Spatiotemporal distributions and influences on snow density in China from 1999 to 2008

Ground snow observation data from 1999 to 2008 were used to analyze the temporal and spatial distribution of snow density in China. The monthly maximum density shifted from north to south during the period from October to the following January, and then moved back from south to north during the period from January to April. The maximum snow density occurred at the border between Hunan and Jiangxi provinces in January, where snow cover duration was short and varied remarkably. Snow density in Northeast China and the Xinjiang Uygur Autonomous Region were also high and showed less variation when the snow cover duration was long. Ground observation data from nine weather stations were selected to study changes of snow density in Northeast and Northwest China. A phase of stable snow density occurred from the middle ten days of November to the following February; non-stationary density phases were observed from October to the first ten days of November and from March to April. To further investigate the effects of climatic factors on snow density, correlations between snow density and precipitation, air temperature, snow depth and wind velocity for Northeast and Northwest China were analyzed. Correlation analysis showed that snow depth was the primary influence on snow density.

Spatial distribution of snow depth based on geographically weighted regression kriging in the Bayanbulak Basin of the Tianshan Mountains, China

Snow depth is a general input variable in many models of agriculture,hydrology,climate and ecology.This study makes use of observational data of snow depth and explanatory variables to compare the accuracy and effect of geographically weighted regression kriging(GWRK)and regression kriging(RK)in a spatial interpolation of regional snow depth.The auxiliary variables are analyzed using correlation coefficients and the variance inflation factor(VIF).Three variables,Height,topographic ruggedness index(TRI),and land surface temperature(LST),are used as explanatory variables to establish a regression model for snow depth.The estimated spatial distribution of snow depth in the Bayanbulak Basin of the Tianshan Mountains in China with a spatial resolution of 1 km is obtained.The results indicate that 1)the result of GWRK's accuracy is slightly higher than that of RK(R^2=0.55 vs.R^2=0.50,RMSE(root mean square error)=0.102 m vs.RMSE=0.077 m);2)for the subareas,GWRK and RK exhibit similar estimation results of snow depth.Areas in the Bayanbulak Basin with a snow depth greater than 0.15m are mainly distributed in an elevation range of 2632.00–3269.00 m and the snow in this area comprises 45.00–46.00% of the total amount of snow in this basin.However,the GWRK resulted in more detailed information on snow depth distribution than the RK.The final conclusion is that GWRK is better suited for estimating regional snow depth distribution.

Investigation of Spatial and Temporal Distribution of Snow Cover by Using Satellite Imagery (Case Study: Sheshpirdam Basin)

About one third of the water needed for agriculture in the world is generated by melting snow. Snow cover, surface and ground water recharge are considered as sustainable and renewable resources. It is therefore necessary to identify and study these criteria. The aim of this study is to determine the spatial and temporal distribution of snow cover in the district of the Sheshpir basin in Fars province (in south of Iran). Ground-based observation of snow covers, especially in mountainous areas, is associated with many problems due to the insufficient accuracy of optical observation, as opposed to digital observation. Therefore, GIS and remote sensing technology can be partially effective in solving this problem. Images of Landsat 5TM and Landsat 7TM satellites were used to derive snow cover maps. The images in ENVI 4.8 software were classified by using the maximum likelihood algorithm. Other spatial analyses were performed in ARC-GIS 9.3 software. The maximum likelihood method was accuracy assessed by operation points of testing. The least and the average of overall accuracy of produced maps were found to be 91% and 98%, respectively. This demonstrates that the maximum likelihood method has high performance in the classification of images. Overall snow cover and the review of terrain through the years 2008-2009 and 2009-2010 showed that snow cover begins to accumulate in November and reaches its highest magnitude in February. Finally, no trace of snow can be observed on the surface of the basin in the month of May. By average, 34% of the basin is covered in snow from November through to May.

Analysis of the characteristics of snow drop size distribution in the Qilian Mountains

Under the Watershed Allied Telemetry Experimental Research （WATER） project, a significant amount of snow size data was collected from March to April 2008. However, because of limited observation data for the Qinghai-Tibet Plateau, the modeling behavior was not satisfactory. This paper demonstrates characteristics of the snow drop size distribution （SSD） in this region. The experimental area is located in the northeastern part of the Qinghai-Tibet Plateau. The Heihe River Basin, which is the second largest interior river basin in China and is located on the northern slopes of the Qilian Mountains, was selected as the simulation region. This basin ranges from approximately 5,000 m to 1,000 m in elevation. A new generation Parsivel disdrometer, the OTT Parsivel, was used for measurements. Four data sets were compiled to determine the average distributions for four different snowfall rates. The characteristics of the snow particle size distribution in the mountainous area were analyzed. Similar to the raindrop distribution, there was a multi-peak structure. Most peaks appear in the D 〈 2 mm region （D： diameter of the snow drop size）. An M-P distribution and a Г distribution were developed based on the precipitation data observed in Qilian mountainous area. We found that the Г distribution has a better fit than the M-P distribution for the actual distribution. In addition, we observed that the intercept parameter （N0） and the slope parameter （Λ） correlate well with the shape parameter （μ）. The disdrometer data can also be used to model the reflectivity factor （ZH） and differential reflectivity factor （ZDR）. The radar reflectivity （ZHH, ZVV） and differential reflectivity （ZDR） were modeled in order to facilitate understanding of the connections between radar and ground measurements, and were used to support work for the improvement of rainfall estimates by polarimetric radar. Rain rate estimation using radar measurements was based on empirical models, such as the Z-R relationship and R（ZH, ZDR） in the Qilian mountainous areas. The relationship of R=0.017×100.079×ZH-0.022×ZDR is better than R=0.019×100.078×ZH for estimating R （melted snow）. The normalized errors （NE） of R（ZH） and R（ZH, ZDR） are 13.22% and 5.20%, respectively.

Source and yearly distribution of PAHs in the snow from the Hailuogou glacier of Mountain Gongga, China

Snow samples were collected over a 3-year period from 2012 to 2014 at the Hailuogou glacier of Mountain Gongga(Mt. Gongga) and analyzed for 16 priority polycyclic aromatic hydrocarbons(PAHs) using Gas Chromatography–Mass Spectrometry(GC–MS). The results show that total average levels of the 16 PAHs ranged from 452 to 290 ng·L^(-1) with a possible declining trend from 2012 to 2014. Distances between the sampling sites and the emission sources were estimated at typically less than 500 km. The results suggest that the major source of PAHs was from coal combustion, while contributions from automobile exhaust played an important role in more recent years. This finding was in agreement with the characteristics of presence of local industry, residence, and recent development of tourism of the surrounding areas.

Usingvery long-range terrestriallaser scanner to analyze the temporal consistency of the snowpack distribution in a high mountain environment

This study demonstrated the usefulness of very long-range terrestrial laser scanning(TLS) for analysis of the spatial distribution of a snowpack, to distances up to 3000 m, one of the longest measurement range reported to date. Snow depth data were collected using a terrestrial laser scanner during 11 periods of snow accumulation and melting,over three snow seasons on a Pyrenean hillslopecharacterized by a large elevational gradient, steep slopes, and avalanche occurrence. The maximum and mean absolute snow depth error found was 0.5-0.6 and 0.2-0.3 m respectively, which may result problematic for areas with a shallow snowpack, but it is sufficiently accurate to determine snow distribution patterns in areas characterized by a thick snowpack. The results indicated that in most cases there was temporal consistency in the spatial distribution of thesnowpack, even in different years. The spatial patterns were particularly similar amongst thesurveys conducted during the period dominated by snow accumulation(generally until end of April), or amongst those conducted during the period dominated by melting processes(generally after mid of April or early May). Simple linear correlation analyses for the 11 survey dates, and the application of Random Forests analysis to two days representative of snow accumulation and melting periods indicated the importance of topography to the snow distribution. The results also highlight that elevation and the Topographic Position index(TPI) were the main variables explaining the snow distribution, especially during periods dominated by melting. The intra-and inter-annual spatial consistency of the snowpack distribution suggests that the geomorphological processes linked to presence/absence of snow cover act in a similar way in the long term, and that these spatial patternscan be easily identifiedthrough several years of adequate monitoring.

THERMAL PROPERTIES AND TEMPERATURE DISTRIBUTION OF SNOW/FIRN ON THE LAW DOWE ICE CAP, ANTARCTICA

Based on detailed measurements of density and a numerous data on temperature in shallow boreholes (about 20m deep), the thermal properties and temperature distribution of snow / firn layer on the Law Dome ice cap, Antarctica, are discussed. According to a review of works on thermal properties of snow by Yen (1981), a relationship between thermal conductivity (K) and density (ρ) is proposed to be expressed by a formula, K=0.0784+2.697/ρ2. Then an eqation of heat transfer in a deformed ununiform medium is applied and solved analytically by two approaches. Comparison of calculated and measured temperatures indicates that the difference is mainly dependent on the determination of boundary donditions.

Aerodynamic Behavior of Snowflakes on an Uneven Road Surface during a Snowstorm

The removal of snow from a road or railroad results in an uneven surface and thus the formation of snowdrifts. However, the effect of a surface bump on the scale of a snowdrift is not clear. Snowdrift wind tunnel tests have long been performed to predict the snow cover distribution due to a snowstorm. However, such tests require a large-scale experimental device, have high installation and maintenance costs, and are not easy to perform. The present study thus used a small water tunnel that is easier to implement. The snowdrift pattern for the real phenomenon of a cube model was reproduced using the small water tunnel and the performance of the tunnel thus verified. The snowdrift water tunnel was then used to predict the snowdrift distribution for uneven surfaces. The tunnel well reproduced the snow cover distribution when the sedimentation velocity ratio and Stokes number in the water tunnel test were the same as those for the real phenomenon, again verifying the performance of the water tunnel test.

Micro-particle in surface snow at Princess Elizabeth Land, East Antarctica

During the Austral summer of 1996/1997, the First Chinese Antarctic Inland Expedition reached the inland area about 330 km along the direction around 76°E from Zhongshan Station, and collected 84 surface snow samples at an interval of 4 km . Micro particle analysis of the samples indicates that the micro particle concentration apparently decreases with the increasing of altitude, and the amplitudes of micro particle concentration is much larger in the lower altitude than in the higher altitude. Further analysis of grain size distributions of micro particle, percentage of micro particles from different sources and variations with altitude suggest that micro particles in this area are from a considerably dominant source. Although this area is controlled by polar easterly wind and katabatic wind, transportation and deposition of the micro particles are mainly influenced by marine transportation in coastal area.

Effect of seasonal snow on the start of growing season of typical vegetation in Northern Hemisphere

Under global warming, seasonal snow takes faster melting rate than before, which greatly changes the hydro-logical cycle. In this study, by targeting three typical seasonal snow-covered land types (i.e., open shrubland,evergreen needleleaf forest and mixed forest) in the Northern Hemisphere, the start of growing season (SGS) hasbeen found obviously advanced in the past years, greatly contributed by the faster melting rate of seasonal snow.It is manifested that significantly positive correlation has been found between SGS and May snow depth for openshrubs, March and April snow depth for evergreen needleleaf forests and March snow depth for mixed forests.However, such close association is not appeared in all the climate conditions of same vegetation. In the future,as the rate of melting snow becomes faster in the high emission of greenhouse gasses than the current situation,continuously advanced SGS will accelerate the change of vegetation distribution in the Northern Hemisphere.These findings offer insights into understanding the effect from seasonal snow on vegetation and promote thesustainable utilization of regional vegetation in the Northern Hemisphere.

城市中压配电网雪花格式网架结构初探

为适应新型电力系统建设需求,提出一种适合国情的雪花格式网架结构。首先,总结国内外典型城市中压配电网结构的特征与优缺点;然后,结合天津已有网架结构,提出雪花格式网架结构及其构建方法;其次,分析测算雪花网结构的负荷转移能力、可靠性与效率效益水平;最后,从结构形式、适合场景等方面给出雪花网结构与花瓣结构等的综合对比情况。结果表明,雪花格式网架结构具有一定综合比较优势,可为中压配电网远景目标网架规划提供指导。

遗传神经网络下光伏功率高比例异常数据检测

在天气、设备以及多个因素的影响下,大部分光伏功率易出现异常。因此,该文提出基于遗传神经网络的光伏功率高比例异常数据检测方法。分析光伏功率高比例异常数据聚集特征,并利用遗传神经网络架构确定光伏发电条件概率分布。结合最小化估算区间原理,在确定高比例异常光伏概率分布情况下,估计光伏概率所在区间。利用遗传算法调整神经网络权值,确定神经细胞异常分数以及离群点异常分数平均值,从而判断当前数据是否为高比例异常数据,并得到光伏功率高比例异常数据检测结果。实验结果表明,该文方法能够有效检测出异常数据,误差小,实际应用效果好。

Vertical distribution of snow cover and its relation to temperature over the Manasi River Basin of Tianshan Mountains, Northwest China

How snow cover changes in response to climate change at different elevations within a mountainous basin is a less investigated question. In this study we focused on the vertical distribution of snow cover and its relation to elevation and temperature within different elevation zones of distinct climatology, taking the mountainous Manasi River Basin of Xinjiang, Northwest China as a case study. Data sources include MODIS 8-day snow product, MODIS land surface temperature(LST) data from 2001 to 2014, and in situ temperature data observed at three hydrological stations from 2001 to 2012. The results show that:(1) the vertical distribution of snow areal extent(SAE) is sensitive to elevation in low(<2100 m) and high altitude(>3200 m) regions and shows four different seasonal patterns, each pattern is well correspondent to the variation of temperature.(2) The correlation between vertical changes of the SAE and temperature is significant in all seasons except for winter.(3) The correlation between annual changes of the SAE and temperature decreases with increasing elevation, the negative correlation is significant in area below 4000 m.(4) The snow cover days(SCDs) and its long-term change show visible differences in different altitude range.(5) The long-term increasing trend of SCDs and decreasing trend of winter temperature have a strong vertical relation with elevation below 3600 m. The decreasing trend of SCDs is attributed to the increasing trend of summer temperature in the area above 3600 m.

基于Fluent软件的风向夹角对高速公路半路堑风吹雪影响研究

对高速公路两种半路堑路况进行Fluent数值模拟,分析风向夹角对半路堑积雪浓度的影响,得到半路堑积雪分布规律,为高速公路选线设计提供理论参考。结果表明:随风向夹角增大,背风半路堑积雪浓度整体为增加趋势,风向夹角为90°时积雪浓度最高,达到79.18 kg/m~3,形成严重的风积雪灾害;迎风半路堑整体浓度浮动趋势在5 kg/m~3以内,且积雪浓度在20 kg/m~3以下,不足以形成风积雪灾害。在风吹雪灾害频发地区进行高速公路选线设计时,应减小公路与主风向之间夹角,减少风吹雪灾害的发生。

持续时间下路堑内风致积雪数值模拟研究

路堑是风吹雪灾害最为严重的路基形式之一,为给实际道路断面设计和风吹雪灾害的防治提供参考依据,文中针对交通线路中常见的路堑展开研究,基于Fluent中的Mixture模型对风雪两相流进行模拟,同时对模拟结果进行验证。研究路堑风吹雪灾害中的积雪分布规律,并对积雪分布演化过程中的流场进行比较分析。结果发现路堑下风坡位置形成局部突出积雪与路堑内产生漩涡再附点有直接关系。不同时刻路堑内雪相浓度受积雪量增加和风速流场变化的影响,其值整体上增加,且雪相浓度最大值在上风坡坡顶附近出现,研究可为路堑内积雪灾害预测以及风吹雪两相流数值模拟参数取值提供参考。

路堑风吹雪灾害的形成和防治研究

风吹雪灾害是一种寒冷山区交通线路比较常见的自然灾害,现场调研发现路堑是风吹雪灾害最为严重的路基形式之一。本文针对路堑风吹雪灾害的形成和防治展开研究,基于Euler-Euler方法和Mixture模型模拟风雪两相流,同时利用现场实测数据验证模拟结果。研究典型路堑风吹雪灾害中风雪分布的演化过程,并比较分析不同形式路堑的风吹雪灾害特征,结果发现两侧边坡比小于1∶2的路堑风吹雪灾害最为严重。该类路堑严重的风雪灾害的形成原因是两侧边坡积雪的增加压缩了路面旋涡尺度,进而削弱了旋涡的回流加速作用。同时发现雪檐在推进到上风侧边坡中点前为安全储备期,此时上风侧边坡积雪量即为临界储雪量。

八车道高速公路风吹雪积雪分布特征及路堤高度相关性研究

为研究八车道高速公路风吹雪积雪分布特征以及路堤高度对风吹雪的影响。基于室外模型试验方法,研究不同路堤高度下路堤周围速度流场、积雪分布规律和演化过程;基于数值模拟试验方法,对不同路堤高度下周围速度流场变化进行研究,并与室外模型试验速度流场变化结果比较,验证数值模拟结果的准确性;基于路面积雪量和积雪深度评估不同路堤高度抵御灾雪能力。结果表明:当风吹雪运动到路堤时,受到路堤阻碍产生速度分区,分别形成气流减速区、气流加速区、气流高速区、气流涡流回旋区和气流恢复区,路堤背风侧气流减速区面积明显大于路堤迎风侧;在路堤路面处,气流速度先降低后升高且在路堤背风侧路肩达到最大。路堤积雪主要发生在迎风侧,路面上有较多积雪,背风侧积雪较少。路堤周围速度流场特性与路堤高度密切相关,气流流过路堤迎风侧与背风侧周围形成风速减弱区与路堤高度正相关。通过对比3种不同路堤高度路面积雪量,0.3 m高度路堤路面积雪量最大,路面积雪最深,风吹雪环境下最不利。因此,通过设置合理路堤高度,可以改善路堤周边风速流场并减弱风吹雪灾害,从而起到阻雪作用。

长江中下游地区雪和雨夹雪垂直热力特征的聚类分析

基于ERA5逐小时再分析资料和地面观测资料,对2019—2022年长江中下游地区雪和雨夹雪的垂直热力特征进行分析,并应用K-means聚类方法分型探讨其物理过程特征。结果表明:1)雪和雨夹雪的聚类均可分为“冷型”和“逆温型”两簇,“冷型”降雪、雨夹雪多数出现在28°N以北地区,江南地区以“逆温型”为主。2)通过湿球温度曲线的聚类分析可以较好地区分雪、雨夹雪相态,优于样本合成平均。3)大部分雪、雨夹雪的云顶温度都低于-10℃,且量级越大,云顶温度越低,“冷型”雪、雨夹雪云顶温度低于“逆温型”。4)“逆温型”雪和雨夹雪的降雪率高于对应的“冷型”样本,且“逆温型”南风、北风风速均强于“冷型”。5)“逆温型”雪和雨夹雪比“冷型”样本出现暖层比例高,且“冷型”样本暖层绝大部分都位于近地面层。

铁路站场风吹雪分布特征研究

风吹雪现象会影响铁路运输安全,积雪严重时阻断铁路交通。因此该论文基于建立的铁路站场和车辆的多相流仿真计算模型,对有无列车停站和不同股道数对风雪场分布特征的影响进行了分析。研究表明,站内无停车时,迎风侧路基区域的流速较低,而站内顺风向的流速逐渐增加,风速和积雪分布的变化趋势相对平缓;而在站内有停车时,列车上风侧存在一个长约8 m、高为2 m的流场减速区,下风侧存在一个长约5 m、高为0.5 m的流场加速区。列车上风侧近处和下风侧远处的雪量增加,上风侧远处和下风侧近处的雪量减少。同时,站场内的股道数也会影响风雪场分布,增加股道数时,站场内的雪量最小值和平均雪量减小,但雪量最大值较为接近且位置都在列车上风侧;站场内的流场变化是雪量分布差异的根本原因,股道数的增加减缓了站场结构对风吹雪的影响作用。

基于风云卫星遥感资料的中国青藏高原积雪分布研究

文章以中国青藏高原地区为研究区,通过对1990-2019年气象站实测雪深数据(简称“实测雪深”)和卫星遥感反演雪深数据(简称“遥感雪深”)互补应用,分析实测雪深与遥感雪深的差值情况,评估遥感雪深的精度;通过多种方法对遥感雪深进行订正,形成质量最优的长时间序列遥感雪深订正数据集;总结积雪的时空变化典型趋势和特征,揭示在全球气候变暖过程中,雪深对时间变化的响应,以期为青藏高原雪灾防御工作中对积雪资料的应用提供参考。