Search Results (81)

Freezing precipitation and the resultant ice glaze can have catastrophic impacts on urban infrastructure, the environment, forests, and various industries, including transportation, energy, and agriculture. In this study, we develop and evaluate regional algorithms for detecting freezing precipitations in the Far East, utilizing the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts, along with standard meteorological observations for 20 cold seasons (September–May) from 2004 to 2024. We propose modified diagnostic algorithms based on vertical atmospheric temperature and humidity profiles, as well as near-surface characteristics. Additionally, we apply a majority voting ensemble (MVE) technique to integrate outputs from multiple algorithms, thereby enhancing classification accuracy. Evaluation of detection skills shows significant improvements over the original method developed at the Finnish Meteorological Institute and the ERA5 precipitation-type product. The MVE-based method demonstrates optimal verification statistics. Furthermore, the modified algorithms validly reproduce the spatially averaged inter-annual variability of freezing precipitation activity in both continental (mean correlation of 0.93) and island (correlation of 0.54) regions. Overall, our findings offer a more effective and valuable tool for operational activities and climatological assessments in the Far East. Full article

Stones are traditionally used in construction and architectural applications as building elements due to their aesthetic and technical/structural performance. Like other environmental factors (rain, humidity, moisture, salt presence, biological activity, etc.), heating–cooling and freeze–thaw cycles significantly threaten the longevity of stone materials. Hence, considering the socio-economic and cultural value of stones, preventive actions such as hydrophobic coatings are applied to prevent or mitigate damage. The scope of this study is the performance assessment of limestones with different characteristics and the efficiency of various commercial silane/siloxane-based hydrophobic coatings when exposed to thermal variation and freeze–thaw. For that purpose, the standards EN 14066:2013 (determination of resistance to aging by thermal shock) and EN 12371:2010 (determination of frost resistance) were followed. Open porosity and static contact angles were estimated to assess the stone durability and water protection capabilities of the hydrophobics. Additionally, sound speed propagation velocity, quality of building material index, elastic modulus and flexural strength were measured to evaluate the variation of mechanical properties. Static contact angle revealed that the coatings maintained an efficient level of hydrophobicity even after thermal-shock and freeze–thaw weathering tests. The study also revealed a critical interaction between freeze–thaw cycles, hydrophobic coatings and structural integrity of the stones, mostly on more porous ones. When they are subjected to harsh environmental conditions, untreated porous limestones keep structural cohesion, allowing for the natural absorption and release of water during freezing and thawing. On the contrary, when limestones are treated, the hydrophobic coatings can moderately obstruct the water release due to the partial saturation of the porous framework by the products. It also probably resulted from the different mechanical behavior between the inner matrix and layer of stone coated, resulting in a premature breakout and mechanical damage of the stone. Full article

The capacity of biological self-healing concrete (BSHC) to repair cracks relies on the sustained viability and metabolic function of bacteria embedded within the concrete. BSHC structures face significant risk in cold climates due to low temperatures and freeze–thaw (FT) cycles, during which freezing water can generate internal pressure that damages bacterial cells and diminishes their activity. A special feature of this study is the incorporation of bacterial spores within expanded clay aggregates, tested under varying environmental conditions. The viability of bacterial spores was measured under cold and freeze–thaw cycles by counting colony-forming units, and a specific methodology was developed to assess the efficiency of self-healing under rain-simulated conditions. It was demonstrated that bacteria embedded in concrete could endure fluctuations in low temperatures and freeze–thaw cycles, compromising approximately 50% of viable spores. Also, it was found that water immersion during concrete curing can trigger early germination, decreasing viable spore counts by nearly tenfold. Ultimately, it was demonstrated that the healing of cracks in BSHC components is influenced by the conditions under which the specimens are incubated. The results suggest that BSHC can be employed in cold climate areas, given that suitable curing conditions and adequate bacterial protection within the concrete are ensured. Full article

We examine the impact of physical climate risks on energy markets in China, distinguishing between traditional energy and new energy stock markets, and the energy commodity market, utilizing a time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR). Specifically, we investigate the dynamic effects of five specific subtypes of physical climate risks, namely waterlogging by rain, drought, typhoon, cryogenic freezing, and high temperature, on WTI oil prices and coal prices. The findings reveal that these physical climate risks exhibit time-varying similar effects on the returns of traditional energy and new energy stocks, but heterogeneous effects on the returns of WTI oil prices and coal prices. Finally, we categorize and examine the impact of both acute and chronic physical risks on the energy commodity market. Full article

The bright band (BB) is an important symbol of the ice–water transition zone in stratiform precipitation, and the presence or absence of BB will lead to different microphysical processes. In this paper, the characteristics of BB and precipitation characteristics with and without BB in summer at Tibetan Plateau (TP) as well as Central-eastern China (CEC) are analyzed by using Global Precipitation Measurement (GPM) and the fifth generation ECMWF atmospheric reanalysis of the global climates (ERA5) datasets. The results show the freezing level height and BB height in TP are 0.5 km higher than those in CEC. With the increase in rain rate, the BB height decreases in TP but increases in CEC. The BB width becomes wider with the increase in maximum radar reflectivity. Secondly, the maximum reflectivity factor and particle diameter of stratiform precipitation with BB appear at 5 km, while the maximum reflectivity factor of stratiform precipitation without BB and convective precipitation appear near the ground. The particle diameter first decreases and then increases from the cloud top to the ground. Thirdly, the land surface temperature of convective precipitation is about 2.5 °C higher than stratiform precipitation with BB, indicating higher land surface temperatures are more likely to trigger convection. Lastly, BB can lead to a decrease in brightness temperature and an increase in polarized difference at 89 GHZ and 166 GHZ in CEC, likely due to the increasing ice particles in stratiform precipitation with BB. Full article

This study aimed to prepare a facile hierarchical aluminium surface using a two-step process consisting of chemical etching in selected concentrations of CuCl₂ solution and surface grafting through immersion in an ethanol solution containing 1H, 1H, 2H, 2H-perfluorodecyltriethoxysilane. The goal was to achieve superhydrophobic characteristics on the aluminium surface, including enhanced corrosion resistance, efficient self-cleaning ability, and improved anti-icing performance. The surface characterisation of the untreated aluminium and treated in CuCl₂ solutions of different concentrations was performed using contact profilometry, optical tensiometry, and scanning electron microscopy coupled with energy dispersive spectroscopy to determine the surface topography, wettability, morphology, and surface composition. The corrosion properties were evaluated using potentiodynamic measurements in simulated acid rain solution and salt-spray test according to ASTM B117-22. In addition, self-cleaning and anti-icing tests were performed on superhydrophobic surfaces prepared under optimal conditions. The results showed that the nano-/micro-structured etched aluminium surface with an optimal 0.5 M concentration of CuCl₂ grafted with a perfluoroalkyl silane film achieved superhydrophobic characteristics, with water droplets exhibiting efficient corrosion protection, self-cleaning ability, and improved anti-icing performance with decreased ice nucleation temperature and up to 545% increased freezing delay. Full article

Existing approaches for image deraining often rely on synthetic or unpaired real-world rainy datasets, leading to sub-optimal generalization ability when processing the complex and diverse real-world rain degradation. To address these challenges, we propose a novel iterative semantic-guided detail fusion model with implicit neural representations (INR-ISDF). This approach addresses the challenges of complex solution domain variations, reducing the usual negative impacts found in these situations. Firstly, the input rainy images are processed through implicit neural representations (INRs) to obtain normalized images. Residual calculations are then used to assess the illumination inconsistency caused by rain degradation, thereby enabling an accurate identification of the degradation locations. Subsequently, the location information is incorporated into the detail branch of the dual-branch architecture, while the normalized images obtained from the INR are used to enhance semantic processing. Finally, we use semantic clues to iteratively guide the progressive fusion of details to achieve improved image processing results. To tackle the partial correspondence between real rain images and the given ground truth, we propose a two-stage training strategy that utilizes adjustments in the semantic loss function coefficients and phased freezing of the detail branch to prevent potential overfitting issues. Extensive experiments verify the effectiveness of our proposed method in eliminating the degradation in real-world rainy images. Full article

Sea surface salinity (SSS) observed by satellite has been widely used since the successful launch of the first salinity satellite in 2009. However, compared with other oceanographic satellite products (e.g., sea surface temperature, SST) that became operational in the 1980s, the SSS product is less mature and lacks effective validation from the user end. We employed an unsupervised machine learning approach to classify the Level 3 SSS bias from the Soil Moisture Active Passive (SMAP) satellite and its observing environment. The classification model divides the samples into fifteen classes based on four variables: satellite SSS bias, SST, rain rate, and wind speed. SST is one of the most significant factors influencing the classification. In regions with cold SST, satellite SSS has an accuracy of less than 0.2 PSU (Practical Salinity Unit), mainly due to the higher uncertainty in the cold environment. A small number of observations near the seawater freezing point show a significant fresh bias caused by sea ice. A systematic bias of the SMAP SSS product is found in the mid-latitudes: positive bias tends to occur north (south) of 45°N(S) and negative bias is more common in 25°N(S)–45°N(S) bands, likely associated with the SMAP calibration scheme. A significant bias also occurs in regions with strong ocean currents and eddy activities, likely due to spatial mismatch in the highly dynamic background. Notably, satellite SSS and in situ data correlations remain good in similar environments with weaker ocean dynamic activities, implying that satellite salinity data are reliable in dynamically active regions for capturing high-resolution details. The features of the SMAP SSS shown in this work call for careful consideration by the data user community when interpreting biased values. Full article

Modeling the atmospheric boundary layer (ABL) in the area of a wind farm using computational fluid dynamics (CFD) methods allows us to study the characteristics of air movement, the shading effect, the influence of relief, etc., and can be actively used in studies of local territories where powerful wind farms are planned to be located. The operating modes of a wind farm largely depend on meteorological phenomena, the intensity and duration of which cause suboptimal operating modes of wind farms, which require the use of modern tools for forecasting and classifying precipitation. The methods and approaches used to predict meteorological phenomena are well known. However, for designed and operated wind farms, the influence of meteorological phenomena on the operating modes, such as freezing rain and hail, remains an urgent problem. This study presents a multi-layered neural network for the classification of precipitation zones, designed to identify adverse meteorological phenomena for wind farms according to weather stations. The neural network receives ten inputs and has direct signal propagation between six hidden layers. During the training of the neural network, an overall accuracy of 81.78%, macro-average memorization of 81.07%, and macro-average memorization of 75.05% were achieved. The neural network is part of an analytical module for making decisions on the application of control actions (control of the boundary layer of the atmosphere by injection of silver iodide, ionization, etc.) and the formation of the initial conditions for CFD modeling. Using the example of the Ulyanovsk wind farm, a study on the movement of air masses in the area of the wind farm was conducted using the initial conditions of the neural network. Digital models of wind turbines and terrain were created in the Simcenter STAR-CCM+ software package, version 2022.1; an approach based on a LES model using an actuating drive disk model (ADM) was implemented for modeling, allowing calculation with an error not exceeding 5%. According to the results of the modeling of the current layout of the wind turbines of the Ulyanovsk wind farm, a significant overlap of the turbulent wake of the wind turbines and an increase in the speed deficit in the area of the wind farm were noted, which significantly reduced its efficiency. A shortage of speed in the near and far tracks was determined for special cases of group placement of wind turbines. Full article

The impact of lichens on the conservation of monuments, such as the World Heritage Site (WHS) of Cappadocian churches, presents a multifaceted challenge for conservators. Previous studies have shown that lichens can both induce deterioration processes of stone through their penetration into the substrate and chemical interactions as well as provide bioprotection, forming encrustations including calcium oxalate layers, which help mitigating the effects of weathering, reducing water penetration and eolian erosion. Evaluating the impact of lichens requires a comprehensive understanding of various factors, which include the type of rock substrate, the colonizing lichen species, the monument architecture, and the prevailing physic-chemical weathering processes. This study aims to provide a comprehensive analysis of the impact of lichen colonization on Saint Simeon Church in the Paşabağı Valley (Turkey) with a multidisciplinary approach to investigate the interplay between lichens, microclimatic conditions, and the degradation of stone. Specifically, this study examines the influence of wind-driven rain (WDR) occurrences on lichen distribution and stone weathering to develop comprehensive conservation strategies. The results confirmed the previous observations and showed a prevalence of the protective role of lichens over their deterioration. The northwest side of the church, despite being heavily impacted by environmental factors such as WDR and freezing–thawing cycles, showed reduced deterioration due to extensive lichen coverage. In contrast, the northeast side, with lower lichen colonization, demonstrated more severe deterioration. These findings suggest that integrating the protective aspects of lichen colonization into conservation strategies can enhance their preservation. Full article

The preservation of cultural heritage, particularly historical stone structures, represents a very challenging matter due to several environmental and anthropogenic factors. Vicenza stone, a calcareous rock known for its historical significance and widespread use in architectural masterpieces, requires significant attention for conservation. In fact, as the demand for sustainable and effective preservation methods intensifies, the exploration of innovative consolidation strategies becomes essential. To this end, inorganic consolidants, based on alkaline silicate formulations and nano-silica, were explored for their promising performance in enhancing the surface properties and chemical stability of Vicenza stone. In particular, the durability of treated and untreated Vicenza stone samples was evaluated by means of accelerated weathering tests such as freeze–thaw cycles, salt crystallization and simulation of acid rain. The experimental results revealed that Vicenza stone is very resistant to the effects of freeze–thaw cycles and acid rain; both the accelerated weathering tests did not show significant differences between treated and untreated VS samples. A different behavior was detected for the test for resistance to salt crystallization, whose findings led us to deduce that, for this kind of degradation, it is possible to observe a more beneficial effect of the consolidation treatments on the stone durability. Full article

Snow cover and runoff play an important role in the Arctic environment, which is increasingly affected by climate change. Over the past 30 years, winter temperatures in northern Sweden have risen by 2 °C, accompanied by an increase in precipitation. This has led to a higher incidence of thaw–freeze and rain-on-snow events. Snow properties, such as the snow depth and longevity, and the timing of snowmelt in spring significantly impact the alpine tundra vegetation. The emergent vegetation at the edge of the snow patches during spring and summer constitutes an essential nutrient supply for reindeer. We have used Sentinel-1 synthetic aperture radar (SAR) to determine the onset of the surface melt and the end of the snow cover in the core reindeer grazing area of the Laevás Sámi reindeer-herding community in northern Sweden. Using SAR data from March to August during the period 2017 to 2021, the start of the surface melt is identified by detecting the season’s backscatter minimum. The end of the snow cover is determined using a threshold approach. A comparison between the results of the analysis of the end of the snow cover from Sentinel-1 and in situ measurements, for the years 2017 to 2020, derived from an automatic weather station located in Laevásvággi reveals a 2- to 10-day difference in the snow-free ground conditions, which indicates that the method can be used to investigate when the ground is free of snow. VH data are preferred to VV data due to the former’s lower sensitivity to temporary wetting events. The outcomes from the season backscatter minimum demonstrate a distinct 25-day difference in the start of the runoff between the 5 investigated years. The backscatter minimum and threshold-based method used here serves as a valuable complement to global snowmelt monitoring. Full article

This paper presents the extension of the monolayer snow model of a semi-distributed hydrological model (HYDROTEL) to a multilayer model that considers snow to be a combination of ice and air, while accounting for freezing rain. For two stations in Yukon and one station in northern Quebec, Canada, the multilayer model achieves high performances during calibration periods yet similar to the those of the monolayer model, with KGEs of up to 0.9. However, it increases the KGE values by up to 0.2 during the validation periods. The multilayer model provides more accurate estimations of maximum SWE and total spring snowmelt dates. This is due to its increased sensitivity to thermal atmospheric conditions. Although the multilayer model improves the estimation of snow heights overall, it exhibits excessive snow densities during spring snowmelt. Future research should aim to refine the representation of snow densities to enhance the accuracy of the multilayer model. Nevertheless, this model has the potential to improve the simulation of spring snowmelt, addressing a common limitation of the monolayer model. Full article

Yunnan plays a pivotal role in transmitting electricity from west to east within China’s Southern Power Grid. During 7–13 January 2021, a large-scale continuous ice-covering event of ultra-high voltage (UHV) transmission lines occurred in the Qujing area of eastern Yunnan Province. Based on ERA5 reanalysis data and meteorological observation data of UHV transmission line icing in China’s Southern Power Grid, the synoptic causes of the icing are comprehensively analyzed from various perspectives, including weather situations, vertical stratification of temperature and humidity, local meteorological elements, and atmospheric circulation indices. The results indicate a strong East Asian trough and a blocking high directing northern airflow southward ahead of the ridge. Cold air enters the Qujing area and combines with warm and moist air from the subtropical high pressure of 50–110° E. As warm and cold air masses form a quasi-stationary front over the northern mountainous area of Qujing due to topographic uplift, the mechanism of “supercooling and warm rain” caused by the “warm–cold” temperature profile structure leads to freezing rain events. Large-scale circulation indices in the Siberian High, East Asian Trough, and 50–110° E Subtropical High regions provided clear precursor signals within 0–2 days before the icing events. Full article

Damage to birch (Betula spp.) trees after an extensive freezing rain and snowing event was assessed in hemiboreal stands aged from 2 to 30 years. Tree diameter, height, and stem bending were measured, stand age and time of thinning were obtained from inventory data, and the relative distance from a sample plot to the nearest adjacent stand was calculated. Stem bending was remeasured after one and three growing seasons to assess tree recovery potential. Stem damage was found for 31.0% of birch trees, with 93.7% of them bent. The probability of being bent was increased (p < 0.001) for trees of a lower social position within the stand and was higher in stands with larger growing stock (p < 0.05) and relative distance to the adjacent stand (p < 0.001). The probability of damage was significantly (p < 0.05) affected by recent tree removal, with decreasing susceptibility until five to six years after the last thinning. After one growing season, 31.3% of trees had less intense bending, and 8.2% had more intense bending compared with the initial assessment. A tree’s ability to recover stem bending to less than 15° was linked (p < 0.001) to its damage intensity, whereas the magnitude of the recovery was affected by both the damage intensity and the relative diameter (p < 0.001 and p < 0.01, respectively). The results indicate the importance of timely thinning that maintains a stable tree form and is performed considering the spatial planning of heterogeneity in the heights of adjacent stands to avoid damage at a young age. Full article