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.     

临清市近40年降雪天气特征分析

通过对1970—2010年临清市降雪及积雪观测资料的统计分析表明：聊城年降雪日数和积雪日数总体呈现波动下降的趋势,但降雪的极端天气出现的概率逐步增大;临清市降雪和积雪主要出现在10月到次年4月之间,12月—次年2月是降雪和积雪多发季节,12月—次年2月降雪日和积雪日分别占全年的75%,82%,其中1月降雪日和积雪日最多,分别占全年的28%,36%。     

1961-2014年青藏高原积雪时空特征及其影响因子

利用青藏高原(下称高原)1961-2014年地面110个气象站积雪深度、积雪日数、气温和降水逐日资料,系统地分析了高原积雪深度和积雪日数时空特征,并进一步探究了高原积雪深度和积雪日数与气候因子和地理因子之间的关系。研究发现:1961-2014年高原年平均积雪深度和积雪日数分别为0.26 cm和23.78 d,空间和季节尺度上分布不均匀,且积雪深度和积雪日数大值并不完全重合;在整体变化趋势上,积雪深度和积雪日数均呈缓慢下降趋势,分别为-0.0080±0.0086 cm·(10a)^-1(p=0.36)和-0.64±0.47 d·(10a)^-1(p=0.17),但在数理统计上不显著,且各站点差异性大;积雪深度和积雪日数在春季、冬季和年表现为“减-增-减”的年代际变化特征,而在秋季为“增-减”的变化特征;气温与积雪深度和积雪日数均有较好的相关性,冬季的降水与积雪深度和积雪日数高度相关;积雪深度和积雪日数随海拔呈增加趋势,积雪日数与纬度也高度相关,但积雪深度与纬度的相关性不明显。     

山东降雪含水比统计特征分析

降雪含水比（snow-to-liquid ratio,SLR）是指积雪深度与降雪融化后等量液体深度（降雪量）的比值,可用来计算积雪深度。山东有两种产生机制不同的降雪,冷流降雪主要分布在山东半岛北部沿海地区,其他类降雪在全省范围均可发生,二者的降雪含水比有明显差异。利用山东122个国家级气象观测站自建站以来至2018年12月的逐12 h降水量、日积雪深度、降水性质、日最高气温及1999—2018年的MICAPS高空、地面图资料,通过限定条件进行质量控制,统计分析了山东不同地区的降雪含水比气候特征,为积雪深度预报提供参考。结果表明：1）山东降雪含水比的变化范围为0.1～3.0 cm·mm-1,全省大部地区多年平均降雪含水比为0.9 cm·mm-1,主要集中在0.3～1.1 cm·mm-1之间;山东半岛北部沿海地区（强冷流降雪区域）的多年平均降雪含水比为1.3 cm·mm-1,主要集中在0.9～2.0 cm·mm-1之间。2）降雪含水比的大小与降雪量等级有关,且存在明显月变化。全省大部地区从中雪至暴雪随着降雪量等级的增大,降雪含水比依次减小;各等级的降雪含水比月最大值均出现在1月或12月,最小值出现在11月或2月;山东半岛北部沿海地区的降雪含水比表现出更为复杂的特征,在以冷流降雪为主的11月—次年1月,中雪、大雪和暴雪的降雪含水比基本相当;2月和3月冷流降雪不明显,降雪含水比表现出与其他地区降雪类似的特征。3）不同天气系统暴雪的降雪含水比有差异。江淮气旋暴雪过程平均降雪含水比为0.69 cm·mm-1,总体上呈现“北大南小,山区大沿海小”分布,中雪、大雪和暴雪的降雪含水比中位数分别为0.8、0.7和0.5 cm·mm-1;回流形势暴雪过程的全省平均降雪含水比为0.67 cm·mm-1,中雪的降雪含水比中位数为0.8 cm·mm-1,大雪和暴雪均为0.6 cm·mm-1;冷流暴雪的降雪含水比明显大于其他两类暴雪,中位数在1.1～1.6 cm·mm-1之间变化,中雪、大雪和暴雪的降雪含水比中位数分别为1.4、1.6和1.3 cm·mm-1。     

SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai-Xizang(Tibet)Plateau of China.The melt-water from the snow-cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring .So snowmelt runoff forecast has importance for hydropower,flood prevention and water resources utilize-tion.The application of remote sensing and Geographic Information System(GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper.The key parame-ter-snow cover area can be computed by satellite images from multi-platform,multi-templral and multi-spectral.A clus-ter of snow-cover data can be yielded by means of the classification filter method.Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning .According to the typical samples extracting snow covered moun-tained in detail also.The runoff snowmelt models based on the snow-cover data from NOAA images and observation data of runoff,precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reser-voir,which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June.The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin.With the develop-ment of remote sensing technique and the progress of the interpretation method,the forecast accuracy of snowmelt runoff will be improved in the near future .Large scale extent and few stations are two objective reality situations in Chian,so they should be considered in simulation and forecast.Apart from dividing ,the derivation of snow cover area from satellite images would decide the results of calculating runoff.Field investigation for selection of the learning samples of different snow patterns is basis for the classification.     

长时间尺度下自然资源动态综合区划理论与实践研究——以青藏高原为例

自然资源综合区划是自然资源统一管理与利用的基础,其动态变化是自然资源合理可持续利用的重要科学依据。由于青藏高原海拔高、气候寒冷,分布着除极地以外的最大冰川遗迹,极端的环境和气候对自然资源分布影响较大。选取含冰川积雪在内的14个指标,基于遥感和地理信息系统技术,采用K-means聚类算法对自然资源综合指数进行空间聚类,采用“自上而下”演绎法和“自下而上”归纳法相结合确定研究区自然资源综合区划的等级和范围; 探讨了1990—2018年青藏高原综合区划的变化,分析了自然资源动态变化特征以及空间差异。研究成果清晰地认识了青藏高原的自然资源关系和演化趋势,为区划的多学科交叉应用提供案例。     

2001-2015年天山山区积雪时空变化及其与温度和降水的关系

采用2001-2015年MODIS积雪和陆表温度数据、中国高时空分辨率降水数据,基于趋势分析和相关分析方法,分析了天山山区积雪时空变化及其与温度和降水的关系。结果表明：（1）年内积雪面积变化受海拔影响,海拔≤4 000 m,呈单峰型分布,积雪面积冬季大,夏季小;海拔介于4 000~≤5 000 m,积雪面积分别在春季和秋季出现两次峰值;海拔>5 000 m,积雪面积变化与低海拔相反,在夏季达到最大,冬季最小。就年际变化而言,全区积雪面积呈略微减少趋势,其中秋季略微增加,春季变化不大,冬季和夏季明显减少。（2）积雪覆盖频率受水汽来向和地形影响,呈西高东低、北高南低分布格局,与海拔呈正相关。山区大部分区域积雪覆盖频率呈减少趋势,其中海拔介于3 600~≤4 600 m的积雪覆盖频率减少最为显著。（3）在春、夏季,温度是决定积雪面积变化的主要因素,与积雪面积呈负相关;在秋、冬季,降水对积雪面积变化的贡献大于温度,与积雪面积呈正相关。（4）积雪覆盖频率整体上与年均温度呈负相关,与降水呈低度正相关,相关程度及显著性水平在空间分布上存在差异,温度对积雪覆盖频率变化的贡献大于降水。     

青藏高原初春积雪的多尺度变化与北大西洋海温的关系

青藏高原冬、春季积雪变化影响东亚甚至全球春、夏季的环流及气候异常。利用中国西部环境与生态科学数据中心提供的中国雪深长时间序列数据集,美国大气海洋局提供的全球逐月扩展重建海表温度,以及欧洲中期天气预报中心提供的逐月再分析数据,对青藏高原初春（3、4月）积雪的多尺度变化与北大西洋海表温度的关系进行了研究。结果表明,初春青藏高原雪深异常与初春北大西洋关键区海温异常有显著的负相关关系。当初春关键区海温正（负）异常时,初春高原中部偏北腹地地区、东南部地区积雪深度减少（增加）;初春北大西洋关键区海温异常通过激发下游青藏高原上空大气波列以及波作用通量异常来影响高原局地区域的温度和垂直运动,从而影响降雪的产生和积雪的累积。该结果为青藏高原初春积雪的多尺度变化及其影响提供了依据。     

小流域积雪时空变化特征对比研究

利用Terra和Aqua卫星提供的2002~2012年MODIS 8d积雪分类产品MOD10A2和MYD10A2生成双星8d合成产品MOYD10A2,并进行精度评价。在此基础上,提取了嫩江与辽河流域积雪覆盖率、相对积雪日数和归一化积雪指数,并对比分析了嫩江与辽河流域的积雪时空变化特征。结果表明:(1)合成后的图像大大降低了云层对积雪产品的影响,更好地恢复了云下积雪遥感信息,提高了积雪遥感指数的精度;(2)嫩江、辽河流域积雪高峰期均出现在11月中下旬到次年4月中上旬,每年的积雪覆盖率高峰期和变化趋势基本保持一致,但嫩江流域的积雪覆盖率明显高于辽河流域;受地理位置和海陆分布的影响,嫩江流域积雪天数呈由东北向西南方向减小的趋势,且积雪天数明显多于辽河流域;(3)MODIS 8d积雪分类产品可在长时间、大范围积雪监测中发挥作用。