Surface Energy Balance Research Articles (Page 1)

Anthropogenic heat (AH) emissions in urban environments alter the surface energy budget and significantly influence urban climates. However, these emissions vary spatiotemporally, leading to considerable uncertainty in their estimation. As remote sensing in the urban environment advances, the remotely sensed urban surface temperatures are becoming increasingly available. Yet, assimilating these observations into surface energy modelling for AH estimation has not been fully explored. In this study, a model for AH estimation based on the Kalman filter-surface energy balance (KF-SEB) is developed. Urban meteorological data, including air temperature and building surface temperature, are assimilated into the Kalman filter (KF), yielding sensible heat flux, building heat storage and estimated AH using the surface energy balance (SEB) equation. The KF-SEB model is evaluated using two forward models with predefined AH emissions. The first model is a simple slab model, and the second one is a more complex single-layer urban canopy model (UCM). The results show that the KF-SEB model accurately captures the magnitude and temporal variation of AH, with reduced uncertainties compared to previous studies. This study offers a novel approach to AH estimation based on urban meteorological data and provides important insights into the feedback between urban microclimates and anthropogenic energy use.This article is part of the theme issue 'Urban heat spreading above and below ground'.

Evaluation of Actual Evapotranspiration from Rice Fields of Odisha Using Remote Sensing Based Surface Energy Balance Approach

Abstract. Accurate Snow Water Equivalent (SWE) estimation is significant for understanding global climate change, surface energy balance, and regional water cycles. However, although many studies have examined the inversion of SWE using active and passive microwave remote sensing, it remains challenging to assess its global distribution with sufficient temporal and spatial resolution and accuracy. Interferometric Synthetic Aperture Radar (InSAR) has become a promising technique for SWE change estimation, which is limited by the optimal radar frequencies and revisit intervals that have not been available until recently. In this study, 12 d Sentinel-1 C-band InSAR data from 2019 to 2021 are used to retrieve ΔSWE (SWE change in one InSAR pair) and cumulative SWE in the Altay region of Xinjiang, China. The correlation between the retrieved ΔSWE and in-situ observations reaches R = 0.56, with a low RMSE of 9.54 mm (n = 152) throughout the two whole snow seasons, with values of R = 0.58 and RMSE of 10.1 mm for 2019–2020, and R = 0.48 and RMSE of 8.6 mm for 2020–2021, respectively. These results are obtained by filtering wet snow. Heavy snowfall leads to decorrelation and phase unwrapping errors, which affect ΔSWE retrieval and are propagated into cumulative SWE. Validation of the cumulative SWE after removing wet snow yields an RMSE of 40.9 mm, which improves to 28.3 mm when high-elevation stations with unwrapping errors due to heavy snowfall are also excluded. InSAR-derived cumulative SWE time series show consistency with ground observations at some stations, though slight overestimations and underestimations are observed due to error accumulation. Various factors combined with validation results show that higher coherence, lower air temperature, and reliable snow density improve the retrieval accuracy. The proposed coherence-weighted least squares phase calibration method demonstrates that selecting at least half of the available in-situ ΔSWE stations for calibration yields reliable ΔSWE estimates, although including more points can further improve the robustness. Calibrating only the integer multiples of 2π provides reasonable accuracy, but is still inferior to the full calibration method, indicating that residual modulo 2π phase has a noticeable contribution to the final inversion accuracy, which highlights that phase calibration plays a key role in the accurate ΔSWE retrieval. This study provides a valuable reference and processing prototype for applying 12 d revisit Sentinel-1 and future NISAR InSAR data to SWE monitoring.

Abstract The strengthening of the zonal sea surface temperature (SST) gradient observed in the tropical Pacific in recent decades is a regional climate change signal that may be outside the range of historical simulations with comprehensive climate models. Given the important role that this change has on other aspects of climate, a series of idealized surface energy balance calculations with imposed parameters are performed to build a baseline understanding of the sensitivities that govern these changes. I quantify the requisite magnitudes of five perturbations that reach a new equilibrium with a mean SST warming of about 0.5 K and about 0.4 K more west Pacific warming than east Pacific warming, based approximately on the observed trends. A characteristic magnitude of zonal asymmetry in a surface energy tendency that can bring changes in line with observed trends is ≈3 W m−2. Strengthened zonal SST gradients can arise from a more zonally asymmetric ocean heat flux that increases by ≈20% K−1 using that implied by ERA5’s surface fluxes, a spatially varying radiative forcing with a west–east contrast of ≈3.3 W m−2, a more amplifying surface radiative feedback in the west than in the east with a contrast of ≈4 W m−2 K−1, a surface-air relative humidity (RH) contrast that increases RH in the west and decreases it in the east by ≈0.5% K−1, or a more zonally asymmetric wind speed that increases by ≈16% K−1. The “storylines” of forced surface energy budget change identified here are valuable in determining the plausibility of mechanisms that may be absent or underestimated in coupled climate model simulations. Significance Statement What is the magnitude of changes in energy fluxes in the tropical Pacific that could provoke the recent several decades of observed sea surface temperature trends? This urgent question of climate science is addressed using surface energy balance calculations with the various input terms perturbed in an idealized manner. These calculations provide an essential order-of-magnitude baseline for evaluating how novel mechanisms that are absent or weak in comprehensive climate model simulations might affect the pattern of historical trends.

Enhancing evapotranspiration estimates in orchards with the Surface Energy Balance for Partially Vegetated surfaces (SEB-PV) model through combined use of gridded soil moisture and temporal upscaling methods.

Breaking the zero-flux paradigm: an iterative surface energy balance framework for enhanced cold pixel characterization

ABSTRACTThe canopy thermal response of natural forests to elevated CO2 (eCO2) is an understudied biophysical feedback in the global climate system. We investigated the effects of eCO2 (150 μmol mol−1 above ambient) on canopy temperature (Tcan) dynamics of mature (> 175 years) Quercus robur (oak) at the Birmingham Institute for Forest Research Free Air CO2 Enrichment (BIFoR‐FACE) facility in Staffordshire, England, during the growing seasons of 2021, 2022 and 2023. We employed long‐term, high‐frequency thermal infrared (TIR) imaging to measure Tcan. Our results show that daily maximum oak Tcan under eCO2 was, on average, approximately 1.3°C higher than under ambient (aCO2) conditions (21.5°C ± 4.4°C for aCO2 vs. 22.8°C ± 5.2°C for eCO2 oaks). Moreover, daily maximum Tcan–air temperature (Tair) differences were significantly higher under eCO2, resulting from more frequent extreme temperature excursions. These differences appear primarily to be driven by reduced stomatal conductance under eCO2, which limits transpirational cooling and alters the surface energy balance. This effect was evident in the different relationship between Tcan–Tair and vapour pressure deficit (VPD) for eCO2 compared to aCO2, showing a reduction in transpirational cooling under high VPD. Also, CO2‐induced leaf structural and anatomical modifications, such as increased leaf mass per area, may have enhanced solar radiation absorption, thereby enabling greater canopy warming under high radiation conditions. Thus, eCO2 could likely cause a reduction in leaf transpiration in oaks, reducing its contribution to processes such as humidification of the lower atmosphere and precipitation in local and regional climates. Our findings highlight how high CO2 conditions may intensify thermal stress in temperate forests, influencing water and carbon cycles and potentially impacting forest resilience. Furthermore, Tcan will be essential for refining global Earth system models, which often use Tair as a proxy for Tcan, despite the latter's direct influence on carbon and hydrological cycles.

Identifying the primary soil parameters, weather variables and crop management practices that influence spatial variations in crop water use is essential for strategically defining optimal agricultural management practices. In this study, soil physico-chemical, weather and crop management variables were used through random forest (RF)-based modeling to evaluate the determinants of actual evapotranspiration (ETa) in winter wheat across Slovakia. ETa was estimated using Landsat imagery and the Python implementation of the Surface Energy Balance Algorithm for Land (PySEBAL), along with information from the Land Use/Cover Area frame Survey (LUCAS) over four cropping seasons. Overall, good agreements were found between PySEBAL-derived ETa and measured values, with RMSE and R2 values of 0.93 mm and 0.87, respectively. Seasonal ETa values ranged from 434.87 mm to 506.12 mm, with the highest and lowest average values found in the 2011/2012 and 2017/2018 cropping seasons, respectively. The RF model showed good performance in predicting seasonal ETa, with an RMSE of 21 mm/season for the training data and 32 mm/season for the validation data, and R2 values of 0.90 and 0.72, respectively. Our analysis indicated that ETa was primarily influenced by relative humidity, wind speed, solar radiation, altitude, and pH. The study further indicated that wheat production was unsuitable above 600 m elevation, while optimal crop water use occurred below 200 m. Addressing issues such as soil erosion and acidification could improve wheat crop water use efficiency across Slovakia. This modeling approach can serve as a basis to develop a crop water use forecasting system for sustainable wheat production in the region.

Potential evaporation (PE) from saturated bare surfaces is the basis for estimating actual evaporation (Es) in agricultural and related disciplines. Most models estimate PE using meteorological data. Thus, the dependence of soil temperature (T) on PE is often simplified in applications. To address this gap, we conducted an in situ lysimeter experiment in the Guanzhong Basin, China, continuously measuring PE, T, and soil heat flux (G) at high temporal resolution over three fully saturated sandy soils. Results show that annual PE over fine sand was 7.1% and 11.0% higher than that of coarse sand and gravel. The observed PE differences across textures can be quantitatively explained using the surface energy balance equation and a radiatively coupled Penman-Monteith equation, accounting for the dependence of T on net radiation (Rn) and G. In contrast, PE estimates diverged from observations when Rn and G were assumed to be independent of T. We further evaluated the influence of T and other influencing variables on PE. The random forest model identified that near-surface heat storage variations (∆S) contribute most significantly to PE estimation (relative importance = 0.37), followed by surface temperature (0.24) and sensible heat flux (0.23). These findings highlight the critical role of near-surface temperature in PE estimation.

Urban Heat Island Response to Projected Land-Use Change and Surface Energy Balance Modifications in Chongqing City, China

ABSTRACTIn this study, we applied the Community Earth System Model version 1 (CESM1) to investigate the impacts and physical and dynamic mechanisms of Anthropogenic Heat Release (AHR) due to global energy consumption on the Arctic climate in boreal summer from 1992 to 2013. AHR increases the air temperature in eastern Siberia and the Eastern European Plain obviously. AHR increases the air temperature significantly in eastern Siberia (60° N–70° N, 130° E–140° E) by 0.49 K on average, while it decreases the air temperature in the western Siberian plain regions in the Arctic. The results of our study demonstrate that AHR can affect lower‐troposphere stability in the Arctic, which further affects the low cloud fraction and the surface energy balance. AHR can affect the atmospheric circulation in the Arctic, bringing more water vapor and amplifying the greenhouse effect, which leads to further warming in the Arctic in the boreal summer. The Relative Humidity (RH) in the Arctic is increased by an average of 0.12% due to AHR in the boreal summer. These thermal and dynamic effects of AHR lead to uneven warming in the Arctic in summer, indicating AHR acts as a non‐negligible factor for the climate in the Arctic.

Abstract Land surface water and energy balances are important for understanding the coupling between land and atmosphere in Earth’s climate system. This study employs principal component analysis (PCA) and a variation on Granger causality to investigate land–atmosphere (LA) interactions among soil water content (SWC), surface latent heat flux (LE), sensible heat flux (H), and net radiation (RAD) at flux observation sites across seasons. The time scales of variability for each surface variable are key: For daily data, H is a crucial variable in LA interactions across all seasons, while LE becomes important for LA interactions mainly during warm seasons. SWC, despite its direct link to the surface water budget, appears less influential than energy at daily time scales, as its variability is mainly at longer time scales. Effects of RAD vary seasonally, being more significant in energy-limited regimes during spring and summer. The familiar SWC:LE correlation metric is expanded into a two-dimensional LA coupling matrix by including SWC:H relationships. This matrix facilitates fine classification of LA feedback providing a clearer understanding of water- and energy-limited regimes. Spatial analysis of observation sites shows significant LA interactions mainly in midlatitudes, influenced by solar radiation. The global distribution of LA feedback regimes underlines the complexity of defining such regimes, which vary according to geographic location, local climate, and land/vegetation types. Meanwhile, climate models and reanalyses fail to capture many observed aspects of LA interactions. Such insights are vital for enhancing the predictability of climate models and comprehending the intricate interplay between different surface conditions in LA interactions.

Evolution of natural ventilation potential under urbanization: A method based on Monin-Obukhov similarity theory and surface energy balance model

Observational evidence highlights the spatial divergence of vegetation changes in altering land surface energy balance over the Three-North region in China in summer

Comparison of surface energy balance and melt characteristics between debris-covered and debris-free zones on Qingbingtan Glacier No. 72, Mt. Tomor of Tien Shan

Abstract Due to the harsh environment of the inland plateau in East Antarctica and the associated scarcity of in situ meteorological measurements, its climatological features and surface energy balance (SEB) remain poorly understood. Using hourly meteorological data measured at Dome Argus (Dome A) and nearby Kunlun stations during a 3‐year period (2018–2020), we present the characteristics of the SEB components along with the frequency and intensity of the near‐surface temperature inversion. Due to the strong radiative imbalance at the surface, a quasi‐continuous temperature inversion persisted throughout the observational period (frequency 96%), with an average temperature gradient exceeding 1°C/m between the surface and 4 m height. The combination of relatively strong near‐surface winds and significant vertical temperature gradients resulted in monthly average surface turbulent sensible heat gains of up to in June, largely compensating for the concurrent net surface radiation loss. In contrast, the monthly average surface turbulent latent heat gains reached only due to the minimal atmospheric‐surface moisture gradients caused by the extremely low near‐surface air temperatures. Persistent surface‐based temperature inversions typically emerge under conditions of strong radiative cooling, characterized by reduced variability in surface temperature and subsurface heat fluxes, enhanced turbulent mixing and the sustained moisture. This represents the first comprehensive attempt to quantify near‐surface atmospheric heat exchange processes in the Dome A area, shedding light on interactions between the snow surface and near‐surface atmosphere at the East Antarctic inland plateau.

Abstract With the growth of the economy and population, along with the development of urbanization in southwest China (SWC), the impacts of anthropogenic heat release (AHR) from energy consumption on the climate in this region have gradually increased. This study uses the high‐resolution variable‐resolution Community Earth System Model Version 2 (VR‐CESM2) to simulate the impacts of AHR on the summer climate in SWC from 1995 to 2014 while also exploring the possible climate feedback mechanisms considering the complex terrain of SWC. The results indicate that AHR significantly enhanced southeastward moisture transport and weakened southwestward moisture transport in SWC. This shift results in increased vertical upward motion over the western Sichuan Basin and the western and southeastern parts of the Yunnan‐Guizhou Plateau, leading to increased precipitation with a regional average increase of 0.1 mm per day. AHR contributes to wetter summers in SWC and increased cloud cover, which further affects the surface energy balance. In the Sichuan Basin, AHR significantly raised summer temperatures, with a regional average increase of 0.04°C; in some areas, temperatures have risen by as much as 0.4°C. Compared to previous findings obtained from coarse‐resolution models, the high‐resolution VR‐CESM model provided a more accurate simulation of the climatic effects of AHR, as it better accommodates the unique terrain of SWC. In summary, this study uses the high‐resolution VR‐CESM2 to explore the impacting mechanisms of AHR on the climate in SWC, which is crucial for understanding climate change in this region.

Abstract Clouds play an important role in the Southern Ocean and Antarctic surface energy balance via their radiative effects and in surface mass balance via precipitation formation. Here, we use measurements at Escudero Station (62.2°S, 58.97°W) on King George Island, north of the Antarctic Peninsula, to characterize clouds and their effects on the surface incoming radiation between 2017 and 2023. These measurements are unique providing 7 years of simultaneous cloud and radiation measurements, including year‐round observations. Cloud measurements using a mini micropulse lidar showed that clouds are present 96% of the time with persistent low‐level supercooled liquid‐containing clouds: 86% of the lowest cloud bases are within the first 1 km. Liquid was present about 80% of the time, and most liquid was supercooled: cloud‐base temperatures were below 0°C for 82% of atmospheric columns classified as liquid‐containing. Combining pyranometer and pyrgeometer measurements with clear‐sky radiative transfer modeling, we find that the downward cloud radiative forcing is negative during October–March and positive during April–September. For clouds with base temperatures below 260 K, downward longwave cloud forcing is found to be lower for ice‐only clouds than for liquid‐containing clouds; however, at warmer temperatures, both ice‐only and liquid‐containing clouds exhibited similar radiative forcing. During strong atmospheric river (AR) events, when long corridors of moisture bring heat and precipitation, surface temperatures are found to be positively correlated with downward shortwave (DSW) cloud forcing in summer, indicating that weaker DSW cloud forcing is linked to higher summertime surface temperatures.

Westerly winds impact glacier energy balance and sublimation at August-one glacier in northern Tibetan Plateau

Longwave radiation (LWR) is a critical factor in surface energy balance and greenhouse effect studies, and its accurate measurement is essential for understanding climate change. However, existing remote sensing-based LWR products still have room for improvement in terms of spatiotemporal coverage, resolution, and accuracy. To address this issue, we developed the LWR Component of the global Long-term Earth System spatiotemporally Seamless Radiation budget dataset (LessRad). LessRad provides high-resolution (0.05°, hourly) LWR components including longwave downward radiation (LWDR), longwave upward radiation (LWUR), and longwave net radiation (LWNR). It extends the temporal coverage to 41 years (1982-2022) and outperforms existing comparable products. For LWDR and LWUR, rigorous validation against 565 ground-based observation sites demonstrates high accuracy, with correlation coefficients (R) of 0.94 and 0.97, biases of -4.39 W/m2 and -0.14 W/m2, and root mean square errors (RMSE) of 24.74 W/m2 and 20.42 W/m2, respectively. The high quality and extensive coverage make the LessRad LWR dataset an invaluable resource for fine-scale analysis of global surface radiation dynamics.