Snowfall Conditions Research Articles

Analyzing influences of snowfall on electric field at the interface of composite cross-arm with finite element method

The composite cross-arm was used in large numbers in power systems due to its safety and economic advantages. The interfaces were the weak link in the property of composite cross-arm. However, the influence of severe weather such as ice and snow on the interface property was not clear, which would bring potential risks to operation safety for composite cross-arm. To this end, the finite element method was used to study the characteristics of the electric field at the FRP-silicone rubber and FRP-RPUF interfaces under snowfall conditions in this paper. Firstly, the snow and snowmelt models of the composite cross-arm were established by combining the natural snowfall conditions and the classical snowed model, then the influence of snowed degrees, snowmelt stages and dry-band on the interfaces electric field was analyzed. The results show that the snow without melting basically does not change the interface electric field. During the snowmelt stages, the average electric field intensity of the FRP-silicone rubber interface increases and the maximum electric field intensity of the two interfaces decreases. The distortion of the interface electric field caused by the dry-band in the middle snowmelt stage is the most serious, at this time, the electric fields at FRP-silicone rubber interfaces reach a maximum of 14.72 kV/cm and 8.53 kV/cm respectively. When the length of dry-band reaches or exceeds the distance between the high-voltage fitting and the eighth large umbrella skirt, it basically no longer causes the distortion of interface electric field. Compared to the FRP-RPUF interface, the FRP-silicone rubber interface is more severely affected by snowfall. The results can provide a reference for improving the interface property and ensuring the safety of the composite cross-arm in severe weather conditions.

강설과 눈 비산 상황에 따른 고속열차의 착설에 대한 수치적 비교 연구

The accumulation of snow on train bogies hinders the smooth operation of important parts, degrading the safety of the vehicle. This is primarily due to snowfall and snow saltation from the ground. This study conducted a comparative study on the snow accumulation of high-speed trains due to snowfall and snow saltation conditions. To describe the movement of the snow, we adopted the Eulerian method which consists of continuity and momentum equations for snow density. Additionally, the process of snow saltation was described by implementing the semi-empirical model into a boundary condition. As a result, the snow accumulation on the train showed different trends in the snowfall and snow saltation conditions. The amount of snow accumulation decreased toward the rear of the train in snowfall conditions, but it showed a tendency to increase toward the rear in snow saltation conditions.

Experimental investigation of snow drifting on flat roofs during snowfall: Impact of roof span and snowfall intensity

Owing to the controllability and reliability, wind tunnel experiment is considered as a powerful and effective approach for the investigation of snow drifting. Most of the previous experimental studies were mainly concerned with snow drifting on roofs without snowfall, in which a layer of particles was uniformly paved on the roof surface to model the initial snow cover. Hence, a cryogenic wind tunnel experiment using artificial snow particles was conducted to investigate snow drifting on flat roofs during snowfall. The similarity requirement related to snowfall intensity is derived according to the similarities of snow distribution pattern and the development of snow transport. Based on the results of snow distributions and transport rates for different roof spans and snowfall intensities, the features of snow drifting under snowfall conditions are analyzed in detail. The concurrence of snowfall is further revealed to greatly affect the development of snow drifting on flat roofs and thereby result in a reduction in the required fetch for reaching the saturated state. And the typical distribution patterns for snow drifting on flat roofs with and without snowfall are also summarized. Besides, the snow transport rate is found to increase along the roof surface before the achievement of the saturated state, whereas a slight decrease in the degree of snow erosion with roof span is observed. But the location of the crest formed near the windward edge is nearly unaffected by roof span as well as snowfall intensity. The results also indicate obvious linear characteristics in the relationship between the degree of erosion on the roof surface and snowfall intensity. And the normalized development process of snow transport before reaching the saturated state is nearly independent of snowfall intensity, although both the saturated transport rate and the required fetch for saturated drifting are strongly affected in the meantime.

Determining Freshwater Lake Communities’ Vulnerability to Snowstorms in the Northwest Territories

As the exposure to extreme snowstorms continues to change in response to a warming climate, this can lead to higher infrastructure damages, financial instability, accessibility restrictions, as well as safety and health effects. However, it is challenging to quantify the impacts associated with the combination of the many biophysical and socio-economic factors for resiliency and adaptation assessments across many disciplines on multiple spatial and temporal scales. This study applies a framework to quantitatively determine the multiple impacts of snowstorms by calculating the livelihood vulnerability index (LVI) for four exposed freshwater lake communities in Canada’s Northwest Territories using three contributing factors (exposure, sensitivity, and adaptive capacity). Results indicate that Déline is the most vulnerable community (0.67), because it has the highest exposure and one of the highest sensitivity ranks, while its ability to adapt to exposure stressors is the lowest among the communities. In contrast, Fort Resolution exhibits the lowest LVI (0.26) and has one of the highest adaptive capacities. This study emphasizes that while these freshwater communities may be exposed to snowstorms, they have different levels of sensitivity and adaptive capacities in place that influences their vulnerability to changes in hazardous snowfall conditions. The information gained from this study can help guide future adaptation, mitigation, and resiliency practices for Arctic sustainability efforts.

Conceptualizing How Agencies Could Leverage Weather-Related Connected Vehicle Application to Enhance Winter Road Services

Abstract Winter inclement weather negatively influences the safety, mobility, economy, and user experience of roadway transportation systems. Ice and snowfall conditions result in more accidents an...

Classification of pavement climatic regions through unsupervised and supervised machine learnings

This study extracted 16 climatic data variables including annual temperature, freeze thaw, precipitation, and snowfall conditions from the Long-term Pavement Performance (LTPP) program database to evaluate the climatic regionalization for pavement infrastructure. The effect and significance of climate change were firstly evaluated using time as the only predictor and t-test. It was found that both the temperature and humidity increased in most States. Around one third of the 800 weather stations record variation of freeze and precipitation classifications and a few of them show significant change of classifications over time based on the results of logistic regression analyses. Three unsupervised machine learning including Principle Component Analysis (PCA), factor analysis and cluster analysis were conducted to identify the main component and common factors for climatic variables, and then to classify datasets into different groups. Then, two supervised machine learning methods including Fisher’s discriminant analysis and Artificial Neural Networks (ANN) were adopted to predict the climatic regions based on climatic data. Results of PCA and factor analysis show that temperature and humidity are the first two principle components and common factors, accounting for 71.6% of the variance. The 4-means clusters include wet no freeze, dry no freeze, dry freeze and snow freeze. The best k-mean clustering suggested 9 clusters with more temperature clusters. Both the Fisher’s linear discriminant analysis and ANN can effectively predict climatic regions with multiple climatic variables. ANN performs better with higher R square and low misclassification rate, especially for those with more layers and nodes.

What millimeter-wavelength radar reflectivity reveals about snowfall: an information-centric analysis

Abstract. The ability of single-frequency, millimeter-wavelength radar reflectivity observations to provide useful constraints for retrieval of snow particle size distribution (PSD) parameters, snowfall rates, and snowfall accumulations is examined. An optimal estimation snowfall retrieval that allows analyses of retrieval uncertainties and information content is applied to observations of near-surface W-band reflectivities from multiple snowfall events during the 2006–2007 winter season in southern Ontario. Retrieved instantaneous snowfall rates generally have uncertainties greater than 100 %, but single-event and seasonal snow accumulations from the retrieval results match well with collocated measurements of accumulations. Absolute fractional differences are mainly below 30 % for individual events that have more substantial accumulations and, for the season, 12.6 %. Uncertainties in retrieved snowfall rates are driven mainly by uncertainties in the retrieved PSD parameters, followed by uncertainties in particle model parameters and, to a lesser extent, the uncertainties in the fall-speed model. Uncertainties attributable to assuming an exponential distribution are negligible. The results indicate that improvements to PSD and particle model a priori constraints provide the most impactful path forward for reducing uncertainties in retrieved snowfall rates. Information content analyses reveal that PSD slope is well-constrained by the retrieval. Given the sensitivity of PSD slope to microphysical transformations, the results show that such retrievals, when applied to radar reflectivity profiles, could provide information about microphysical transformations in the snowing column. The PSD intercept is less well-constrained by the retrieval. While applied to near-surface radar observations in this study, the retrieval is applicable as well to radar observations aloft, such as those provided by profiling ground-based, airborne, and satellite-borne radars under lighter snowfall conditions when attenuation and multiple scattering can be neglected.

Not avian but mammalian scavengers efficiently consume carcasses under heavy snowfall conditions: a case from northern Japan

Interest in trophic interactions and ecosystem functions derived from carcass consumption by scavengers has been increasing. Here, we conducted the first evaluation of scavenging processes in an ecosystem with heavy snow, located in northern Japan, which is characterized by the limitations of visual and odor cues to detect carcasses. In this study, we verified the behavioral traits and assemblage compositions of avian and mammalian scavengers, which consumed six different carcass types buried in snow. We measured the visits of scavengers using camera traps between 2010 and 2020. The total scavenger richness observed was relatively low (only 12 species) compared to warmer biomes. We observed seven avian scavenger species, but their visit frequencies were extremely low compared with those of nocturnal mammalian scavengers, such as raccoon dogs (Nyctereutes procyonoides) and martens (Martes melampus), which were able to detect carcasses more rapidly and frequently. Our findings imply that large snow piles significantly prevent avian scavengers from detecting carcasses. In contrast, the snow piles could protect carcasses from the freezing air and ensure the occurrence of a basal level of microbial decomposition, possibly leading to carcass decomposition. This probably results in carcasses still providing odor cues for mammalian scavengers with heightened sense of smell. Moreover, considering the high carcass consumption rate (91.3% of full-body carcass; n = 23) and short carcass detection times (approximately 90 h) observed, it is possible that scavenging in heavy snowfall conditions has become systematically integrated into the foraging tactics of many mammalian scavengers.

Design and Intensive Experimental Evaluation of an Enhanced Visible Light Communication System for Automotive Applications.

As the interest toward communication-based vehicle safety applications is increasing, the development of secure wireless communication techniques has become an important research area. In this context, the article addresses issues that are related to the use of the visible light communication (VLC) technology in vehicular applications. Thus, it provides an extensive presentation concerning the main challenges and issues that are associated to vehicular VLC applications and of some of the existing VLC solutions. Moreover, the article presents the aspects related to the design and intensive experimental evaluation of a new automotive VLC system. The experimental evaluation performed in indoor and outdoor conditions shows that the proposed system can achieve communication distances up to 50 m and bit error ratio (BER) lower than 10−6, while being exposed to optical and weather perturbations. This article provides important evidence concerning the snowfall effect on middle to long range outdoor VLC, as the proposed VLC system was also evaluated in snowfall conditions. Accordingly, the experimental evaluation showed that snowfall and heavy gust could increase bit error rate by up to 10,000 times. Even so, this article provides encouraging evidence that VLC systems will soon be able to reliably support V2X communications.

Soil temperature and soil moisture dynamics in winter and spring under heavy snowfall conditions in North‐Eastern Japan

AbstractWarm winters and high precipitation in north‐eastern Japan generate snow covers of more than three meters depth and densities of up to 0.55 g cm−3. Under these conditions, rain/snow ratio and snowmelt have increased significantly in the last decade under increasing warm winters. This study aims at understanding the effect of rain‐on‐snow and snowmelt on soil moisture under thick snow covers in mid‐winter, taking into account that snowmelt in spring is an important source of water for forests and agriculture. The study combines three components of the Hydrosphere (precipitation, snow cover and soil moisture) in order to trace water mobility in winter, since soil temperatures remained positive in winter at nearly 0.3°C. The results showed that soil moisture increased after snowmelt and especially after rain‐on‐snow events in mid‐winter 2018/2019. Rain‐on‐snow events were firstly buffered by fresh snow, increasing the snow water equivalent (SWE), followed by water soil infiltration once the water storage capacity of the snowpack was reached. The largest increase of soil moisture was 2.35 vol%. Early snowmelt increased soil moisture with rates between 0.02 and 0.035 vol% hr−1 while, rain‐on‐snow events infiltrated snow and soil faster than snowmelt and resulted in rates of up to 1.06 vol% hr−1. These results showed the strong connection of rain, snow and soil in winter and introduce possible hydrological scenarios in the forest ecosystems of the heavy snowfall regions of north‐eastern Japan. Effects of rain‐on‐snow events and snowmelt on soil moisture were estimated for the period 2012–2018. Rain/snow ratio showed that only 30% of the total precipitation in the winter season 2011/2012 was rain events while it was 50% for the winter 2018/2019. Increasing climate warming and weakening of the Siberian winter monsoons will probably increase rain/snow ratio and the number of rain‐on‐snow events in the near future.

Exploring the effect of thermoplastic composition on light emission

Currently, reflective coloring agents are used for road markings. To obtain the best result from the use of the light-reflecting effect of the marking, we propose to use luminophore (light-emitting powder), by adding it to the thermoplastic composition heated at about 200 ° C. It can ensure the best visibility in the dark, in the conditions of rain and snowfall. The effect of the use of this technology will be visible both in urban and rural areas, where it can surely be an excellent alternative in case of the absence of stationary lighting. This will give the driver a good view of the route, even with the lights off. By analyzing the available and relevant information and conducting the necessary research and experimentation, the main goal will be to obtain the best results and a rational proportion of components in the manufacture of experimental samples that provide the maximum light-emitting effect.

Experimental Research on the Deformation and Failure Characteristics of Coarse-Grained Soil Slopes in Seasonal Frozen Region along Sichuan-Tibet Railway

The field investigation of the seasonal coarse grained frozen soil slopes along the eastern section of the proposed Sichuan-Tibet railway shows that the deformation and failure of the slopes are widespread. In order to explore the deformation characteristics and failure mechanisms of the slopes in this area and provide a basis for the design and protection of the slopes along Sichuan-Tibet railway, laboratory model tests on the seasonal coarse grained frozen soil slopes under snowfall conditions were conducted. The results show that, the deformation and failure of the seasonal coarse grained frozen soil slope are caused by the repeated alternation of the failure of the surface soil structure caused by frost heave and the surface soil saturation caused by snow thaw infiltration, and the reduction of the shear strength of the surface soil under repeated freezing and thawing conditions. The deformation and failure of the seasonal coarse grained frozen soil slopes along the eastern section of the Sichuan-Tibet railway are mainly characterized by creep-flowed, topsoil slip and slippage on slope surface. The emphasis of slope protection in this area are slope thermal insulation and waterproof.

Hazardous weather affecting European airports: Climatological estimates of situations with limited visibility, thunderstorm, low-level wind shear and snowfall from ERA5

The consistently growing demand for airline transportation has resulted in increased air traffic and air operations in airports across the world. According to the International Air Transport Association, forecasts assume that in the year 2036 about 7.8 billion passengers will travel using air transport. In Europe, it is estimated that 16.2 million flights will take place in 2040, 53% more than in 2017. One of the crucial factors that significantly affect air transportation is the weather. In this article, ERA5 reanalysis and a 40-year timeframe (1979–2018) are used to construct the European climatology of environmental proxies associated with hazardous weather conditions causing disruptions in airline traffic. These include situations with limited visibility, thunderstorm, low-level wind shear, and snowfall. Results indicate that northern Europe and mountain zones are the most often affected by unfavorable weather conditions, while southern Europe is the least affected. Winter has the highest estimated number of situations with low-level wind shear and snowfall conditions. Situations with limited visibility are the most frequent in autumn and winter while thunderstorms are the main threat during summer over continental Europe and autumn in the Mediterranean area. Long-term changes of the analyzed proxies indicate that situations with low-level wind shear and snowfall are becoming less frequent while the number of thunderstorms generally increases, particularly over northern, central and south-central Europe. A decrease of situations with limited visibility is observed over majority of Europe with the exception of Scandinavia and parts of central Europe.

Sensitivity of snowfall radar reflectivity to maximum snowflake size and implications for snowfall retrievals

The cutoff point of the snowflake (or snow and ice particle) size distribution (SSD) used for modeling the snowfall radar reflectivity and for snowfall retrievals in radar remote sensing is characterized by high uncertainties because only very limited information is available about the maximum snowflake size for different snow types and snowfall conditions. To complement previous works that examined the influence of other snowfall microphysical characteristics on the analysis of snowfall radar reflectivity, this study investigates the impact of SSD cutoff size on modeled snowfall radar reflectivity factors at X, Ku, Ka, and W band and evaluates implications for radar snowfall retrievals. While a detailed assessment can only be realized for snowfall retrieval algorithms individually, this study focuses on identifying typical snowfall characteristics where accounting for uncertainties in SSD cutoff size can be especially important. These include snowflake populations limited to a maximum snowflake size of a few mm or characterized by a small SSD (exponential) slope parameter or a large SSD (gamma distribution) shape parameter. In general, using SSD cutoff sizes that overestimate the maximum snowflake size has a smaller impact on modeled radar reflectivity and simulated snowfall retrievals than underestimating the maximum snowflake size by the same amount. Summarizing SSDs by their median volume diameter, i.e., combining SSD slope parameter, shape parameter, and cutoff size into a single characteristic snowflake size, mitigates the impact that uncertainties in these parameters can have on the analysis of snowfall radar reflectivity and may therefore offer a robust approach for relating radar snowfall retrievals to snowfall microphysics.

Size distribution and concentration of aerosol particles in Yinchuan area, China

ABSTRACTThe size distribution and concentration of atmospheric aerosol particles are important parameters that characterize the physical and optical properties of aerosols. Understanding the spectral distribution of atmospheric particles is fundamental for studying particulate pollution. Based on observational data acquired by an aerodynamic particle sizer APS-3321 and a laser dust meter LD-5 from September 2017 to July 2018, the temporal evolution of particle size distribution and concentration of aerosols were studied at the North Minzu University in Yinchuan (38°29’52"N 106°06’28"E), China. By cluster analysis of particle surface area distribution in different weathers, seven clusters were obtained and discussed. The experimental results showed that the particle number and mass concentrations were different in the four seasons of the year. Compared with the unimodal distribution of the particle number concentration and the doublet mass concentration distribution in sunny weather conditions, there were great differences in the particle spectrum distribution in haze, snowfall, and dusty weather conditions. The particle surface area distributions of the seven clusters were clearly different from each other and influenced by meteorological conditions. Additionally, the PM2.5 value has a relationship with the meteorological elements. The research is helpful to reveal the formation mechanism and source of aerosols in Yinchuan, China.

Assessment of GPM high‐frequency microwave measurements with radiative transfer simulation under snowfall conditions

The Global Precipitation Mission (GPM) Microwave Imager (GMI) has four channels at 166 and 183 GHz that provide critical information on snow precipitation. Since the applications of these high‐frequency microwave channels to snowfall prediction and retrieval are still in a very early stage, it is important to evaluate the biases between observed and simulated brightness temperatures for those channels under snowfall conditions. A radiative transfer model that supports the computation of single‐scattering properties for non‐spherical snow particles is employed to simulate GMI brightness temperatures. Snow water content profiles are first derived from the CloudSat Cloud Profiling Radar (CPR) measurements and then used as input to the radiative transfer model. Results show that the biases of observed minus simulated brightness temperatures for GMI channels averaged over all selected pixels are generally less than 1 K under snowfall conditions, except for the 166 GHz horizontal polarization (166H) channel that has a bias of about 3 K. Larger biases are observed under snowfall conditions when the scene brightness temperatures are low. Further investigation indicates that the GMI remaining biases are often associated with shallow snow cells or deep convective clouds. We hypothesize that in shallow snow cells the errors in retrieved cloud liquid water likely contribute to the large bias for the GMI 166H channel, while in deep convective clouds the attenuation in CPR radar reflectivities and possible sampling bias likely cause the biases for GMI channels under low scene brightness temperatures. This study lays out an applicable configuration in simulating microwave brightness temperatures at high frequency under snowfall conditions, and the explanation provided for the GMI remaining biases at 166 and 183 GHz are useful for future applications of these channels.

Increased snowfall weakens complementarity of summer water use by different plant functional groups.

Winter snowfall is an important water source for plants during summer in semiarid regions. Snow, rain, soil water, and plant water were sampled for hydrogen and oxygen stable isotopes analyses under control and increased snowfall conditions in the temperate steppe of Inner Mongolia, China. Our study showed that the snowfall contribution to plant water uptake continued throughout the growing season and was detectable even in the late growing season. Snowfall versus rainfall accounted for 30% and 70%, respectively, of the water source for plants, on the basis of hydrogen stable isotope signature (δD) analysis, and accounted for 12% and 88%, respectively, on the basis of oxygen stable isotope signature (δ18O) analysis. Water use partitioning between topsoil and subsoil was found among species with different rooting depths. Increased snowfall weakened complementarity of plant water use during summer. Our study provides insights into the relationships between precipitation regimes and species interactions in semiarid regions.

A study of snow drifting on a flat roof during snowfall based on simulations in a cryogenic wind tunnel

Wind tunnel simulation is a very important approach to studying snow drifting and predicting drift snow loads on roofs. A complete simulation of the full process of wind-induced snow accumulation on a roof should include snow drifting both during snowfall and after snowfall. However, in most of the previous studies, snow drifting phenomenon was only simulated without concurrence of snowfall. We herein describe simulations of snow drifting on a flat roof during snowfall, which were carried out in a cryogenic wind tunnel using artificial snow particles. Based on the results, we demonstrate the differences and similarities between snow drifting during snowfall and that without concurrent snowfall. The developments of snow transport before saturated state apparently follow the same rule, no matter whether there is concurrent snowfall or not. However, it seems that the required fetch distance for a saturated saltation state can be reduced by snowfall. A formula is proposed to more reasonably describe the development of snow transport rate. Based on test results and deductions, some discussions on similarity requirements for modelling snow drifting on roofs during snowfall will be presented. Finally, a prediction of the prototype fetch distances under different wind and snowfall conditions will also be presented, which can provide a guide for further research and engineering application.

Controls on stream hydrochemistry dynamics in a high Arctic snow‐covered watershed

AbstractArctic streams are highly sensitive to climate change due to warmer air temperature and increased precipitation associated with an encroaching low Arctic climatic zone into currently high‐Arctic coastal areas. Increases in nivation processes and permafrost degradation will lead to potential changes in stream physicochemical habitat, although these impacts are poorly understood. To address this gap, physicochemical habitat characteristics in streams around Zackenberg in Northeast Greenland National Park were investigated during the summers of 2013 to 2016. Streams with different sized snowpacks represented both low and high snowfall conditions leading to different nivation processes. Streams with larger snowpacks displayed lower channel stability, with higher channel mobility, suspended sediment and solute concentrations. Suspended sediment concentration was identified as a key driver of stream solute concentrations, and varying snowpack levels caused high interannual variability in solute concentrations. Winter snowpack size was confirmed to be an important driver of stream physicochemical habitat in an Arctic region with low glacial cover. We predict climate change will strongly impact stream hydrochemistry in this region through increased nivation processes alongside active layer thickening and solifluction, thereby increasing stream suspended sediment and solute concentrations. These findings indicate that hydrochemistry was principally a function of erosion, with variation being determined by spatial and temporal patterns in erosional processes, and as such, alternative methods to fingerprint water sources should be considered in this region.

An experimental investigation of snow removal from photovoltaic solar panels by electrical heating

A key challenge to the wide-scale implementation of photovoltaic solar panels (PV) in cold and remote areas is dealing with the effects of snow and ice buildup on the panel surfaces. In this study, a thermal method for snow removal from PV solar panels was experimentally tested. Nine PV panels were mounted at tilt angles of 30, 45 and 55° (three panels at each angle). One of the panels at each angle was insulated on the back with a heater embedded between the panel surface and a back layer of insulation. The other two panels remained unheated as reference cases. Outdoor tests were conducted under natural conditions including different snowfall conditions. Solar radiation, ambient temperature, relative humidity and wind speed were also measured during each test. Results showed that the frame at the bottom edge of the panels prevented the snow-cover from sliding off the panels. In addition, it was observed that the entire panel surface requires heat to remove snow, as the panel thermal conduction was not sufficient to conduct heat to unheated areas. To investigate these issues, the lower edge of the frame for one of the reference panels at tilt angle of 45° was removed, and the panel was heated using reversing electrical current flow through it. For most of the experiments with this panel, the snow-cover slid off the panel in less than 30 min.