Impact Of Snowfall Research Articles

Research on Glacier Changes and Their Influencing Factors in the Yigong Zangbo River Basin of the Tibetan Plateau, China, Based on ICESat-2 Data

The intense changes in glaciers in the southeastern Tibetan Plateau (SETP) have essential impacts on regional water resource management. In order to study the seasonal fluctuations of glaciers in this region and their relationship with climate change, we focus on the Yigong Zangbo River Basin in the SETP, extract the annual and seasonal variations of glaciers in the basin during 2018–2023, and analyze their spatio-temporal characteristics through the seasonal-trend decomposition using the LOESS (STL) method. Finally, combining the Extreme Gradient Boosting (XGBoost) model and the Shapley additive explanations (SHAP) model, we assess the comprehensive impact of meteorological factors such as temperature and snowfall on glacier changes. The results indicate that glaciers in the Yigong Zangbo River Basin experienced remarkable mass loss during 2018–2023, with an average annual melting rate of −0.83 ± 0.12 m w.e.∙yr−1. The glacier mass exhibits marked seasonal fluctuations, with increases in January–March (JFM) and April–June (AMJ) and noticeable melting in July–September (JAS) and October–December (OND). The changes over these four periods are 2.12 ± 0.04 m w.e., 0.93 ± 0.15 m w.e., −1.58 ± 0.19 m w.e., and −1.32 ± 0.17 m w.e., respectively. Temperature has been identified as the primary meteorological driver of glacier changes in the study area, surpassing the impact of snowfall. This study uses advanced altimetry data and meteorological data to monitor and analyze glacier changes, which provides valuable data for cryosphere research and also validates a set of replicable research methods, which provides support for future research in related fields.

Impact of Snowfall on Terahertz Channel Performance: Measurement and Modeling Insights

Impact of Snowfall on Terahertz Channel Performance: Measurement and Modeling Insights

CFD-Based Sensitivity-Analysis and Performance Investigation of a Hydronic Road-Heating System

To minimize the impact of snowfall and ice formation on safety of transportation, salt is sprinkled on the asphalt every winter. However, the use of salt has economical as well as ecological disadvantages. To resolve these problems, road heating systems are used in the northern regions of Europe and America. Despite their widespread usage, considerable potential of the operational optimization is evident. The current systems are controlled under predefined weather conditions such as start of operation at 5 °C air temperature, even when snowfall is absent. Consequently, loss of energy input to heat the system is caused. To avoid unnecessary financial and energetic expense, this study presents CFD-based performance investigation as a basis for a novel predictive controller to increase the operational efficiency of hydronic road heating systems (HRS). The simulation model was developed based on a real operational HRS located in Ingolstadt and composed of bridges and ramps for a total surface of 1989 m2. Climate data of the years 2019–2020 from local weather stations were implemented in the simulation model for performance prediction on extreme climate conditions. This investigation identified that up to 70% of operational hours in terms of energy input can be saved by using a hypothetical predictive controller, thus making the HRS a more economically efficient and environmentally attractive alternate to conventional de-icing techniques.

Influence of weather conditions on the traffic flow parameters on Pešter plateau

In the middle of the last century, research began on the influence of weather conditions on the parameters of traffic flow. Due to the lack of these researches in our country, the aim of this paper was to perform a detailed analysis of the impact of snowfall on the volume and speed in the traffic flow on the sections of state road IB order on the Peshter plateau. For the needs of the research, three traffic sections were selected, which are suitable for the realization of this analysis due to their position, characteristics of traffic flows and geometric and operational features. The research was performed by comparing the flow and velocities between the periods with and without intense snowfall. The obtained results show that intense snowfall reduces traffic volume by more than 40% and average speeds in the range of 9 - 18% depending on the analyzed section, on a total sample of 123,014 vehicles, which is a statistically significant sample size. When it comes to velocity dispersion, no significant change between the two reference periods was observed on either of the observed sections.

The Impact of Snowfall on Crashes, Traffic Volume, and Revenue on the New York State Thruway

Abstract Snow has numerous effects on traffic, including reduced traffic volumes, greater crash risk, and increased travel times. This research examines how snow affects crash risk, traffic volume, and toll revenue on the New York State Thruway. Daily data from January for a 10-yr period (2010–19) were analyzed for the Thruway from the Pennsylvania state line in western New York to Syracuse. Anywhere from 35% to 50% of crashes are associated with inclement weather, with smaller impacts, proportionally, in areas with greater traffic volumes. As expected, snow was almost always involved when weather was a factor. “Unsafe speed” was the most common cause of crashes in inclement weather with all other factors (e.g., animals, drowsiness) much less likely to play a role. The percentage of crashes resulting in an injury did not change significantly with inclement conditions when compared with crashes occurring in fair conditions, and there were too few fatal crashes to make any inferences about them. Daily snowfall rates predicted about 30% of the variation in crash numbers, with every 5.1 cm of snowfall resulting in an additional crash, except in Buffalo where 5.1 cm of snow resulted in an additional 2.6 crashes. Confirming earlier results, daily snowfall had a large impact on passenger vehicle counts whereas commercial vehicle counts were less affected. Revenue data showed a similar pattern, with passenger revenue typically decreasing by 3%–5% per 2.5 cm of snow, whereas commercial revenue decreases were 1%–4% per 2.5 cm of snow. Significance Statement While it seems obvious that snowfall increases the number of crashes, decreases traffic volume, and reduces toll revenues, research is limited to support these assumptions, especially the latter two. This study involved an analysis of such items for the New York State Thruway. We found that increasing amounts of snow did cause more crashes. While traffic counts decreased, most of the decrease was in the number of passenger vehicles; commercial vehicle traffic was much less affected. Every 2.5 cm of snow costs the New York State Thruway approximately $1300 at each toll barrier and about $331 at each exit. These findings are helpful to law enforcement, emergency responders, and highway managers.

Assessing the effect of snowfall and cold temperature on a commuter highway traffic volume using several layers of statistical methods

Presented in this paper is an application of the parametric and non-parametric statistical modelling technique to assess and diagnosis the impact of snowfall and cold temperature on classified vehicle volume variations with five years of Weigh-in-Motion (WIM) data recorded at the commuter type highway nearby the City of Leduc in Alberta, Canada. The influence of the winter driving conditions on classified vehicle volumes travelling in mixed traffic stream is examined. The first phase involves developing parametric dummy-variable regression models to relate and then quantify the variations of daily traffic volumes associated with snowfall and temperature. The second phase involves utilizing a non-parametric Chi-square test combined with the Binomial and the Friedman test. Two levels of statistical tests commonly revealed that the total traffic and passenger car volumes are influenced by both snowfall and temperature, but the truck traffic volumes are not affected significantly. The results of this study may contribute to presenting a new statistical methodology for observing changes in highway traffic in winter. It can also provide important insights for highway agencies to develop efficient traffic monitoring programs throughout the year.

Characterizing the impact of snowfall on patient attendance at an urban emergency department in Toronto, Canada

ObjectivesWe sought to determine whether addition of a snowfall variable improves emergency department (ED) patient volume forecasting. Our secondary objective was to characterize the magnitude of effect of snowfall on ED volume. MethodsWe used daily historical patient volume data and local snowfall records from April 1st, 2011 to March 31st, 2018 (2542 days) to fit a series of four generalized linear models: a baseline model which included calendar variables and three different snowfall models with an indicator variable for either any snowfall (>0 cm), moderate snowfall (≥1 cm), or large snowfall (≥5 cm). To evaluate model fit, we examined the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Incident rate ratios were calculated to determine the effect of snowfall in each model. ResultsAll three snowfall models demonstrated improved model fit compared to the model without snowfall. The best fitting model included a binary variable for snowfall (<1 cm vs. ≥1 cm). This model showed a statistically significant decrease in daily ED volume of 2.65% (95% CI: 1.23%–4.00%) on snowfall days. DiscussionThe addition of a snowfall variable results in improved model performance in short-term ED volume forecasting. Snowfall is associated with a modest, but statistically significant reduction in ED volume.

LO75: The impact of snowfall on patient attendance at an urban academic emergency department

Introduction: Accurate forecasting of emergency department (ED) patient visits can inform better resource matching. Calendar variables such as day of week and time of day are routinely used as predictors of ED volume. Further improvement in forecasting will likely come from dynamic variables. The effect of snowfall on ED volumes in colder climates remains poorly understood. We sought to determine whether accounting for snowfall improves ED patient volume forecasting. Our secondary objective was to characterize the magnitude of effect of snowfall on ED volume. Methods: This was a retrospective observational study using historical patient volume data and local snowfall records from April 1st, 2011 to March 31st, 2018 (2,542 days) at a single urban ED. We fit a series of four generalized linear models: a baseline model which included calendar variables and three different snowfall models which contained the variables in the baseline model plus an indicator variable for modelling snowfall. Each snowfall model had a different daily threshold for its indicator variable: any snowfall ( &amp;gt;0cm), moderate snowfall ( &amp;gt; = 1 cm), or high snowfall ( &amp;gt; = 5 cm). We modeled daily ED volume as the dependent variable using a Poisson distribution. To evaluate model fit, we examined the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) in each of the four models. In both cases, a lower number indicates better model fit. Incident rate ratios were calculated to determine the effect of snowfall. We used the delta method to calculate confidence intervals. Results: A total of 2542 days were used to develop the model. All three snowfall models demonstrated improved model fit compared to the baseline model with lower AIC and BIC values. The best fitting model included a binary variable for moderate snowfall ( &amp;gt; = 1cm/day). This model showed a statistically significant decrease in ED volume of 2.65% (95% CI: 1.23% -4.00%) on snowfall days, representing 5.4 (95% CI: 2.5 -8.2) patients per day at our hospital with an average daily volume of 205 patients. Conclusion: The addition of a snowfall variable results in improved forecasting model performance in ED volume forecasting with optimal threshold set at 1 cm of snow in our setting. Snowfall is associated with a modest, but statistically significant reduction in ED volume.

Impact of Snowfall and Road Structure on Travel Speedin Winter in Niigataprefecture, Japan

Impact of Snowfall and Road Structure on Travel Speedin Winter in Niigataprefecture, Japan

Temperature and Snowfall in Western Queen Maud Land Increasing Faster Than Climate Model Projections

AbstractEast Antarctic Ice Sheet (EAIS) mass balance is largely driven by snowfall. Recently, increased snowfall in Queen Maud Land led to years of EAIS mass gain. It is difficult to determine whether these years of enhanced snowfall are anomalous or part of a longer‐term trend, reducing our ability to assess the mitigating impact of snowfall on sea level rise. We determine that the recent snowfall increases in western Queen Maud Land (QML) are part of a long‐term trend (+5.2 ± 3.7% decade−1) and are unprecedented over the past two millennia. Warming between 1998 and 2016 is significant and rapid (+1.1 ± 0.7°C decade−1). Using these observations, we determine that the current accumulation and temperature increases in QML from an ensemble of global climate simulations are too low, which suggests that projections of the QML contribution to sea level rise are potentially overestimated with a reduced mitigating impact of enhanced snowfall in a warming world.

Uncertainties of ground-based microwave radiometer retrievals in zenith and off-zenith observations under snow conditions

Abstract. This paper is to investigate the uncertainties of microwave radiometer (MWR) retrievals in snow conditions and also explore the discrepancies of MWR retrievals in zenith and off-zenith observations. The MWR retrievals were averaged in a ±15 min period centered at sounding times of 00:00 and 12:00 UTC and compared with radiosonde observations (RAOBs). In general, the MWR retrievals have a better correlation with RAOB profiles in off-zenith observations than in zenith observations, and the biases (MWR observations minus RAOBs) and root mean square errors (RMSEs) between MWR and RAOB are also clearly reduced in off-zenith observations. The biases of temperature, relative humidity, and vapor density decrease from 4.6 K, 9 %, and 1.43 g m−3 in zenith observations to −0.6 K, −2 %, and 0.10 g m−3 in off-zenith observations, respectively. The discrepancies between MWR retrievals and RAOB profiles by altitude present the same situation. Cases studies show that the impact of snow on accuracies of MWR retrievals is more serious in heavy snowfall than in light snowfall, but off-zenith observation can mitigate the impact of snowfall. The MWR measurements become less accurate in snowfall mainly due to the retrieval algorithm, which does not consider the effect of snow, and the accumulated snow on the top of the radome increases the signal noise of MWR measurements. As the snowfall drops away by gravity on the sides of the radome, the off-zenith observations are more representative of the atmospheric conditions for RAOBs.

Temporal and spatial features and inter‐annual variability of wintertime snow mass balance over China

ABSTRACTUsing observational data for 1979–2010, the temporal and spatial variations of wintertime (December–February) snow water equivalent (SWE) over China and their relations to the November SWE, wintertime snowfall, snow evaporation, sublimation and melting are investigated. The results revealed that the SWE is principally distributed in four snow regions of northwestern (NW) China, northeastern (NE) China, the Tibetan Plateau (TP) and the Yangtze–Huaihe River valley (YH). It is found that the impact of the November SWE is confined to the north of 42°N, while the impact of snowfall are relevant over all China, and the impacts of snow evaporation and sublimation are limited to NW, NE and the TP. The effect of snow melting is large in the YH but weak in other regions. On the inter‐annual timescale, the snow mass balance shows different features in different snow regions. The wintertime SWE is in line with snowfall. The November SWE has a major effect on the wintertime SWE in NW and NE but not in the TP and YH. The effect of meteorological factors on snow evaporation, sublimation and melting differs in different snow regions. Evaporation is mainly affected by vapour pressure deficit in NW and wind speeds in NE and the TP. Sublimation is controlled by air temperature in NW, wind speeds in NE, vapour pressure deficit in YH and air temperature, pressure and vapour pressure deficit in the TP. Melting is closely related with air temperature in the TP and net radiation in the YH.

Snowfall time-series reconstruction in Italy over the last 300 years

Snow events are not a rare episode in Mediterranean area, especially in northern and hilly areas of Italy. However, snowfall occurring quasi-simultaneously in the whole peninsula is extraordinary. This study collects, reconstructs, and analyzes the extraordinary snowfall episodes that occurred simultaneously in the whole Italian peninsula since 1709. This is the longest snowfall time series in the central Mediterranean area. The data, obtained by several documentary sources (from ancient archival to online databases), have been analyzed using different statistical tests, in order to explore normality, homogeneity, and stationarity. The results are characterized by a time-series stationarity with a quasi 60- and 100-year-dominant oscillation. No clear trend in the snowfall episode records is found. The 60-year cycle roughly matches with global-scale oscillations linked to natural forces, such as the Atlantic Multidecadal Oscillation and the winter North Atlantic Oscillation. Particular attention was directed to analyze the impact of snowfall on pre-industrial society, underlining the differences among northern and central regions, where snow was a more usual phenomenon, and its impact was mainly on transports of supplies or exceptionally on buildings, and southern regions, where it had a stronger impact also on orchards and cattle.

Multiple hydroclimatic controls over recent sedimentation in proglacial Mirror Lake, southern Selwyn Mountains, Northwest Territories

Varves from Mirror Lake, Northwest Territories (62°N, 128°W) reveal significant, but changing climatic influences on discharge and sedimentation on a decadal scale during the late 20th century. The complex hydroclimatic signal within the sediments indicates the difficulty in identifying a quantitative relationship between varve thickness and a single climatic variable. Regression of recent varve thickness with local meteorological data shows July temperature as the dominant control over sediment accumulation. In contrast, the dampening effects of increased snowfall on glacier ablation and resultant runoff reduce sediment delivery. Although the impact of snowfall does not appear to significantly weaken the relationship between summer temperature and varve formation, periods when multiple climatic factors control sediment delivery are characterized by distinctive varves containing two prominent silt units. Thus, the Mirror Lake hydrological system appears to shift between two general states. The first state involves a pronounced summer glacial meltwater phase due to dominant summer temperature influences on glacial melt, resulting in varves with one silt unit. This varve structure dominates the sedimentary record from A.D. 1670 to 1941, possibly reflecting a Little Ice Age influence in the study area. The second state operates in years when glacial meltwater discharge is delayed until August, due to increased snow cover, and the lake receives increased sediment-poor nival melt. These conditions lead to the formation of varves with two silt units corresponding to nival and glacial discharge phases and are common in the sedimentary record from A.D. 1390 to 1669 and A.D. 1942 to 1996.

建築環境工学の視点からみた克雪住宅の評価の試み

This paper describes the problems related to snow for houses from the point of view of the building environmental engineering. So far, the researchers of building environmental engineering have been investigating the problems of low room temperature and vapor condensation for the residential buildings in Tohoku district. However, the problems related to snow should also be dealt with by the researchers in this field. In the areas of heavy snowfall, the snow accumulation on the roof and around the buildings causes many problems for indoor and outdoor environment. In many cases, these problems are linked with the treatment of the accumulated snow on the roof. There are many ways developed for disposition of accumulated snow on the roofs.This paper, mainly dealing with the snow problems in Tohoku District, clarifies the impact of snowfall and its accumulation on the living environment. Secondly, various ways adopted for avoiding the snow related to problems are evaluated. Lastly, houses featured by the treatment of accumulated snow on the roof are assessed from the aspects of merits and demerits, and the conditions for their application are discussed.