Metamorphism and Microstructure of Seasonal Snow:Single Layer Tracking in Western Tianshan,China

【Title】【Author】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.

Seasonal snow cover patterns explain alpine treeline elevation better than temperature at regional scale

Unprecedented modern rates of warming are expected to advance alpine treelines to higher elevations,but global evidence suggests that current treeline dynamics are influenced by a variety of factors.Seasonal snow cover has an essential impact on tree recruitment and growth in alpine regions,which may in turn influence current treeline elevation;however,little research has been conducted on its role in regional treeline formation.Based on 11,804treeline locations in the eastern Himalayas,we extracted elevation,climate,and topographic data for treeline and snowline.Specifically,we used linear and structural equation modelling to assess the relationship between these environmental factors and treeline elevation,and the climate-snow-treeline interaction mechanism.The results showed that the treeline elevation increased with summer temperature and permanent or seasonal snowline elevation,but decreased with snow cover days and spring temperature at the treeline positions(P<0.001).Importantly,spring snowline elevation(33.4%)and seasonal snow cover days(21.1%)contributed the most to treeline elevation,outperforming the permanent snowline,temperature,precipitation,and light.Our results support the assertion that the temperature-moisture interaction affects treeline elevation in the eastern Himalayas,but we also found that the effects were strongly mediated by seasonal snow cover patterns.The increasing tendency of snow cover governed by climate humidification observed in the eastern Himalayas,is likely to limit future treeline advancement and may even cause treeline decline due to the mortality of the remaining old trees.Together,our findings highlight the role of seasonal snow cover patterns in determining treeline elevation in the eastern Himalayas,which should be considered when assessing the potential for treeline ascent in snow-mediated alpine systems elsewhere.

Energy Budget over Seasonal Snow Surface at an Open Site and Beneath Forest Canopy Openness during the Snowmelt Period in Western Tianshan Mountains,China

In this study, meteorological factors and snowmelt rate at an open site on sunny slope(OPS) and beneath forest canopy openness on shady slope(BFC) were measured using an automatic weather station and snow lysimeter during the snowmelt period in 2009, 2010 and 2013. The energy budget over snow surface was calculated according to these meteorological datasets. The analysis results indicated that the net shortwave radiation(K) and sensible heat flux(H) were energy sources, and the latent heat flux(LVE) was energy sinks of snow surfaces at all sites. The net longwave radiation(L) was energy sink at OPS and 80% BFC, but energy source at 20% BFC. The gain of K, H, and the loss of LVE at BFC were obviously lower than those at OPS. The L was the maximum difference of energy budget between snow surface at BFC and OPS. In warm and wet years, the most important factor of the energy budget variation at OPS was air humidity and the second mostimportant factor was air temperature. However, the ground surface temperature on the sunny slope was the most important factor for L and energy budget at BFC. With the increases in forest canopy openness and the slope of adjacent terrains, the influences of ground surface temperature on the sunny slope on L and the energy budget over snow surface at BFC increased, especially when the snow cover on the sunny slope melts completely.

Characteristics of abrupt changes of snow cover and seasonal freeze-thaw layer in the Tibetan Plateau and their impacts on summer precipitation in China

In this paper, a variation series of snow cover and seasonal freeze-thaw layer from 1965 to 2004 on the Tibetan Plateau has been established by using the observation data from meteorological stations. The sliding T-test, M-K test and B-G algorithm are used to verify abrupt changes of snow cover and seasonal freeze-thaw layer in the Tibetan plateau. The results show that the snow cover has not undergone an abrupt change, but the seasonal freeze-thaw layer obviously witnessed a rapid degradation in 1987, with the frozen soil depth being reduced by about 15 cm. It is also found that when there ~s less snow in the plateau region, precipitation in South China and Southwest China increases. But when the frozen soil is deep, precipitation in most of China apparently decreases. Both snow cover and seasonal freeze-thaw layer on the plateau can be used to predict the summer precipitation in China. However, if the impacts of snow cover and seasonal freeze-thaw layer are used at the same time, the predictability of summer precipitation can be significantly improved. The significant correlation zone of snow is located in middle reaches of the Yangtze River covering the Hexi Corridor and northeastern Inner Mongolia, and the seasonal freeze-thaw layer exists in Mt. Nanling, northern Shannxi and northwestern part of North China. The significant correlation zone of simultaneous impacts of snow cover and seasonal freeze-thaw layer is larger than that of either snow cover or seasonal freeze-thaw layer. There are three significant correlation zones extending from north to south： the north zone spreads from Mr. Daxinganling to the Hexi Corridor, crossing northern Mt. Taihang and northern Shannxi; the central zone covers middle and lower reaches of the Yangtze River; and the south zone extends from Mt. Wuyi to Yunnan and Guizhou Plateau through Mt. Nanling.

Oceans, Ice &Snow and CO2 Rise, Swing and Seasonal Fluctuation

Carbon dioxide rise, swing and spread (seasonal fluctuations) are addressed in this study. Actual CO2 concentrations were used rather than dry values. The dry values are artificially higher because water vapor must be removed in order for the NDIR instrument to work and is not factored back into the reported numbers. Articles addressing these observations express opinions that are divergent and often conflicting. This investigation resolves many of those inconsistencies. The data were obtained from many measuring stations at various latitudes since 1972 and then graphical compared to changes in sea temperatures, fossil fuel emissions, humidity, and seasonal ice and snow changes. In analyzing the data, various parameters were addressed including: variability, R squared curve values, correlations between curves, residence times, absorption percentages, and Troposphere effects. Mass balance calculations were also made to corroborate viability. The CO2 “rise” over a 33-year period from a slight ocean temperature increase (0.7°F) contributed 2.3 percent of the total rise while fossil fuel emissions contributed 1.5 percent. The overwhelming majority (60 ppmv, 96%+) was caused by other factors including ocean and land biology as well potential errors in fundamental hypotheses. With respect to “spread” (seasonal CO2 fluctuations) at the Polar Circles, graphical analysis with high correlations supported by mass balance calculations confirm that ice and snow are the primary cause and explain why the concentrations are the highest at these cold locations. The global variations in “swing” remain uncertain.

Impacts of Snow Cover on Vegetation Phenology in the Arctic from Satellite Data

The dynamics of snow cover is considered an essential factor in phenological changes in Arctic tundra and other northern biomes. The Moderate Resolution Imaging Spectroradiometer （MOD1S）/Terra satellite data were selected to monitor the spatial and temporal heterogeneity of vegetation phenology and the timing of snow cover in western Arctic Russia （the Yamal Peninsula） during the period 2000 10. The magnitude of changes in vegetation phenology and the timing of snow cover were highly heterogeneous across latitudinal gradients and vegetation types in western Arctic Russia. There were identical latitudinal gradients for ＂start of season＂ （SOS） （r2 = 0.982, p〈0.0001）, ＂end of season＂ （EOS） （r2 = 0.938, p〈0.0001）, and ＂last day of snow cover＂ （LSC） （r2 = 0.984, p〈0.0001）, while slightly weaker relationships between latitudinal gradients and ＂first day of snow cover＂ （FSC） were observed （r2 = 0.48,p〈0.0042）. Delayed SOS and FSC, and advanced EOS and LSC were found in the south of the region, while there were completely different shifts in the north. SOS for the various land cover features responded to snow cover differently, while EOS among different vegetation types responded to snowfall almost the same. The timing of snow cover is likely a key driving factor behind the dynamics of vegetation phenology over the Arctic tundra. The present study suggests that snow cover urgently needs more attention to advance understanding of vegetation phenology in the future.

Nitrous oxide emissions following seasonal freeze-thaw events from arable soils in Northeast China

Seasonal soil freeze-thaw events may enhance soil nitrogen transformation and thus stimulate nitrous oxide （N2O） emissions in cold regions. However, the mechanisms of soil N2O emission during the freeze-thaw cycling in the field remain unclear. We evaluated N2O emissions and soil biotic and abiotic factors in maize and paddy fields over 20 months in Northeast China, and the structural equation model （SEM） was used to determine which factors affected N2O production during non-growing season. Our results verified that the seasonal freeze-thaw cycles mitigated the available soil nitrogen and carbon limitation during spring thawing period, but simultaneously increased the gaseous N2O-N losses at the annual time scale under field condition. The N2O-N cumulative losses during the non-growing season amounted to 0.71 and 0.55 kg N ha 1 for the paddy and maize fields, respectively, and contributed to 66 and 18% of the annual total. The highest emission rates （199.2- 257.4 μg m-2 h-1） were observed during soil thawing for both fields, but we did not observe an emission peak during soil freezing in early winter. Although the pulses of N2O emission in spring were short-lived （18 d）, it resulted in approximately 80% of the non-growing season N2O-N loss. The N2O burst during the spring thawing was triggered by the combined impact of high soil moisture, flush available nitrogen and carbon, and rapid recovery of microbial biomass. SEM analysis indicated that the soil moisture, available substrates including NH4＋ and dissolved organic carbon （DOC）, and microbial biomass nitrogen （MBN） explained 32, 36, 16 and 51% of the N2O flux variation, respectively, during the non-growing season. Our results suggested that N2O emission during the spring thawing make a vital contribution of the annual nitrogen budget, and the vast seasonally frozen and snow-covered croplands will have high potential to exert a positive feedback on climate change considering the sensitive response of nitrogen biogeochemical cycling to the freeze-thaw disturbance.

青藏高原雪盖次季节变率的季节进程

利用1998—2020年交互式多传感器雪冰制图系统雪盖资料、ERA-Interim再分析资料的近地层气温数据和美国气候预测中心提供的格点降水资料,研究了青藏高原雪盖次季节变率的变化特征及其与气温和降水的关系。结果表明:青藏高原积雪覆盖率随季节变化较为明显,冬季积雪覆盖率最高,春季、秋季次之,夏季最小;雪盖季节内变化进程为1月活跃区域达到最大,此后逐步缩小,夏季最小,春季、秋季为过渡季节;青藏高原平均气温年内差值约为20℃,1月平均气温最低,且呈现南高北低的分布特征;气温对于青藏高原雪盖分布的影响较大,气温变化标准差大的时期,雪盖次季节变率也对应较大,且在空间分布上两者也较为类似;降水对青藏高原雪盖次季节变化的影响较小,二者没有明显的相关关系。

新疆北部地区季节性积雪密度变化特征分析

选取新疆北部地区季节性积雪期的定点站和典型区域,应用北疆20个气象站点观测资料和使用便携式测雪仪(Snow Fork),在不同地域、不同雪层和不同时间进行观测与测量,并且在积雪稳定期中的一次降雪过程对新雪密度变化过程中影响它的诸多因子进行观测,对新疆北部地区冬季季节性积雪密度变化特征进行的观测和分析.结果表明:雪面辐射热量和雪层内温度梯度对积雪密度起主要作用,变化主要是通过雪层内深霜和粗粒雪层的温度减小而实现的;在隆冬期全层积雪密度最大的为深霜层,入春2月下旬回暖期以后,由于雪层含水率的增加,季节性积雪密度最大层则为粒雪层.

青藏高原积雪和季节冻融层的突变特征及其对中国降水的影响

利用青藏高原气象台站观测的积雪和冻土资料,建立了高原积雪和季节冻融层1965—2004年的变化序列,通过滑动T平均、M-K检验、动力学分割算法(BG算法)等方法检验出高原积雪没有发生明显的突变过程,而高原季节冻融层在1987年前后有一次明显的突变,冻结深度减少比较显著.当高原积雪偏少时,华南和西南降水偏多,而当高原冻结较厚时,全国的降水几乎都偏少.通过计算高原积雪和季节冻融层与全国夏季降水的单因子相关和复相关发现,积雪和季节性冻土对中国夏季降水都有一定的可预测性,但是如果共同考虑两个因子的影响,则能够提高夏季降水预测的准确率.考虑两个因子的共同影响,有3个明显的相关带,分别是北部沿大兴安岭经太行山北部到陕北最后到河西走廊,中部在长江中下游地区,南部则是沿武夷山经南岭到云贵高原中部.

积雪对冻土热状况的影响

研究表明季节性积雪对其下覆冻土的热状况有显著的影响．雪盖的存在不仅阻隔了冻土层的热能散失，从而有提高地温的作用；而且由于积雪本身所具有的低导热性和较大容积热容量等特性，延滞了外部气候条件对冻土热状况的影响．反映冻土热状况的一个重要指标──冻土深度的变化与气温．太阳辐射的变化密切相关，因此，地理位置和地形在地─气系统之间的能量交换中，对冻土的热状况也有重要的影响作用．

天山季节性积雪的能量平衡研究和融雪速率模拟

本文采用能量平衡法模拟计算中国西部天山山地季节性积雪的融雪速率。结果表明:在融雪期,净辐射和感热通量分别占融雪能量输入的75.3％和22.6％;用于融雪和雪面蒸发所消耗的能量分别占吸收能量的95.1％和4.9％。用能量平衡法所计算的融雪速率和实测的雪面数据吻合的较好,表明用能量平衡法估算天山山地季节性积雪的融雪速率是可行的。

天山乌鲁木齐河源区表层雪中含氮离子季节变化特征

通过2004—2007年在天山乌鲁木齐河源1号冰川积累区采集的136个表层雪样品,分析了山岳冰川表层雪中主要含氮离子(NO-3与NH+4)的季节变化特征.结果表明,湿季表层雪中的含氮离子浓度一般比干季高,由于湿季NO-3与NH4+的输入量与流失量均较大,因此湿季浓度波动比干季更强烈.气溶胶与表层雪中的NO-3浓度在干季存在显著的相关性,在湿季相关性差,而NH+4浓度则表现出相反的特征.表层雪中含氮离子浓度大多高于极地和青藏高原,原因在于本研究区受粉尘输入与人类活动的影响较大.

天山季节性积雪稳定期雪密度与积累速率的观测分析

利用Snow Fork雪特性分析仪测量的天山积雪雪崩站2009年2月21-26日及2010年1月26-31日雪特性数据,分析了季节性积雪稳定期内积雪垂直剖面密度的变化特征及其随降雪沉积时间和雪层深度的变化规律.结果表明:季节性积雪稳定期内,积雪剖面密度中部最大,表层和底层密度较低;新雪层密度随时间的推移增加速率逐渐增大,细粒雪层、中粒雪层、粗粒雪层和深霜层密度随时间推移增加速率逐渐减小;不同深度雪层密度随深度变化呈现出规律性的变化.通过建立的雪层密度随降雪沉积时间和积雪深度而变化的经验关系式,可以应用两个极易获取的积雪参数(即降雪沉积时间和积雪深度)来推算不同深度的雪层密度.

近30a来天山西部积雪与气候变化——以天山积雪雪崩研究站为例

利用位于天山西部的中国科学院天山积雪与雪崩研究站1967—2000年近33 a来的观测记录,检验了天山西部中山带季节性积雪、冬季降水、冬季平均气温的变化趋势. 结果表明: 季节性积雪的长期变化呈增加趋势, 近33 a来年平均增加1 43%; 冬季气温和降水的变化趋势也是增加的, 其中冬季降水每年平均增加0 12%, 而冬季气温近30 a来升高了0 8 ℃. 对气温时间序列的一次线性倾向估计的倾向值为0 02, 气温变化表现出稳定的升温趋势, 最大熵谱分析表明气温的变化存在 2 1 a、3 6 a、10 7 a的变化周期. 对多年气温季节的变化研究表明, 升温的季节主要是冬季, 而夏季升温不明显;最大熵谱分析表明降水变化存在2 1 a、6 4 a、10 7 a的周期变化, 降水量的变化没有表现出很强的趋势性特点;逐年最大积雪深度在波动中成逐年增加的趋势, 积雪日数和最大积雪深度之间密切相关, 33 a来的积雪日数是增加的. 通过对相关因子和影响因子分析表明, 季节性积雪与冬季气温之间存在着弱的负相关关系, 与冬季降水呈显著的正相关关系.

中国西北地区季节性积雪的性质与结构

中国内陆地区积雪分布十分广泛。根据西北地区大陆性气候条件下形成的“干寒型”积雪的特征 ,对中国天山和阿尔泰山山区的季节性积雪进行了观测与分析。结果表明 ,该区最大积雪深度达 15 2cm(1997) ,积雪层一般由新雪 (或表层凝结霜 )、细粒雪、中粒雪、粗粒雪、松散深霜、聚合深霜层和薄融冻冰层组成。与“湿暖型”积雪相比 ,“干寒型”积雪的性质具有密度小 (新雪的最小密度为 0 .0 4 g/cm3 )、含水率少 (隆冬期 <1% )、温度梯度大(最大可达 - 0 .5 2℃ /cm)、深霜发育层厚等特点 ,并且变质作用以热量交换和雪层压力变质作用为主。据中国科学院天山积雪与雪崩研究站 (43°2 0N ,84°2 9E ,海拔 1776m)的观测资料 ,中国内陆干旱区冬季积雪期雪面太阳辐射通量以负平衡为主 ,新雪雪面反射率达 96 % ,短波辐射在干寒型积雪中的穿透厚度达 2 8cm。春季积雪消融期 ,深霜层厚度可占整个积雪层厚度的 80 %。随着气温的升高 ,雪粒间的键链首先融化 ,使积雪变得松散 ,内聚力、抗压、抗拉和抗剪强度降低 ,积雪含水率也随之增大 ,整个积雪层趋于接近 0℃的等温现象 ,因此 ,春季天山。

季节性积雪环境雪/气间汞通量特征初步研究

研究区域内冬季存有5个月以上稳定性季节积雪,为研究积雪地表状况下雪/气间汞交换通量特征,设置了平地农田和坡地农田2类共4处采样点,于2011年12月和2012年3月,使用动态通量箱法(dynamic flux chamber,DFC)与汞分析仪(LUMEX Zeeman RA915+)联用技术测定了各样点雪/气间汞交换通量,并同步测定太阳辐射、气温和气湿等气象因子,分析了雪/气间汞通量变化特征及其与气象因子等因素间的关系。结果表明:季节性积雪稳定存在时,雪/气间汞通量表现为明显的由大气指向雪面的沉降特征过程。季节性积雪趋于消融时,雪/气间汞通量表现为沉降与释放交替出现,总通量水平比积雪期降低一个数量级。雪/气间汞通量与大气汞浓度存在明显的负线性相关关系,与太阳辐射强度间有明显的正线性相关性,与气温和气湿间无线性相关性。

季节性冰雪蓄冷技术的研究现状与技术展望

介绍了季节性冰雪蓄冷技术的特点、应用形式、国内外的研究现状及技术发展前 景。通过分析指出,季节性冰雪蓄冷技术在能源利用、环境保护及降低系统运行费用方面与传 统的电制冷系统相比具有很大的优越性,在具有严寒漫长的冬季及温和短暂夏季的气候地区, 季节性冰雪蓄冷技术在工业、农业、舒适性供冷及食品冷藏方面有着广阔的发展与应用前景。

气候模式中积雪覆盖率参数化方案的对比研究

利用基于NCEP再分析的近地面气候资料驱动陆面过程模型NCAR CLM3,检验了6种积雪覆盖率参数化方案(CLM3、Douville1995、Roesch2001、Wu2004、Yang1997、Niu2007)模拟的积雪覆盖率的季节变化,并与NOAA AVHRR得到的观测结果进行了对比分析。结果表明,在NCARCLM3的物理过程框架之下,CLM3、Douville1995、Roesch2001三种方案低估了广大地区的积雪覆盖率,模拟的雪线位置偏北,尤其是在秋季积雪初期;Wu2004方案低估了秋季欧亚大陆的积雪覆盖率;Yang1997方案模拟的积雪覆盖率有些偏高,尤其是在积雪覆盖区的南部边缘;考虑积雪密度变化的Niu2007方案一定程度上克服了Yang1997方案的正偏差。春季末期,6种方案模拟的雪线位置都偏北。在地形比较平缓的地区,Niu2007方案的整体效果最好。观测和模拟的积雪覆盖率的出现频数大部分集中在低(小于0.2)和高(大于0.8)覆盖率等级,中等覆盖率所占比例很少。

阿尔泰山融雪期不同下垫面积雪特性观测与分析研究

2014年3月融雪期间在阿尔泰山额尔齐斯河河源区,基于已有的气象和积雪(雪深、雪密度)观测,利用Snow Fork雪特性仪和便携式温度计TP3001,选择草地、水泥地和河冰三种不同的下垫面分别观测了分层积雪密度、液态水含量和雪层温度变化.结果表明:三种下垫面上表层积雪的温度、液态水含量和密度变化规律基本一致.积雪特性的差异主要体现在积雪层底部,河冰和草地与积雪接触面温度日变化过程呈现出"单峰型",而与水泥地接触面上的温度日变化呈现出"双峰型";河冰上积雪底部的液态水含量最小且日变化幅度较小,草地次之,水泥上积雪底部液态水含量的波动最大;水泥和草地上底部积雪的密度变化趋势一致,为密实化过程,而河冰上积雪底部的积雪因深霜层的形成致使雪密度逐渐减小.对同一下垫面上的积雪而言,水泥和草地上积雪温度的极大值出现在雪层中间,河冰上雪层的温度廓线沿雪深有波动上升的趋势,最大值出现在积雪与河冰的接触面处.三种下垫面上积雪的液态水含量最大值均出现在中间雪层,雪密度均呈现沿雪深增加而递减的变化趋势.液态水含量受积雪温度的控制,当积雪温度低于-3℃时,积雪中的液态水可以忽略不计;当积雪温度低于-1℃时,积雪的液态水含量低于1%;当积雪温度大于-1℃时,积雪中出现液态水的比例显著增加,且液态水含量的波动范围较大,最高可到6.2%.