Search Results (1,493)

Radiometric consistency across satellite platforms is fundamental to producing high-quality Climate Data Records (CDRs). Because different cross-calibration methods have distinct advantages and limitations, comparative evaluation is necessary to ensure record accuracy. This study presents a comparative assessment of two widely applied calibration approaches—Simultaneous Nadir Overpass (SNO) and Double Difference (DD)—for the thermal infrared (TIR) bands of FY-3D MERSI. MODIS/Aqua serves as the reference sensor, while radiative transfer simulations driven by ERA5 inputs are generated with the Advanced Radiative Transfer Modeling System (ARMS) to support the analysis. The results show that SNO performs effectively when matchup samples are sufficiently large and globally representative but is less applicable under sparse temporal sampling or orbital drift. In contrast, the DD method consistently achieves higher calibration accuracy for MERSI Bands 24 and 25 under clear-sky conditions. It reduces mean biases from ~−0.5 K to within ±0.1 K and lowers RMSE from ~0.6 K to 0.3–0.4 K during 2021–2022. Under cloudy conditions, DD tends to overcorrect because coefficients derived from clear-sky simulations are not directly transferable to cloud-covered scenes, whereas SNO remains more stable though less precise. Overall, the results suggest that the two methods exhibit complementary strengths, with DD being preferable for high-accuracy calibration in clear-sky scenarios and SNO offering greater stability across variable atmospheric conditions. Future work will validate both methods under varied surface and atmospheric conditions and extend their use to additional sensors and spectral bands. Full article

Personal comfort systems (PCSs), which provide targeted heating or cooling to specific body parts, have emerged as a promising solution to enhance occupant comfort while reducing energy use in buildings. Among the many factors influencing PCS performance, heat transfer mechanisms (HTMs) play a pivotal role. However, a critical gap remains in the literature regarding the identification of optimal HTMs for achieving both thermal comfort and energy efficiency in PCSs. To address this gap, our study investigates the impact of conduction, convection, and radiation in PCSs on thermal comfort enhancement and energy performance under both heating and cooling modes. A meta-analysis was conducted, extracting data from 64 previous studies to evaluate the effects of HTMs of PCSs on thermal sensation vote (TSV), overall comfort (OC) and corrective energy power (CEP). Results indicate that PCSs typically improve users’ thermal sensation and comfort by about one scale unit in both heating and cooling modes. Radiative HTM is the most effective individual method, while combined conductive and convective HTMs perform best overall. Most PCSs operate efficiently, consuming less than 200 W/°C, with conduction in heating and convection in cooling being recommended for optimal comfort and energy efficiency. These findings suggest that selecting optimal HTMs for PCSs is crucial for achieving maximum comfort performance and energy savings. Data on combined HTMs of PCSs remain limited, underscoring the need for further research in this area. Future research should prioritize optimizing HTMs, especially radiative and combined methods, to maximize comfort and energy savings in PCS design. Full article

The three-dimensional (3D) structure of clouds is a key factor in atmospheric processes, profoundly influencing solar radiation transfer, weather patterns, and climate dynamics. However, accurately representing this complex structure in radiative transfer models remains a significant challenge. As part of the Deep 3D Scattering of Solar Radiation in the Atmosphere due to Clouds (D3D) project, we conducted a comprehensive study on the role of all-sky imagers (ASIs) in reconstructing observational 3D cloud fields and integrating them into advanced 3D cloud modeling. Since November 2022, a network of four ASIs has been operating across the broader Patras region in Greece, continuously capturing atmospheric measurements over an area of approximately 50 km². Using simultaneously captured images from the ASIs within the network, a 3D cloud reconstruction was performed utilizing advanced image processing techniques, with a primary focus on cumulus cloud scenarios. The Structure from Motion (SfM) technique was employed to reconstruct the 3D structural characteristics of clouds from two-dimensional images. The resulting 3D cloud fields were then integrated into the MYSTIC three-dimensional radiative transfer model to simulate and reconstruct solar irradiance fields. Full article

Cold-air pooling (CAP) and frost risk represent significant climate-related hazards in karstic and agricultural environments, where local topography and surface cover strongly modulate microclimatic conditions. This study focuses on the Mohos sinkhole, Hungary’s cold pole, situated on the Bükk Plateau, to investigate the formation, structure, and persistence of CAPs in a Central European karst depression. High-resolution terrain-based modeling was conducted using UAV-derived digital surface models combined with multiple GIS tools (Sky-View Factor, Wind Exposition Index, Cold Air Flow, and Diurnal Anisotropic Heat). These models were validated and enriched by multi-level temperature measurements and thermal imaging under various synoptic conditions. Results reveal that temperature inversions frequently form during clear, calm nights, leading to extreme near-surface cold accumulation within the sinkhole. Inversions may persist into the day due to topographic shading and density stratification. Vegetation and basin geometry influence radiative and turbulent fluxes, shaping the spatial extent and intensity of cold-air layers. The CAP is interpreted as part of a broader interconnected multi-sinkhole system. This integrated approach offers a transferable, cost-effective framework for terrain-driven frost hazard assessment, with direct relevance to precision agriculture, mesoscale model refinement, and site-specific climate adaptation in mountainous or frost-sensitive regions. Full article

This study evaluates the forecast performance of four radiation parameterization schemes—the Rapid Radiative Transfer Model for General Circulation Models (RRTMG), its improved version RRTMG-K, the infrequently applied variant, RRTMG-K_60x, and the neural network emulator, RRTMG-K_NN, within a high-resolution numerical weather prediction (NWP) model. The evaluation uses satellite-derived observations of Outgoing Longwave Radiation (OLR) and Outgoing Shortwave Radiation (OSR) from the Clouds and the Earth’s Radiant Energy System (CERES) over the Korean Peninsula during 2020, including an extreme case study of Typhoon Haishen. Results show that RRTMG-K reduces RMSEs by 4.8% for OLR and 17.5% for OSR relative to RRTMG, primarily due to substantial bias reduction (42.3% for OLR, 60.4% for OSR). The RRTMG-K_NN scheme achieves approximately 60-fold computational speedup while maintaining similar or slightly better accuracy than RRTMG-K; specifically, it reduces OLR errors by 1.2% and OSR errors by 1.6% compared to the infrequently applied RRTMG-K_60x. In contrast, the infrequent application of RRTMG-K (RRTMG-K_60x) slightly increases errors, underscoring the trade-off between computational efficiency and accuracy. These findings demonstrate the value of integrating advanced satellite flux observations and machine learning techniques into the evaluation and optimization of radiation schemes, providing a robust framework for improving cloud–radiation interaction representation in NWP models. Full article

In recent years, unmanned aerial vehicle (UAV) quantitative remote sensing technology has demonstrated significant advantages in fields such as agricultural monitoring and ecological environment assessment. However, achieving the goal of quantification still faces major challenges due to the angle effect. This effect, caused by the bidirectional reflectance distribution function (BRDF) of surface targets, leads to significant spectral response variations at different observation angles, thereby affecting the inversion accuracy of physicochemical parameters, internal components, and three-dimensional structures of ground objects. This study systematically reviewed 48 relevant publications from 2000 to the present, retrieved from the Web of Science Core Collection through keyword combinations and screening criteria. The analysis revealed a significant increase in both the number of publications and citation frequency after 2017, with research spanning multiple disciplines such as remote sensing, agriculture, and environmental science. The paper comprehensively summarizes research progress on the angle effect in UAV quantitative remote sensing. Firstly, its underlying causes based on BRDF mechanisms and radiative transfer theory are explained. Secondly, multi-angle data acquisition techniques, processing methods, and their applications across various research fields are analyzed, considering the characteristics of UAV platforms and sensors. Finally, in view of the current challenges, such as insufficient fusion of multi-source data and poor model adaptability, it is proposed that in the future, methods such as deep learning algorithms and multi-platform collaborative observation need to be combined to promote theoretical innovation and engineering application in the research of the angle effect in UAV quantitative remote sensing. This paper provides a theoretical reference for improving the inversion accuracy of surface parameters and the development of UAV remote sensing technology. Full article

Sea surface salinity (SSS) observations play a crucial role in the study of ocean circulation, climate variability, and marine ecosystems. However, current satellite SSS products suffer from systematic biases due to factors such as radio frequency interference (RFI) and land contamination, resulting in fundamental limitations to their application for SSS monitoring. To address this issue, we propose a physics-informed neural network (PINN) approach that directly integrates radiative transfer physical processes into the neural network architecture for SMAP L2 SSS bias correction. This method ensures oceanographically consistent corrections by embedding physical constraints into the forward propagation model. The results demonstrate that PINN achieved a root mean square error (RMSE) of 0.249 PSU, representing a 5.3% to 8.5% relative performance improvement compared to conventional methods—GBRT, ANN, and XGBoost. Further temporal stability analysis reveals that PINN exhibits significantly reduced RMSE variations over multi-year periods, demonstrating exceptional long-term correction stability. Meanwhile, this method achieves more uniform bias improvement in contaminated nearshore regions, showing distinct advantages over the inconsistent correction patterns of conventional methods. This study establishes a physics-constrained machine learning framework for satellite SSS data correction by integrating oceanographic domain knowledge, providing a novel technical pathway for reliable enhancement of Earth observation data. Full article

Wetland ecosystems, particularly marsh wetlands, are vital for carbon cycling, yet the accurate estimation of the fraction of absorbed photosynthetically active radiation (FPAR) in these environments is challenging due to their complex structure and limited field data. This study employs the large-scale remote sensing data and image simulation framework (LESS), a 3D radiative transfer model, to simulate FPAR and vegetation indices (VIs) under controlled conditions, including variations in vegetation types, soil types, chlorophyll content, solar and observation angles, and plant density. By simulating 8064 wetland scenes, we overcame the limitations of field measurements and conducted comprehensive quantitative analyses of the relationship between the FPAR and VI (which is essential for remote sensing-based FPAR estimation). Nine VIs (NDVI, GNDVI, SAVI, RVI, EVI, MTCI, DVI, kNDVI, RDVI) effectively characterized FPAR, with the following saturation thresholds quantified: inflection points (FPAR.inf, where saturation begins) ranged from 0.423 to 0.762 (mean = 0.594) and critical saturation points (FPAR.sat, where saturation is complete) from 0.654 to 0.889 (mean = 0.817). The Enhanced Vegetation Index (EVI) and Soil-Adjusted Vegetation Index (SAVI) showed the highest robustness against saturation and environmental variability for FPAR estimation in reed (Phragmites australis) marshes. These findings provide essential support for FPAR estimation in marsh wetlands and contribute to quantitative studies of wetland carbon cycling. Full article

To enhance the field calibration capability of ground-based lunar observation instruments for long-term continuous monitoring and to optimize the stability and traceability of lunar observation data, this manuscript presents the development of a SI traceable Portable Self-calibrating Absolute Radiation Source (PSARS) based on an electrical substitute radiometer. A self-calibrating radiation transfer model has been established. The system features a “+” structure layout centered around an integrating sphere, which ensures uniformity of the light source while improving system integration. Preliminary performance testing results indicate that PSARS achieves excellent radiative planar uniformity and angular uniformity within the targeted area, both exceeding 99%. During the self-calibration cycle of PSARS, the detector demonstrates high measurement stability for the built-in light source. Ultimately, through comparative validation and uncertainty assessment, the self-calibration accuracy of spectral irradiance for PSARS in the 400–1000 nm wavelength range is better than 2%, meeting the demands for high-frequency, high-stability, and high-precision real-time on-site radiometric calibration under ground-based lunar observation field test conditions. This provides technical support for the construction of high-precision lunar models and the widespread application of lunar calibration technologies. Full article

Accurate thermal characterization of closed mesoporous metal gels is vital for high-temperature uses, yet microscale effects often ignored in macroscopic models significantly impact heat transfer. This study introduces a new predictive method based on an equivalent Voronoi model, accounting for the Knudsen effect and microscale electromagnetic interactions. Predicted thermal conductivity closely matched experimental results, with an average error of 5.35%. The results demonstrate that thermal conductivity decreases with porosity, increases with temperature, and varies with pore size, with a minimum of 17.47 W/(m·K) observed at ~1 μm. Variations in refractive index, extinction coefficient, and specific surface area exert negligible influence. Conductive heat transfer is suppressed under Knudsen-dominated conditions at small pore sizes. Electromagnetic analysis around the pore size corresponding to minimum conductivity reveals localized surface plasmon resonances and magnetic coupling at the gas–solid interface, which enhance radiative dissipation and further reduce thermal conductivity. Radiation dissipation efficiency increases with decreasing porosity and pore size. This model thus serves as a predictive tool for designing high-performance thermal insulation systems for elevated-temperature applications. Full article

The scalable fabrication of hydrogels with high toughness and low hysteresis is critically hindered by oxygen inhibition, which typically produces brittle, highly crosslinked (HC) networks. This study presents an oxygen-tolerant photoinduced electron transfer–reversible addition–fragmentation chain transfer (PET-RAFT) strategy for synthesizing highly entangled (HE) polyacrylamide hydrogels under open-vessel conditions. By optimizing the water-to-monomer ratio (W = 3.9) and introducing lithium chloride (LiCl) for spatial confinement, we achieved a fundamental shift in mechanical performance. The optimized HE hydrogel exhibited a fracture energy of 1.39 MJ/m³ and a fracture strain of ~900%, starkly contrasting the brittle failure of the HC control (W = 20, C = 10⁻²) at ~50% strain. This represents an order-of-magnitude improvement in deformability. Furthermore, the incorporation of 15 wt% LiCl amplified the HE hydrogel’s fracture energy to 2.17 MJ/m³ while maintaining its low hysteresis. This method enables the rapid, scalable production of robust, transparent thin films that exhibit dual passive cooling via radiative emission (>89% emissivity) and evaporation, rapid self-healing, and reliable strain sensing at temperatures as low as −20 °C. The synergy of entanglement design and confinement engineering establishes a versatile platform for manufacturing multifunctional hydrogels that vastly outperform their crosslink-dominated predecessors. Full article

Monitoring and accurately forecasting ultraviolet (UV) radiation is of great importance especially due to its adverse effects on human health. In this study, we develop a numerical model to estimate the UV surface solar radiation with the overarching goal of providing a fully automated UV forecasting tool in the region of Epirus, Greece, and especially at the city of Ioannina. The UV surface solar radiation (SSR) is estimated based on detailed radiative transfer (RT) calculations. To ensure their accuracy, we employ the well-established UVSPEC model included in the libRadtran RT routines. LibRadtran provides a variety of options to set up and modify an atmosphere with molecules, aerosol particles, water and ice clouds and a surface as the lower boundary. As a first step, we performed a sensitivity study of the surface solar UV radiation with respect to ozone, precipitable water, aerosol optical properties and surface albedo. Our calculations are performed initially under clear-sky conditions to eliminate the uncertainties induced by clouds. All our calculations are performed spectrally within the UV spectral range, for a specific date and time at Ioannina, Epirus. Full article

The current research on light transmission under rainfall conditions primarily focuses on monochromatic converging light sources, and the related conclusions cannot be directly applied to spherical continuous-spectrum light sources (SCLSs). Based on the Lorenz–Mie scattering method, this study calculated the optical parameters of Gamma-distributed rainfall across three rainfall types and four intensity levels. A numerical algorithm model for radiative transfer under rainfall conditions was established for SCLSs. The effects of rainfall type, rainfall intensity, and light wavelength on radiative transfer were analyzed. Key conclusions include the following: when rainfall intensity is below moderate, the type of rainfall can be disregarded. However, for heavy to torrential rain, distinct differences between stratiform and non-stratiform rainfall must be considered. The attenuation caused by rainfall intensity does not increase linearly. Specifically, attenuation during moderate rain is lower than that in light rain, while heavy and torrential rain exhibit greater attenuation than both light and moderate rain. Wavelength bands significantly influence radiative transfer. Efforts to optimize the attenuation of radiative energy by rainfall should focus on the primary energy bands where most energy is concentrated. These findings highlight the importance of considering rainfall classification, nonlinear attenuation mechanisms, and wavelength-specific characteristics when evaluating radiative transfer under varying rainfall conditions. Full article

V658 Car is the first known eclipsing binary system involving a classical Be star and an sdOB companion, offering a unique opportunity to study disk physics and binary interactions in unprecedented detail. From TESS data and multi-color observations from the comissão para a colaboração entre profissionais e amadores collaboration, we analyze the system’s color–magnitude diagram and compare it with radiative transfer models that include the Be star, its circumstellar disk, and the sdOB companion. While the stellar eclipses are well reproduced, two features observed in the multi-color photometry challenge the current modeling paradigm: the discrepancy between the observed reddening and the modeled blueing during the first attenuation phase and the complete lack of modeled attenuation around the second stellar eclipse. These issues highlight the need for more sophisticated modeling approaches to capture the complex interplay between disk opacity and binary dynamics. Full article

The article presents a mathematical description of the thermal phenomena occurring both inside and on the surfaces of a homogeneous plate subjected to an external heat flux on one side. Analytical formulae for thermal excitation, with a given duration and constant power, are derived, enabling the determination of temperature increases on both the heated and unheated surfaces of the plate under specific heat transfer conditions to the surroundings. Convective heat transfer, with individual heat transfer coefficients on both sides of the slab, is considered; however, radiative heat loss can also be included. The solution of the problem obtained using two methods is presented: the method of separation of variables (MSV) and the Laplace transform (LT). The advantages and disadvantages of both analytical formulae, as well as the impact of various factors on the accuracy of the solution, are discussed. Among others, the MSV solution works well for a sufficiently long time, whereas the LT solution is better for a sufficiently short time. The theoretical considerations are illustrated with diagrams for several configurations, each representing various heat transfer conditions on both sides of the plate. The presented solution can serve as a starting point for further analysis of more complex geometries or multilayered structures, e.g., in non-destructive testing using active thermography. The developed theoretical model is verified for a determination of the thermal diffusivity of a reference material. The model can be useful for analyzing the method’s sensitivity to various factors occurring during the measurement process, or the method can be adapted to a pulse of known duration and constant power, which is much easier to implement technically than a very short impulse (Dirac) with high energy. Full article