Search Results (3,242)

The Solar Magnetic Field Telescope (SMFT) at Huairou Solar Observing Station (HSOS) has conducted continuous observations of solar vector magnetic fields for nearly four decades, and while the primary optical system remains unchanged, critical components—including filters, polarizers, and detectors—have undergone multiple upgrades and replacements. Maintaining data consistency is essential for reliable long-term studies of magnetic field evolution and solar activity, as well as current helicity. In this study, we systematically analyze background bias and noise levels in SMFT observations from 1988 to 2019. Our dataset comprises 12,281 vector magnetograms of 1484 active regions. To quantify background bias, we computed mean values of Stokes $Q/I$, $U/I$ and $V/I$ over each entire magnetogram. The background bias of Stokes $V/I$ is small for the whole dataset. The background biases of Stokes $Q/I$ and $U/I$ fluctuate around zero during 1988–2000. From 2001 to 2011, however, the fluctuations in the background bias of both $Q/I$ and $U/I$ become significantly larger, exhibiting mixed positive and negative values. Between 2012 and 2019, the background biases shift to predominantly positive values for both Stokes $Q/I$ and $U/I$ parameters. To address this issue, we propose a potential method for removing the background bias and further discuss its impact on the estimation of current helicity. For each magnetogram, we quantify measurement noise by calculating the standard deviation ($\sigma$) of the longitudinal ($B_{\mathrm{l}}$) and transverse ($B_{\mathrm{t}}$) magnetic field components within a quiet-Sun region. The noise levels for $B_l$ and $B_{\mathrm{t}}$ components were approximately 15 Gauss (G) and 87 G, respectively, during 1988–2011. Since 2012, these values decreased significantly to ∼6 G for $B_{\mathrm{l}}$ and ∼55 G for $B_{\mathrm{t}}$, likely due to the installation of a new filter. Full article

Clouds cover nearly two-thirds of Earth’s surface, making reliable cloud mask data essential for remote sensing applications and atmospheric research. This study develops a TrAdaBoost transfer learning framework that integrates active CALIOP and passive MODIS observations to enable unified, high-accuracy cloud detection across FY-4A/AGRI, FY-4B/AGRI, and Himawari-8/9 AHI sensors. The proposed TrAdaBoost Cloud Mask algorithm (TCM) achieves robust performance in dual validations with CALIPSO VFM and MOD35/MYD35, attaining a hit rate (HR) above 0.85 and a cloudy probability of detection (${POD}_{cld})$ exceeding 0.89. Relative to official products, TCM consistently delivers higher accuracy, with the most pronounced gains on FY-4A/AGRI. SHAP interpretability analysis highlights that 0.47 μm albedo, 10.8/10.4 μm and 12.0/12.4 μm brightness temperatures and geometric factors such as solar zenith angles (SZA) and satellite zenith angles (VZA) are key contributors influencing cloud detection. Multidimensional consistency assessments further indicate strong inter-sensor agreement under diverse SZA and land cover conditions, underscoring the stability and generalizability of TCM. These results provide a robust foundation for the advancement of multi-source satellite cloud mask algorithms and the development of cloud data products integrated. Full article

This study aims to create environmentally comfortable building designs in hot and dry steppe climates using more effective approaches. The purpose of this study is to assess the relationship between mean radiant temperature (MRT) and indoor air temperature (Tia), taking into account the orientation of buildings, for better building thermal performance. For this purpose, residential buildings with different orientations were selected in the study region ‘Garmian—northern Iraq’, and their thermal performance was evaluated. The results show how MRT contributes to the buildings’ thermal comfort. The outcomes of this research provide innovative empirical quantification of the correlation of MRT-Tia, as the regression coefficient (β) represents the rate of change in Tia per unit increase in MRT and ranges by orientation in the study area. The findings demonstrate that north-facing buildings buffer radiant heat gain (β~0.52), resulting in a 0.5 °C increase in indoor air temperature for each 1 °C rise in MRT. Moreover, west orientation delivers promising winter passive heating (MRT up to 22 °C and indoor air temperature up to 22.8 °C with a β of ~0.82). However, south-facing buildings perform poorly in the winter, with low MRT and a weak β (~0.44), contrasting with passive solar design strategies that favor south-facing buildings in the northern hemisphere. Furthermore, in the summer, the MRT is always higher than Tia, while it is lower in winter, indicating poor envelope and fenestration thermal insulation properties, which lead to excessive energy usage to maintain thermal comfort. Finally, the study suggests the novel quantified MRT-Tia mathematical correlation responds to the orientations for such climates, offering both diagnostic and predictive tools for thermal comfort performance optimization. This study is the first to empirically quantify orientation-specific MRT–Tia relationships in BSh climates, offering a novel diagnostic tool for sustainable building design. This study involved field observations in 36 residential row houses across four orientations. Key environmental and personal variables measured included mean radiant temperature (MRT), indoor air temperature (Tia), air velocity, relative humidity, metabolic rate, and clothing insulation. Full article

Atmospheric formaldehyde (HCHO) is a major component of oxygenated volatile organic compounds (OVOCs) and plays an important role in O₃ formation and atmospheric oxidation capacity. In this study, seasonal observations of gaseous pollutants (HCHO, O₃, peroxyacetyl nitrate (PAN), CO, NOx, and VOCs) and ambient conditions (J_HCHO, J_NO2, solar radiation, temperature, relative humidity, wind speed, and wind direction) were conducted in a coastal city in southeast China. The average HCHO concentrations were 2.54 ppbv, 3.38 ppbv, 2.53 ppbv, and 1.98 ppbv in spring, summer, autumn, and winter, respectively. Diurnal variations were high in the daytime and low in the nighttime, and the peak times varied in different seasons. The correlation between HCHO and O₃ was not significant in spring and winter, which is likely related to the effects of photochemical reactions and diffusion conditions. The contributions of background (23.0%), primary (47.6%), and secondary (29.4%) sources to HCHO were quantified using multiple linear regression (MLR) models, revealing that secondary formation was the most significant contributor in summer, whereas primary emissions were predominant in spring. These findings help to improve the understanding of the influence of atmospheric formaldehyde on photochemical pollution control in coastal cities. Full article

Galileo and the telescope revolutionized the concept of the Sun. The discovery of its rotation was possible due to the continuous observation of the sunspots. The faculae and the maculae with umbra and penumbra became accessible daily to new instruments, leaving the perfectly lucid disk to the realm of symbolism. Was this new view possible before the telescope? Technically, pinhole cameras can show the largest sunspots, as well as the naked eye under very particular conditions. However such observations were too scattered to produce any change in the established understanding of the Sun. Synoptic observations of the largest sunspots of the XXV solar cycle made with the naked eye, pinhole camera, and a telescope in camera obscura are presented and compared with the historical ones. Sunspots could have been discovered in Florence as early as 1475 with the pinhole meridian line of S. Maria del Fiore: the Spörer minimum (1460–1550) of the solar activity prevented it. Indications of white light flares and prominence observations appear in a drawing dated back to 1635, well before the first H-alpha inspections in the 19th century. Full article

In order to meet the demand for enhanced heat transfer capabilities in practical application areas such as high heat flux density and high stability, the film evaporation heat dissipation method has been widely applied in fields such as microelectronic device cooling, heat pipe technology, solar steam generation, and seawater desalination. In the current study, film evaporation experiments are conducted on droplets of propylene glycol and ethanol using a film evaporation observation platform. The morphological changes and temperature of the droplets are investigated by varying the overheating degree, material, roughness, and wettability of the heating plate. The results indicate that the droplet thickness undergoes three stages of change with variations in overheating degree, and the droplet thickness decreases overall with increasing roughness. The thickness of ethanol droplets is higher than that of propylene glycol droplets in the low overheating degree range but lower in the high overheating degree range. Ethanol droplets are more sensitive to overheating degree than propylene glycol droplets. As the droplets enter the film evaporation state, the surface temperature of the droplets gradually approaches the wall temperature and the rate of change slows down. This trend shows a certain similarity to the change in droplet thickness. Increasing the surface roughness slightly raises the overall temperature, while altering the wettability has minimal impact on the temperature variation. Full article

This study investigates the origin and amplification of magnetic fields in planets and galaxies, emphasizing the foundational role of a seed magnetic field (SMF) in enabling dynamo processes. We propose a universal mechanism whereby an SMF arises naturally in systems where an orbiting body rotates non-synchronously with respect to its central mass. Based on this premise, we derive a general equation for the SMF applicable to both planetary and galactic scales. Incorporating parameters such as orbital distance, rotational velocity, and core radius, we then introduce a dimensionless factor to characterize the amplification of this seed field via dynamo processes. By comparing model predictions with magnetic field data from the solar system and the Milky Way, we find that the observed magnetic fields can be interpreted as the product of a universal gravitationally induced SMF and a body-specific amplification factor. Our results offer a novel perspective on the generation of magnetic fields in a wide range of astrophysical contexts and suggest new directions for theoretical investigation, including the environments surrounding black holes. Full article

We present a freeze-out approach for describing the formation of heavy elements in expanding nuclear matter. Applying concepts used in modeling heavy-ion collisions or ternary fission, we determine the abundances of heavy elements taking into account in-medium effects such as Pauli blocking and the Mott effect, which describes the dissolution of nuclei at high densities of nuclear matter. With this approach, we search for a universal initial distribution in a quasi-equilibrium state from which the coarse-grained pattern of the solar abundances of heavy elements freezes out and evolves by radioactive decay of the excited states. The universal initial state is characterized by the Lagrange parameters, which are related to temperature and chemical potentials of neutrons and protons. We show that such a state exists and determine a temperature of 5.266 MeV, a neutron chemical potential of 940.317 MeV and a proton chemical potential of 845.069 MeV, with a baryon number density of 0.013 fm⁻³ and a proton fraction of $0.13$. Heavy neutron-rich nuclei such as the hypothetical double-magic nucleus ³⁵⁸Sn appear in the initial distribution and contribute to the observed abundances after fission. We discuss astrophysical scenarios for the realization of this universal initial distribution for heavy-element nucleosynthesis, including supernova explosions, neutron star mergers and the inhomogeneous Big Bang. The latter scenario may be of interest in the light of early massive objects observed with the James Webb Space Telescope and opens new perspectives on the universality of the observed r-process patterns and the lack of observations of population III stars. Full article

The primary objective of this study is to assess the techno-economic feasibility of an innovative solar energy generation system with a rainwater collection feature to generate electrical energy and meet irrigation needs in agriculture. The proposed system is designed for an agricultural area (Gonyeli, North Cyprus) with high solar potential and limited rainfall. In the present study, global rainfall datasets are utilized to assess the potential of rainwater harvesting at the selected site. Due to the lack of the measured rainfall data at the selected site, the accuracy of rainfall of nine global reanalysis and analysis datasets (CHIRPS, CFSR, ERA5-LAND, ERA5, ERA5-AG, MERRA2, NOAA CPC CMORPH, NOAA CPC DAILY GLOBAL, and TerraClimate) are evaluated by using data from ground-based observations collected from the Meteorological Department located in Lefkoşa, Northern Cyprus from 1981 to 2023. The results demonstrate that ERA5 outperformed the other datasets, yielding a high R-squared value along with a low mean absolute error (MAE) and root mean square error (RMSE). Based on the best dataset, the potential of the rainwater harvesting system is estimated by analyzing the monthly and seasonal rainfall patterns utilizing 65 different probability distribution functions for the first time. Three goodness-of-fit tests are utilized to identify the best-fit probability distribution. The results show that the Johnson and Wakeby SB distributions outperform the other models in terms of fitting accuracy. Additionally, the results indicate that the rainwater harvesting system could supply between 31% and 38% of the building’s annual irrigation water demand (204 m³/year) based on average daily rainfall and between 285% and 346% based on maximum daily rainfall. Accordingly, the system might be able to collect a lot more water than is needed for irrigation, possibly producing an excess that could be stored for non-potable uses during periods of heavy rainfall. Furthermore, the techno-economic feasibility of the proposed system is evaluated using RETScreen software (version 9.1, 2023). The results show that household energy needs can be met by the proposed photovoltaic system, and the excess energy is transferred to the grid. Furthermore, the cash flow indicates that the investor can expect a return on investment from the proposed PV system within 2.4 years. Consequently, the findings demonstrate the significance of this system for promoting resource sustainability and climate change adaptation. Besides, the developed system can also help reduce environmental impact and enhance resilience in areas that rely on water and electricity. Full article

This study investigates the climatic dynamics of Odesa, Ukraine, by integrating over 200 years of archival meteorological records with recent observations from the Davis Vantage Pro2 weather station and advanced machine learning techniques. The results reveal a distinct warming trend since 1985, with average annual temperatures projected by a CNN–LSTM model to rise by more than 6–7 °C above the mid-20th-century baseline by 2029, indicating an exceptionally rapid regional climatic shift. Spatial analysis of the July 2024 heatwave demonstrated pronounced thermal gradients, with the strongest overheating observed inland and the moderating influence of the Black Sea reducing temperature extremes in coastal areas. Precipitation analysis (1985–2024) showed an overall statistically insignificant increase; however, the summer months exhibited drying tendencies, a trend reinforced by model forecasts. Solar radiation dynamics (2012–2024) highlighted significant local variability shaped primarily by atmospheric conditions rather than solar activity, with notable monthly increases in October, November, and February. The novelty of this research lies in combining long-term datasets with deep learning methods to produce localized climate scenarios for Odesa, offering new insights into the city’s transition toward extreme warming, shifting precipitation patterns, and evolving solar energy potential. The findings have direct implications for environmental modeling, energy efficiency, and the development of climate change adaptation strategies in urbanized coastal regions. Full article

Using the results of numerical simulations and solar observations, this study shows that the transition from deterministic chaos to hard turbulence in the magnetic field generated by the emerging small-scale, near-surface (within the Sun’s outer 5–10% convection zone) solar MHD dynamos occurs through a randomization process. This randomization process has been described using the concept of distributed chaos, and the main parameter of distributed chaos $\beta$ has been employed to quantify the degree of randomization (the wavenumber spectrum characterising distributed chaos has a stretched exponential form $E\left(k\right)\propto exp-{(k/k_{\beta })}^{\beta }$). The dissipative (Loitsianskii and Birkhoff–Saffman integrals) and ideal (magnetic helicity) magnetohydrodynamic invariants govern the randomization process and determine the degree of randomization $0<\beta \le 1$ at various stages of the emerging MHD dynamos, directly or through Kolmogorov–Iroshnikov phenomenology (the magnetoinertial range of scales as a precursor of hard turbulence). Despite the considerable differences in the scales and physical parameters, the results of numerical simulations are in quantitative agreement with solar observations (magnetograms) within this framework. The Hall magnetohydrodynamic dynamo is also briefly discussed in this context. Full article

The subtropical transitional zone of China exhibits highly complex climatic conditions and diverse forest ecosystems, making it a critical region for understanding vegetation–water interactions. This study employed the Thermal Dissipation Probe (TDP) method to monitor sap flow in three typical forest types—evergreen broad-leaved forest, bamboo forest (Dendrocalamus latiflorus), and Chinese fir (Cunninghamia lanceolata)—in a subtropical transitional watershed in southern China. The aims were to quantify seasonal and annual variations in sap flow, to examine the effects of environmental drivers, and to analyze the hysteretic responses between sap flow and the drivers. The main findings were as follows: (1) bamboo forests exhibited significantly higher sap flow density than evergreen broad-leaved and fir forests at both annual and seasonal scales, though the overall transpiration of bamboo forests was lower than the others due to its limited sapwood area; (2) sap flow was positively correlated with potential evapotranspiration, solar radiation (Ra), vapor pressure deficit (VPD), air temperature, and soil temperature, while it was negatively correlated with relative humidity, atmospheric pressure, soil moisture, and precipitation; (3) Ra and VPD were identified as the dominant drivers of sap flow variations, with nonlinear increases that leveled off once thresholds were reached; (4) clear hysteresis patterns were observed, with sap flow peaks consistently lagging behind Ra but occurring earlier than VPD. These results advance our understanding of forest water-use strategies in the subtropical transitional zone and provide a scientific basis for improving water resource management and ecosystem sustainability in this region. Full article

Perovskite solar cells (PSCs) rarely report, on a single-device platform, concurrent gains in optoelectronic efficiency and buried-interface mechanical robustness—two prerequisites for flexible and roll-to-roll (R2R) integration. We engineered a nanoplate-structured fluorine-doped tin oxide (NP-FTO) front electrode that couples light management with three-dimensional interfacial anchoring, and we quantified both photovoltaic (PV) and nanomechanical metrics on the same device stack. Relative to planar FTO, the NP-FTO PSCs achieved PCE of up to 25.65%, with simultaneous improvements in Voc (to 1.196 V), Jsc (up to 26.35 mA cm⁻²), and FF (to 82.65%). Nanoindentation revealed a ~28% increase in reduced modulus and >70% higher hardness, accompanied by a ~32% reduction in maximum indentation depth, indicating enhanced load-bearing capacity consistent with the observed FF gains. The low-temperature, solution-compatible NP-FTO interface is amenable to R2R manufacturing and flexible substrates, offering a unified route to bridge high PCE with reinforced interfacial mechanics toward integration-ready perovskite modules. 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

Transformerless inverters have received significant attention in solar photovoltaic (PV) applications. The absence of low-frequency transformers contributes to improved efficiency and reduced size compared to other topologies; however, there are concerns about leakage currents. The common ground (CG) connection in PV inverters is an attractive solution to this issue, as it generates a constant common-mode voltage and theoretically eliminates the leakage current. In this context, multilevel CG inverters can eliminate the leakage current while achieving high-quality output voltages. Nonetheless, achieving simultaneous control of the grid current and inner capacitor voltages can be challenging. Furthermore, controlling the capacitor voltages in multilevel inverters requires feedback from measurement sensors, which can increase the cost and may affect the overall reliability. To address these issues, this paper proposes a model predictive controller (MPC) for a CG multilevel inverter with a reduced number of sensors. While conventional MPC uses a classical multi-objective technique with a single cost function, the proposed method avoids the use of weighting factors in the cost function. Additionally, a sliding-mode observer is developed to estimate the capacitor voltages, and an incremental conductance-based maximum power point tracking (MPPT) algorithm is used to generate the current reference. Simulation and experimental results confirm the effectiveness of the proposed observer and MPC strategy. Full article