Change in fresh snow density in Tianshan Mountains,China

The fresh snow density was observed with snow analyzer (Snow Fork) at Tianshan Station for Snowcover and Avalanche Research, Chinese Academy of Sciences from February 21 to March 5, 2009. Results show that fresh snow density increases from the 5th h to the 291st h after the snowfall, with an average rate of increase of 4.0×10-4 g/(cm3·h) (R2 = 0.943). Analysis shows that fresh snow density is negatively correlated with the compac-tion rate of fresh snow (R2 = -0.960). Inversely, it is positively correlated ...     

The influence of seasonal snow on soil thermal and water dynamics under different vegetation covers in a permafrost region

Seasonal snow is one of the most important influences on the development and distribution of permafrost and the hydrothermal regime in surface soil. Alpine meadow, which constitutes the main land type in permafrost regions of the Qinghai-Tibet Plateau, was selected to study the influence of seasonal snow on the temperature and moisture in active soil layers under different vegetation coverage. Monitoring sites for soil moisture and temperature were constructed to observe the hydrothermal processes in active soil layers under different vegetation cover with seasonal snow cover variation for three years from 2010 to 2012. Differences in soil temperature and moisture in areas of diverse vegetation coverage with varying levels of snow cover were analyzed using active soil layer water and temperature indices. The results indicated that snow cover greatly influenced the hydrothermal dynamics of the active soil layer in alpine meadows. In the snow manipulation experiment with a snow depth greater than 15 cm, the snow cover postponed both the freeze-fall and thawrise onset times of soil temperature and moisture in alpine LC （lower vegetation coverage） meadows and of soil moisture in alpine HC （higher vegetation coverage） meadows; however, the opposite response occurred for soil temperatures of alpine HC meadows,where the entire melting period was extended by advancing the thaw-rise and delaying the freeze-fall onset time of the soil temperature. Snow cover resulted in a decreased amplitude and rate of variation in soil temperature, for both alpine HC meadows and alpine LC meadows, whereas the distinct influence of snow cover on the amplitude and rate of soil moisture variation occurred at different soil layers with different vegetation coverages. Snow cover increased the soil moisture of alpine grasslands during thawing periods. The results confirmed that the annual hydrothermal dynamics of active layers in permafrost were subject to the synergistic actions of both snow cover and vegetation coverage.     

Numerical simulation of seasonal snow in Tianshan Mountains

Snowfall in the Tianshan Mountains in China is frequent during winter;thus,avalanches have become a severe issue in snow-covered areas.Accumulation and metamorphosis,as well as hydrothermal exchanges with the environment,considerably affect the stability of snow on slopes.Therefore,a hydrothermal model of snow cover and its underlying surfaces must be developed on the basis of meteorological data to predict and help manage avalanches.This study adopted the conceptual model of snow as a porous medium and quantitatively analysed its internal physical processes on the basis of the thermal exchanges amongst its components.The effects of local meteorological factors on snow structure and the redistribution of energy and mass inside the snow cover in the Tianshan Mountains were simulated.Simulation results showed that deformation as a result of overlying snow and sublimation of snow cover at the bottom is the main cause of density variation in the vertical profile of snow cover.Temperature drives water movement in snow.The low-density area of the bottom snow is the result of temperature gradient.The simulation results of the long-term snow internal mass distribution obtained by the method established in this study are highly consistent with the actual observed trend of variation.Such consistency indicates an accurate simulation of the physical characteristics of snow cover in small and microscale metamorphism in the Tianshan Mountains during the stable period.     

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.     

Metamorphism and microstructure of seasonal snow: Single layer tracking in Western Tianshan,China

Snowpack is a combination of several snow layers. Accordingly, snowpack natural metamorphism is composed of several stages. The aim of this study is to investigate the natural snow metamorphism at the snow layer unit. The field investigation was conducted at the Tianshan Station for Snow Cover and Avalanche Research, Chinese Academy of Sciences(43°16' N, 84°24' E, and 1,776 m a.s.l.), during the winter of 2010-2011. A complete metamorphic procedure and the corresponding microstructure of a target snow layer were tracked. The results indicate that: the ideal and complete metamorphic process and the corresponding predominant snow grain shape have 5 stages: 1) unstable kinetic metamorphism near the surface; 2) unstable kinetic metamorphism under pressure; 3) stable kinetic metamorphism; 4) equilibrium metamorphism; 5) wet snow metamorphism. Snow grain size sharply decreased in the surface stage, and then changed to continuously increase. Rapid increase of grain size occurred in the stable kinetic metamorphism and wet snow metamorphism stage. The characteristic length was introduced to represent the real sizes of depth hoar crystals. The snow grain circularity ratio had a variation of "rapid increase–slow decrease–slow increase", and the snow aggregations continuously increased with time. Snow density grew stepwise and remained steady from the stable kinetic to the equilibrium metamorphism stage. The differences in metamorphism extent and stages among snow layers, led to the characteristic layered structure of snowpack.     

Snow water content estimation from measured snow temperature

The vertical temperature profiles of snow and sea ice have been measured in the Arctic during the 2nd Chinese National Arctic Research Expedition in 2003(CHINARE2003).The high-resolution temperature profile in snow is solved by one-dimensional heat transfer equation.The effective heat diffusivity,internal heat sources are identified.The internal heat source refers to the penetrated solar radiation which usually warms the lower part of the snow layer in summer.By temperature gradient analysis,the zero level can be clarified quantitatively as the boundary of the dry and wet snow.According to the in situ time series of vertical temperature profile,the time series of water content in snow is obtained based on an evaluation method of snow water content associated with the snow and ice physical parameters.The relationship of snow water content and snow temperature and temporal-spatial distribution of snow water content are presented     

Using very long-range terrestrial laser 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 hillslope characterized 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 the snowpack, even in different years. The spatial patterns were particularly similar amongst the surveys 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 patterns can be easily identified through several years of adequate monitoring.     

Densification and grain coarsening of melting snow

1　IntroductionSnowdensificationiscriticalforcalculationsinengineering glaciology,snowavalancheforecasting ,springflooding,andotherpracticalaspects.Itisalsoimportantforinterpretingicecoredataincludingthosetakenfromratherwarmsiteswheresurfacelay ersexperiencemelting ,sinceitwouldaffectthechangeofannuallayerthicknesswithtime.Whileextensivestudies(e.g .AndersonandBenson 1 963 ;Bader1 960 ,1 962 ;Koji ma 1 95 4,1 95 5 ,1 95 6,1 95 7,1 95 8,1 95 9,1 964;Keeler 1 967;Gow 1 975 ;MaenoandE binuma 1…     

NORMALIZED DIFFERENCE SNOW INDEX SIMULATION FOR SNOW-COVER MAPPING IN FOREST BY GEOSAIL MODEL

1INTRODUCTION Snow is an important component of the Earth's surface. Up to 50×106km2(34%) ofthe Earth's land surface is sea- sonally snow-covered (VIKHAMAR and SOLBERG, 2002).Comparedtootherlandcovers,snowcoverextent varies dramatically on very short time scales (hours- months). Its presence affects physical, chemical and bio- logical processes at many spatial scales and has impor- tant social impacts. At the global scale, its high albedo strongly influences the Earth's radiation …     

Chemical characteristics and environmental significance of fresh snow deposition on Urumqi Glacier No. 1 of Tianshan Mountains, China

Ice and snow chemistry of alpine glaciers is crucial for the research of regional atmospheric environment change. Fresh snow samples were weekly collected from Urumqi Glacier No.1 in the Tianshan Mountains, Xin- jiang, China, and the chemical characteristics and seasonal variations of major ions, mineral dust, δ18O and trace metals were measured. Results show that the concentrations of major ions in the snow are Ca2+ SO42- NH4+ NO3- Cl- Na+ Mg2+ K+, in which Ca2+ is the dominant cation, and SO42-is the dominant anion. All major ions have close positive correlations with each other except NO3-. δ18O shows positive correlation with air temperature change during the study period. Mineral dust particle and major ionic concentrations in fresh snow have obvious seasonal change, with high concentration in spring but low concentration in summer and autumn, which indicates that the chemical mass input from Asian dust activity to snow is very significant. Temporal changes of trace metals in fresh snow, e.g., Cd, Pb, Zn, Al, Fe, have shown that human-induced pollution of central Asian region also has large contribution to the snow chemistry on alpine glaciers of the Tianshan Mountains.     

Physico-chemical characteristics and environmental significance of snow deposition on Haxilegen glacier No.51 in Tian Shan, China

Snow chemistry on the glaciers of alpine regions is a good indicator of atmospheric environmental change.We examine snow chemistry in three snowpits at different altitudes on the Haxilegen Glacier No.51,in the Kuitun River source,Tian Shan,China,during July-September 2004 to 2007.We use correlation analysis,factor analysis and sea-salt tracing methods to examine the characteristics and sources of major ions and mineral dust particles in the snow.Results show that mineral dust particles and major ions in the snow pits vary seasonally.During the Asian dust period in springtime,the concentration of mineral dust particles and major ions deposited in snow is high,while the concentration is relatively low during the non-dust period of summer and autumn.This may be caused by dust storm activity in central Asia.The order of major ionic concentrations in the snow packs was determined to be Ca2+ > SO42-> NH4+ > NO3-> Cl-> Na+ > Mg2+ > K+.Ca2+ was the dominant cation;SO42- was the dominant anion.We find,with the exception of NO3-,that the variabilities of ionic concentrations are highly correlated.Results show that the glacier region was significantly affected by dust activity and anthropogenic source.The major ions,especially Na+,originate from dust sources of central Asia and from the Ocean,transported by the westerly winds.     

Snow cover influences the thermal regime of active layer in Urumqi River Source,Tianshan Mountains,China

Snow cover is characterized by the high albedo, low thermal conductivity, and notable heat transition during phase changes. Thus, snow cover significantly affects the ground thermal regime. A comparison of the snow cover in high latitudes or high-altitude snowy mountain regions indicates that the eastern Tianshan Mountains (China) show a characteristically thin snow cover (snow depth below 15 cm) with remarkable temporal variability. Based on snow depth, heat flux, and ground temperature from 2014 to 2015 in the Urumqi River source, the spatialtemporal characteristics of snow cover and snow cover influences on the thermal conditions of active layer in the permafrost area were analyzed. During the autumn (Sept. - Oct.), thin and discontinuous snow cover can noticeably accelerate the exothermic process of the ground, producing a cooling effect on the shallow soil. During the winter (Nov. - Mar.), it is inferred that the effective thermal insulation starts with snow depth exceeding 10 cm during early winter. However, the snow depth in this area is generally below 15 cm, and the resulting snow-induced thermal insulation during the winter is very limited. Due to common heavy snowfalls in the spring (Apr. to May), the monthly mean snow thickness in April reached to 15 cm and remained until mid-May. Snow cover during the spring significantly retarded the ground warming. Broadly, snow cover in the study area exerts a cooling effect on the active layer and plays a positive role in the development and preservation of permafrost.     

FRESH SNOW CHEMISTRY FROM HIGH MOUNTAIN REGIONS IN CENTRAL HIMALAYAS

Investigations of atmospheric composition in the Himalayas has been limited in both temporal and spatial scales, mainly due to difficult logistics. Ideal sites for monitoring atmospheric composition and its evolution should be free from local pollution and representative of the remote troposphere (HUEBERT et al., 1980). As the Himalayas are far removed from highly industrialized regions they provide suitable locations to monitor the chemistry of the remote troposphere and to study the evolu…     

Dry/wet snow mapping based on the synergistic use of dual polarimetric SAR and multispectral data

We propose a multi-sensor multi-spectral and bi-temporal dual-polarimetric Synthetic Aperture Radar(SAR) data integration scheme for dry/wet snow mapping using Sentinel-2 and Sentinel-1 data which are freely available to the research community. The integration is carried out by incorporating the information retrieved from ratio images of the conventional method for wet snow mapping and the multispectral data in two different frameworks. Firstly, a simple differencing scheme is employed for dry/wet snow mapping, where the snow cover area is derived using the Normalized Differenced Snow Index(NDSI). In the second framework, the ratio images are stacked with the multispectral bands and this stack is used for supervised and unsupervised classification using support vector machines for dry/wet snow mapping. We also investigate the potential of a state of the art backscatter model for the identification of dry/wet snow using Sentinel-1 data. The results are validated using a reference map derived from RADARSAT-2 full polarimetric SAR data. A good agreement was observed between the results and the reference data with an overall accuracy greater than 0.78 for the different blending techniques examined. For all the proposed frameworks, the wet snow was better identified. The coefficient of determination between the snow wetness derived from the backscatter model and the reference based on RADARSAT-2 data was observed to be 0.58 with a significantly higher root mean square error of 1.03 % by volume.     

Impacts of snow accumulation on air temperature measured by automatic weather stations on the Antarctic ice sheet

The heights of automatic weather station (AWS) sensors over the Antarctic ice sheet are nominal and change with snow accumulation or ablation. Therefore, the measured data may not be used directly. In this study, we analyzed the impact of snow accumulation on AWS observations using continuous measurements from three AWS that were deployed on the traverse route from the Zhongshan Station to Dome A over East Antarctica. We then corrected the measured air temperature to account for changes in the sensor height relative to the snow surface to improve the authenticity and representativeness of the observation data from the AWS. The results show that (i) the annual mean snow accumulations at Dome A, Eagle and LGB69 were approximately 0.11 m, 0.30 m and 0.49 m, respectively, and the corresponding annual mean air temperature differences between the corrected and measured values at 1 m in height were 0.34℃, 0.29℃ and 0.35℃; (ii) the impact on air temperature from accumulation decreases with height from the surface; (iii) the air temperature difference between the corrected and measured values was not directly proportional to the snow accumulation but was related to the seasonal air temperature variations and the intensity of the local surface inversion; and (iv) the averaged corrected air temperature was higher than the measured values except during the summer when there were days without temperature inversion. The magnitude of the temperature difference between the corrected and measured was mainly determined by snow accumulation and the intensity of the local surface inversion.     

基于动态NDSI阈值的每日积雪监测方法

准确掌握积雪覆盖信息对于气象、水文和全球气候变化研究都具有重要的意义。遥感技术在进行大范围、高频率的积雪覆盖监测中发挥着重要的作用。目前,SNOMAP算法是用于积雪遥感监测最普遍的技术手段,其核心是利用固定阈值的归一化差分积雪指数（Normalized Difference Snow Index,NDSI）进行积雪识别,但这种方法忽略了积雪光谱信息的时相变化,会产生积雪监测的误差。本文提出了一种动态NDSI阈值方法,以纯永久积雪像元的平均NDSI值作为参照系调整固定的NDSI阈值,从而削减影像光谱值波动对积雪识别的影响。以三江源地区作为研究区域,将基于每日MODIS数据进行积雪监测最佳的NDSI阈值与同日纯永久积雪像元的平均NDSI值作线性回归,通过每日纯永久积雪像元平均NDSI值的变化来调整用于积雪识别的NDSI阈值。结果表明：① 基于每日MODIS数据进行积雪覆盖监测最佳的NDSI阈值与同日纯永久积雪像元的平均NDSI值之间存在较好的线性关系,决定系数R ²达到0.86;② 三江源地区动态NDSI阈值的范围为0.29~0.37,其平均值在0.33左右,说明MODIS全球积雪面积产品中将NDSI阈值取为0.40会低估三江源地区的积雪面积;③ 与采用固定NDSI阈值0.33的监测方法相比,动态NDSI阈值法近似率、总体分类精度和F值的平均值分别提高了5.17%、0.70%、1.14%。     

Observations and modeling of incoming longwave radiation to snow beneath forest canopies in the west Tianshan Mountains,China

Forest canopy reduces shortwave radiation and increases the incoming longwave radiation to snowpacks beneath forest canopies. Furthermore, the effect of forest canopy may be changed by complex topography. In this paper, we measured and simulated the incoming longwave radiation to snow beneath forest at different canopy openness in the west Tianshan Mountains, China(43°16'N, 84°24'E) during spring 2013. A sensitivity study was conducted to explore the way that terrain influenced the incoming longwave radiation to snow beneath forest canopies. In the simulation model, measurement datasets, including air temperature, incoming shortwave radiation above canopy, and longwave radiation enhanced by adjacent terrain, were applied to calculate the incoming longwave radiation to snow beneath forest canopy. The simulation results were consistent with the measurements on hourly scale and daily scale. The effect of longwave radiation enhanced by terrain was important than that of shortwave radiation above forest canopy with different openness except the 20% canopy openness. The longwave radiation enhanced due to adjacent terrain increases with the slope increase and temperature rise. When air temperature(or slope) is relatively low, thelongwave radiation enhanced by adjacent terrain is not sensitive to slope(or air temperature), but the sensitivity increases with the decrease of snow cover area on sunny slope. The effect of longwave radiation is especially sensitive when the snow cover on sunny slope melts completely. The effect of incoming shortwave radiation reflected by adjacent terrain on incoming longwave radiation to snow beneath forest canopies is more slight than that of the enhanced longwave radiation.     

一种考虑雪粒径变化的积雪面积反演算法

光谱混合分析能够提取亚像元信息,被广泛地应用于遥感影像目标探测之中。本文针对MODIS积雪遥感影像,基于光谱混合分析框架,利用渐进辐射传输模型建立不同粒径大小的雪反射率光谱库,提出了一种考虑端元变化及二次辐射的雪盖面积反演算法。此算法首先利用渐进辐射传输模型建立不同粒径大小积雪的反射率光谱库,然后使用序贯最大角凸锥方法获取植被、土壤与岩石、阴影的光谱库。在建立各种地物反射率光谱库之后,利用均方根误差最小的方法获取最优端元组合。在此基础上,考虑端元独立辐射以及积雪与其它地物的二次辐射过程,利用稀疏光谱混合模型获取积雪面积与雪粒径大小。实验结果表明：此方法能够同时反演雪粒径与积雪面积,反演的雪粒径相比单波段的渐进辐射传输模型小,反演的积雪面积相比MOD10A1产品精度略微提高。     

东北典型林区雪深反演算法的验证与分析

积雪对自然环境和人类活动都有极其重要的影响。积雪参数（雪面积、雪深和雪水当量）反演对水文模型和气候变化研究有着实际的意义。然而,目前森林区的雪深遥感反演精度一直有待于进一步提高。东北地区是我国最大的天然林区和重要的季节性积雪区之一,本文利用FY3B卫星微波成像仪（MWRI）L1级亮温数据和L2级雪水当量数据,以及东北典型林区野外实测雪深数据,对Chang算法、NASA 96算法和FY3B雪深业务化反演算法进行了验证与分析。结果表明：在东北典型林区的雪深反演中,Chang算法和NASA 96算法反演的雪深波动都比较大,当森林覆盖度f≤0.6时,NASA 96算法表现比较好,均方根误差值在3种算法中较小,但当f >0.6时,NASA 96算法失真严重。当考虑纯森林像元（f=1）时,Chang算法低估了雪深47%。当f≤0.3时,FY3B业务化算法始终优于Chang算法。整体上,FY3B业务化算法相对稳定,具有较高的精度。     

Response of snow hydrological processes to a changing climate during 1961 to 2016 in the headwater of Irtysh River Basin,Chinese Altai Mountains

With changing climatic conditions and snow cover regime, regional hydrological cycle for a snowy basin will change and further available surface water resources will be redistributed. Assessing snow meltwater effect on runoff is the key to water safety, under climate warming and fast social-economic developing status. In this study, stable isotopic technology was utilized to analyze the snow meltwater effect on regional hydrological processes, and to declare the response of snow hydrology to climate change and snow cover regime, together with longterm meteorological and hydrological observations, in the headwater of Irtysh River, Chinese Altai Mountains during 1961-2015. The average δ~(18) O values of rainfall, snowfall, meltwater, groundwater and river water for 2014–2015 hydrological year were-10.9‰,-22.3‰,-21.7‰,-15.7‰ and-16.0‰, respectively.The results from stable isotopes, snow melting observation and remote sensing indicated that the meltwater effect on hydrological processes in Kayiertesi River Basin mainly occurred during snowmelt supplying period from April to June. The contribution of meltwater to runoff reached 58.1% during this period, but rainfall, meltwater and groundwater supplied 49.1%, 36.9% and 14.0% of water resource to annual runoff, respectively. With rising air temperature and increasing snowfall in cold season, the snow water equivalent(SWE) had an increasing trend but the snow cover duration declined by about one month including 13-day delay of the first day and 17-day advancement of the end day during 1961–2016. Increase in SWE provided more available water resource. However, variations in snow cover timing had resulted in redistribution of surface water resource, represented by an increase of discharge percentage in April and May, and a decline in Juneand July. This trend of snow hydrology will render a deficit of water resource in June and July when the water resource demand is high for agricultural irrigation and industrial manufacture.