【作者】 高洁；

【导师】 王光谦；

【作者基本信息】 清华大学 ， 水利工程， 2011， 博士

【摘要】 我国是中低纬度地区冰冻圈最发育的国家。积雪是冰冻圈要素之一，对气候变化响应敏感，同时影响水文循环系统。本文以积雪的时空分布特征和融雪过程为研究对象，首先通过遥感、气象数据的统计和挖掘，分析大、中尺度上藏东南山区积雪的时空分布特征；再从点尺度上研究雪柱的垂向消融过程，依托于Niwot Ridge（美国Colorado州Rocky Mountains）积雪剖面实测资料，建立并验证基于过程的能量平衡融雪模型Snow Column。在大尺度上，提出了区域变动积雪覆盖高程（FSCE）的概念化模型，定量描述高山积雪由于海拔高差导致年内积雪消融时间差异的现象。以藏东南山区15万km~2区域为研究对象，在对25km×25km微波遥感积雪数据有效性验证的基础上，获得了FSCE模型的两个参数：无雪期中期T_m和无雪期持续时间ΔT，建立了FSCE曲线。通过对27年时间序列T_m和ΔT的TFPW-MK趋势检验发现：高海拔处以降水驱动的积雪模式主导，存在积雪期变长的现象；低海拔处以温度驱动为主，存在无雪期变长的现象。在中尺度上，基于MODIS空间分辨率500m的雪产品和植被产品数据，以上述研究区域内拉萨河羊八井小流域2665km~2丰雪区为研究对象，分析了积雪～高程和植被～高程的关系。研究发现，在积雪、植被敏感变化的高程带内，积雪～高程和植被～高程为两条近似互为反向的“S”型曲线。这一现象再次提供了积雪和植被在限定范围内的密切相关性的证据，显示了积雪、高程关系和植被、高程关系两者能够互为指示。与大尺度研究相比，更高精度的中尺度数据信息使积雪～高程关系从大尺度的线性关系丰富为中尺度的非线性“S”型曲线。在小尺度上，建立了描述单点积雪垂向消融过程的Snow Column模型。通过Niwot Ridge观测站#006雪坑剖面资料对模型验证，表明Snow Column模型能反映雪深、雪温和密度等状态量随时间的变化。通过变化气象输入条件，模型再现了雪柱整层融化、雪深减小、融水出流和雪层部分融化、压实、密度增大两种消融现象。Snow Column模型今后有待于耦合积雪空间分布资料和融水汇流过程，进一步发展为空间分布式融雪模型。更多还原

【Abstract】 Snow is an essential factor in cryosphere that is of great importance inChina. The snow shows an indicative response to climate change and affectshydrological cycle system. This study explores the characteristics of the snow atvarious scales: the spatiotemporal distribution of seasonal snow in SouthEastern Tibet and local snowmelt process in a snow column.At the macro-scale, a conceptualized model of Fluctuating Snow-CoveredElevation (FSCE) is proposed, quantifying differentiated onset of snowmeltattributed to different elevation in mountainous regions. The snow in SouthEastern Tibet of approximately15×104km~2is characterized based onmicrowave remote sensing snow product with a spatial resolution of25km. Twokey parameters in the FSCE model, i.e., the median (T_m) and duration (ΔT) ofsnow-free period, are accordingly determined. Meanwhile, the TFPW-MK trendtest is used to reveal the response of seasonal snow to climate change. Theanalysis of27-year time series of T_mand ΔT shows that: the snow-coveredperiod has decreased at low elevations due to the increase in air temperature,and the snow-free period has decreased at high elevations because the increasein precipitation compensates for the increase in air temperature.At the meso-scale, the relationship between snow and elevation and that ofvegetation and elevation are explored for the Yangbajain basin of2665km~2inLhasa River basin. The MODIS snow and vegetation products with a spatialresolution of500m are analyzed. It is shown that there is a pair of “S”-shapedand reversed “S”-shaped profiles for the snow-elevation andvegetation-elevation relationships. This provides an evidence of the closerelationship between the two profiles. It also suggests the effect of spatial scale,that is, the data with the higher spatial resolution provides more information onthe snow-elevation relationship: a non-linear “S”-shaped curve at themeso-scale instead of linear profile at the macro-scale.At the micro-scale, the Snow Column model is developed for representinglocal snowmelt processes in the vertical direction. The observed data at#006 snowpit of Niwot Ridge, Colorado, Front Range of Rocky Mountains, is used tovalidate the Snow Column model. It is shown that the developed model iscapable of characterizing the temporal variation of snow depth, temperature anddensity. Analysis of the response of snowpack to meteorological conditionsshows that there exist two phenomena: one is “the whole snow layer meltsresulting in the decrease in depth and flowing out of water” and the other is“some part of the snow layer melts and the remaining part gets densified”. In thefuture, this local scale model could be developed into a spatially distributedmodel through combing spatial snow input and flow routing method.更多还原