. Findings from this parameter-sparse coupled G–ET model can make a valuable contribution to mapping and monitoring the spatiotemporal variability of ecosystem water stress and evaporation using noon–night thermal infrared observations from future Earth observation satellite missions such as TRISHNA, LSTM, and SBG.

Identification and Quantification of Actual Evapotranspiration Using Integrated Satellite Data for Sustainable Water Management in Dry Areas

Evapotranspiration (ET) is a significant consumer of irrigation water and precipitation on cropland. Global and regional interest in the sustainable management of limited freshwater supplies to meet the rapidly increasing population and food demands has resulted in advanced scientific research on ET measurement, rapid water accounting, and irrigation schedules in the NENA region. The primary goal of this paper is to compare actual daily evapotranspiration (ET) collected by a remote sensing model and validated by Energy Balance (EB) flux tower field measurements. The flux tower was installed in a wheat field in Sids Agricultural Research Station in Beni Suef Governorate. Through the integration of Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Sentinel-2 data, a new remote sensing-based ET model is built on two parties: Thermal condition factor (TCF) and vegetation condition fraction (VCF). The remote sensing-based ET estimation model was evaluated using ET field measurements from the Energy Balance flux tower. The land use and land cover maps were created to assist the interpretation of remotely sensed ET data. Field data for five categories were collected to test the accuracy of the land use and cover maps: Water bodies (93 points), urban areas (252 points), trees (104 points), other field crops (227 points), and wheat (249 points), for a total of 925 ground points. The Google Earth Engine (GEE) imported sentinel-2 datasets and filtered the necessary dates and regions. From 1 October 2020 to 30 May 2021, sentinel-2 data were processed and transformed into the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Built-up Index (NDBI), which were then combined. The composite layer data were classified using the Random Forest (RF) method on the GEE platform, and the results showed an overall accuracy of 91 percent. The validation factors revealed good indices when RS-based ET results were compared to ground-measured ET. The Root Mean Square Error (RMSE) was 0.84 mm/day. The ‘r’ and ‘d’ values indicated satisfactory results, where ‘r’ yielded a value of 0.785, which indicates that the correlation between predicted and reference results is robust. The analysis of d values revealed a high degree of correlation between predicted (RS-based ET) and reference results (measured ET). The d value was found to be 0.872. Between 21 November 2020 and 30 April 2021, RS-based accumulated ET was 418 mm/season, while ground-measured ET was 376 mm/season. The new RS-based ET model produced acceptable daily and seasonal results.

Evapotranspiration Retrieval Using S-SEBI Model with Landsat-8 Split-Window Land Surface Temperature Products over Two European Agricultural Crops

Crop evapotranspiration (ET) is a key variable within the global hydrological cycle to account for the irrigation scheduling, water budgeting, and planning of the water resources associated with irrigation in croplands. Remote sensing techniques provide geophysical information at a large spatial scale and over a relatively long time series, and even make possible the retrieval of ET at high spatiotemporal resolutions. The present short study analyzed the daily ET maps generated with the S-SEBI model, adapted to Landsat-8 retrieved land surface temperatures and broadband albedos, at two different crop sites for two consecutive years (2017–2018). Maps of land surface temperatures were determined using Landsat-8 Collection 2 data, after applying the split-window (SW) algorithm proposed for the operational SW product, which will be implemented in the future Collection 3. Preliminary results showed a good agreement with ground reference data for the main surface energy balance fluxes Rn and LE, and for daily ET values, with RMSEs around 50 W/m2 and 0.9 mm/d, respectively, and high correlation coefficient (R2 = 0.72–0.91). The acceptable uncertainties observed when comparing with local ground data were reaffirmed after the regional (spatial resolution of 9 km) comparison with reanalysis data obtained from ERA5-Land model, showing a StDev of 0.9 mm/d, RMSE = 1.1 mm/d, MAE = 0.9 mm/d, and MBE = −0.3 mm/d. This short communication tries to show some preliminary findings in the framework of the ongoing Tool4Extreme research project, in which one of the main objectives is the understanding and characterization of the hydrological cycle in the Mediterranean region, since it is key to improve the management of water resources in the context of climate change effects.

Revising the definition of anthropogenic heat flux from buildings: role of human activities and building storage heat flux

Abstract. Buildings are a major source of anthropogenic heat emissions, impacting energy use and human health in cities. The difference in magnitude and time lag between building energy consumption and building anthropogenic heat emission is poorly quantified. Energy consumption (QEC) is a widely used proxy for the anthropogenic heat flux from buildings (QF,B). Here we revisit the latter's definition. If QF,B is the heat emission to the outdoor environment from human activities within buildings, we can derive it from the changes in energy balance fluxes between occupied and unoccupied buildings. Our derivation shows that the difference between QEC and QF,B is attributable to a change in the storage heat flux induced by human activities (ΔSo-uo) (i.e. QF,B=QEC-ΔSo-uo). Using building energy simulations (EnergyPlus) we calculate the energy balance fluxes for a simplified isolated building (obtaining QF,B, QEC, ΔSo-uo) with different occupancy states. The non-negligible differences in diurnal patterns between QF,B and QEC are caused by thermal storage (e.g. hourly QF,B to QEC ratios vary between −2.72 and 5.13 within a year in Beijing, China). Negative QF,B can occur as human activities can reduce heat emission from a building but this is associated with a large storage heat flux. Building operations (e.g. opening windows, use of space heating and cooling system) modify the QF,B by affecting not only QEC but also the ΔSo-uo diurnal profile. Air temperature and solar radiation are critical meteorological factors explaining day-to-day variability of QF,B. Our new approach could be used to provide data for future parameterisations of both anthropogenic heat flux and storage heat fluxes from buildings. It is evident that storage heat fluxes in cities could also be impacted by occupant behaviour.

Alteration in surface energy balance fluxes induced from long-term disk-tilled versus no-till management in maize production

Impacts of tillage-induced surface conditions on modification of the soil-crop-atmospheric interface have not been adequately studied. There is poor quantitative understanding at the intersection of tillage and surface energy balance (SEB), especially for the complete growing season. This research measured and evaluated SEB fluxes, i.e., net radiation (Rn), latent heat (LE), sensible heat (H), and ground heat flux (G) for three growing seasons (2011–2013) in a concurrent fashion in two similarly-managed maize (Zea mays L.) fields, which were under disk-till (DT) and no-till (NT) management for 17 years. To this end, each field was equipped with an identical Bowen Ratio Energy Balance System (BREBS) that collected 30-minute SEB data throughout the growing season. G was the most impacted SEB component, followed by H, LE, and Rn on an average basis, although these comparisons were subject to change during different times in the growing season. Seasonal mean interpretations masked within-season heterogeneity in DT vs. NT SEB dynamics and thus, daily differences for all SEB components, albedo (α), surface soil moisture (θv), and Bowen Ratio (β) were quantified. Greater α in NT field (0.16) was maintained throughout the growing season than DT field (0.14). All SEB components demonstrated greater differences between DT and NT in the early and late growing season. Nevertheless, SEB observations show that tillage impacts during significant crop canopy cover should not be ignored. NT surface (0–0.30 m) θv was as much as 22% greater than that of DT, and held critical importance for regional NT crop production during the extreme 2012 drought. θv also exerted control on albedo, with wetter soils having a lower albedo, which consequently translated into altered Rn across DT and NT fields. The research findings shown here underscore the particular importance of accounting for within-season behavior of albedo and G along with other components of SEB for evaluating soil management-related applications.

Influence of short-term surface temperature dynamics on tree orchards energy balance fluxes

Land surface temperature (LST) plays an essential role in developing and applying precision agriculture protocols, especially for calculating crop evapotranspiration (ETc) by surface energy balance (SEB) approaches; and for determining crop water status. However, LST is quite dependent on the meteorological conditions, which can rapidly vary. This variability, together with the limited meterological data acquisition frequency in most weather stations, can lead to the miscalculation of the SEB components, especially relevant when used for irrigation purposes.The present study assessed the temporal dynamic of LST in a very short period of time (20-minutes) through the acquisition of multiple thermal imagery. Additionally, a combination of SEB approach with Eddy Covariance technique was performed for quantifying the effect that LST variations have on the sensible (H) and latent (LE) heat fluxes.Even under steady meteorological conditions, temporal variations in LST of 3.5 and 4.0 K were observed for tree canopy and sunny bare soil surfaces, respectively. These LST oscillations reached values of about 7.8 and 17.9 K for tree canopies and bare soil when heterogeneous meteorological conditions were observed (i.e. cloud presence). Such LST differences translated into H and LE differences of about 26 and 19%, respectively; with variations up to 5 (for H) and 2.7 times (for LE) under fast-varying meteorological conditions.The obtained results suggest the necessity of acquiring thermal imagery when steady meteorological conditions exist or, otherwise, ensuring the collection of instantaneous meteorological data for applying post-processing corrections. This is of importance when incorporating the obtained ETc maps into precision irrigation protocols.

Surface Albedo and Temperature Models for Surface Energy Balance Fluxes and Evapotranspiration Using SEBAL and Landsat 8 over Cerrado-Pantanal, Brazil

The determination of the surface energy balance fluxes (SEBFs) and evapotranspiration () is fundamental in environmental studies involving the effects of land use change on the water requirement of crops. SEBFs and have been estimated by remote sensing techniques, but with the operation of new sensors, some variables need to be parameterized to improve their accuracy. Thus, the objective of this study is to evaluate the performance of algorithms used to calculate surface albedo and surface temperature on the estimation of SEBFs and in the Cerrado-Pantanal transition region of Mato Grosso, Brazil. Surface reflectance images of the Operational Land Imager (OLI) and brightness temperature () of the Thermal Infrared Sensor (TIRS) of the Landsat 8, and surface reflectance images of the MODIS MOD09A1 product from 2013 to 2016 were combined to estimate SEBF and by the surface energy balance algorithm for land (SEBAL), which were validated with measurements from two flux towers. The surface temperature () was recovered by different models from the and by parameters calculated in the atmospheric correction parameter calculator (ATMCORR). A model of surface albedo () with surface reflectance OLI Landsat 8 developed in this study performed better than the conventional model () SEBFs and in the Cerrado-Pantanal transition region estimated with combined with and performed better than estimates with . Among all the evaluated combinations, SEBAL performed better when combining with the model developed in this study and the surface temperature recovered by the Barsi model (). This demonstrates the importance of an model based on surface reflectance and atmospheric surface temperature correction in estimating SEBFs and ET by SEBAL.

Assessment of spatio-temporal changes of land surface temperature (LST) in Kanchenjunga Biosphere Reserve (KBR), India using Landsat satellite image and single channel algorithm

Land surface temperature (LST) is known as skin temperature of the earth surface and it is used for analyzing the energy balance and thermal flux of the earth surface. The rise of surface temperature is a major environmental concern at present day. The present study analyzed the spatio-temporal pattern and changes of LST in Kanchenjunga Biosphere reserve (KBR) of Sikkim Himalaya, India from 1994 to 2019. Single channel algorithm has been used to estimate the LST from Landsat 5, 7 and 8 satellite imageries. Correlation analysis was carried out to understand the correlation of LST with altitude, vegetation indices, snow index and water index. The result shows there is bilinear correlation between LST with altitude, vegetation indices (NDVI, PV and EVI), snow index (NDSI) and water index (NDWI). Vegetation indices positively correlated with LST whereas NDSI and NDWI negatively correlated with LST. To understand the spatial association of LST, Moran's spatial autocorrelation method has been used which reveals that there is strong positive spatial uniformity of LST. Local Moran's I index was used to detect spatio-temporal cluster pattern and outlier of LST from 1994 to 2019. Spatial mean method used to understand the spatio-temporal changes of LST in the study area. From this analysis, it is clear that there is significant spatio-temporal change of LST observed in the study area.

Energy Balance, CO2 Balance, and Meteorological Aspects of Desertification Hotspots in Northeast Brazil

The main objective of this study was to evaluate meteorological variables and the simulated components of energy and CO2 balances in desertification hotspots in Northeast Brazil. Meteorological data were obtained from the National Institute of Meteorology measurement network for the Cabrobó and Ibimirim sites. Initially, hourly linear trends were calculated for the meteorological variables using the non-parametric Mann–Kendall test. Then, the seasonal variability in the components of energy and CO2 balances was assessed through simulations of the simple tropical ecosystem (SITE) model. Results showed evidence of increasing air temperature trends in the Cabrobó site in the first months of the year, which was not observed in the Ibimirim site. Regarding relative humidity, increasing trends were observed in a few months over the Cabrobó site, while decreasing trends were observed in the Ibimirim site. Opposite behaviors were also identified for the trends in wind speed in both sites. Gross primary production (GPP) and net ecosystem exchange (NEE) simulated values were higher in the first half of the year in both sites. GPP varied from 0.8 to 1.2 g C m−² h−¹, and NEE fluctuated around approximately −5 g C m−² h−¹. These results indicate that rainfall seasonality is a crucial factor for the modulation of CO2 and energy balance fluxes in the Caatinga biome.

Distributed Energy Balance Flux Modelling of Mass Balances in the Artesonraju Glacier and Discharge in the Basin of Artesoncocha, Cordillera Blanca, Peru

A distributed energy balance model (DEBAM) is applied to estimate the mass balance of the Artesonraju glacier in the Cordillera Blanca (CB), Peru, and to simulate the ensuing discharge into its respective basin, Artesoncocha. The energy balance model calibrations show that, by using seasonal albedos, reasonable results for mass balances and discharge can be obtained, as witnessed by annually aggregated Nash Sutcliffe coefficients (E) of 0.60–0.87 for discharge and of 0.58–0.71 for mass measurements carried out in the period 2004–2007. Mass losses between −1.42 and −0.45 m.w.e. are calculated for that period. The elevation line altitudes (ELAs), which lie between 5009 and 5050 m.a.s.l., are also well simulated, compared to those measured by the Unidad Glaciologica de Recursos Hídricos del Perú (UGRH). It is demonstrated that the net radiation which drives the energy balance and melting processes is mainly affected by the amount of reflected shortwave radiation from the different surfaces. Moreover, the longwave radiation sinks between 63 and 73% of solar radiative energy in the dry season. Further sensitivity studies indicate that the assumed threshold temperature T0 is crucial in mass balance simulations, as it determines the extension of areas with different albedos. An optimal T0 between 2.6 and 3.8 °C is deduced from these simulations.

Influence of bushfire on accumulation and ablation of a marginal montane snowpack in Snow Gum forests

Forests modulate energy reaching the Earth’s surface. They can change energy balance fluxes, near-ground meteorological conditions, and seasonal snowpack properties in montane areas. Regions of forests cover are often collocated with areas of freshwater importance for ecosystem and anthropogenic uses. As such, alteration of forests in these regions has the potential to significantly impact water resources that many depend upon for daily life. Warmer climates with marginal snowpacks are known to be particularly vulnerable to impacts of climate change that may increase air temperatures and change precipitation. Similarly, montane forests are also becoming increasingly susceptible to modification by wildfire. This study measured energy fluxes, rates of snow accumulation and ablation, and applied (energy flux adjusted) physically-based snowpack models to examine fire alteration of snowmelt yield. Analysis focused on differences between an undisturbed and fire-disturbed forest stand, and referenced an unforested site. Fire-disturbance of forest canopy enhanced ablation rates by 53% relative to the undisturbed site. SWE storage and snowpack longevity were greater at the undisturbed forest, with seasonal snowpack in the fire-disturbed forest stand existing for 19 fewer days and at the unforested site for 32 fewer days. Overall, our results are congruent with canopy disturbance by fire having the impact of reducing snow accumulation (50 mm less SWE over two seasons, 4% reduction), enhancing ablation through increased evaporation (1% higher at the fire-disturbed site), and less total snowmelt available for runoff (38% less at the fire-disturbed stand). These results have significant implications for montane forests, and quantifies how they modulate energy fluxes, increase snow accumulation, seasonal snowpack longevity and melt volume, and how the impact of fire can persist for decades after burning and leads to reduced sub-alpine snow accumulation and melt.

SCOPE 2.0: a model to simulate vegetated land surface fluxes and satellite signals

Abstract. The Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model aims at linking satellite observations in the visible, infrared, and thermal domains with land surface processes in a physically based manner, and quantifying the microclimate in vegetation canopies. It simulates radiative transfer in the soil, leaves, and vegetation canopies, as well as photosynthesis and non-radiative heat dissipation through convection and mechanical turbulence. Since the first publication 12 years ago, SCOPE has been applied in remote sensing studies of solar-induced chlorophyll fluorescence (SIF), energy balance fluxes, gross primary production (GPP), and directional thermal signals. Here, we present a thoroughly revised version, SCOPE 2.0, which features a number of new elements: (1) it enables the definition of layers consisting of leaves with different properties, thus enabling the simulation of vegetation with an understorey or with a vertical gradient in leaf chlorophyll concentration; (2) it enables the simulation of soil reflectance; (3) it includes the simulation of leaf and canopy reflectance changes induced by the xanthophyll cycle; and (4) the computation speed has been reduced by 90 % compared to earlier versions due to a fundamental optimization of the model. These new features improve the capability of the model to represent complex canopies and to explore the response of remote sensing signals to vegetation physiology. The improvements in computational efficiency make it possible to use SCOPE 2.0 routinely for the simulation of satellite data and land surface fluxes. It also strengthens the operability for the numerical retrieval of land surface products from satellite or airborne data.