Knowledge Resource Center for Ecological Environment in Arid Area
| AMSR-E土壤水分分析和TRMM降雨降尺度研究 | |
| 其他题名 | AMSR-E Soil Moisture Analysis and Method for Downscaling TRMM Precipitation |
| 刘强 | |
| 出版年 | 2014 |
| 学位类型 | 博士 |
| 导师 | 施建成 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 水循环是联系地球表面各圈层之间物质交换和能量平衡的纽带，其变化影响着全球水资源系统和生态环境系统的结构和演变，影响着人类社会的发展。在全球变化的背景下，水循环在全球气候和生态环境变化中的作用，越来越受到重视，成为各项科学计划共同关注的科学问题。作为全球水循环研究中的两个关键变量，土壤水分和降雨是目前遥感领域研究的热点。 表层土壤水分通过控制着降雨的地表下渗和蒸发，影响地表和大气之间的水和能量交换，最终影响到全球天气系统。“世界第三极”的青藏高原地区对亚洲季风和全球大气循环有着极大的影响。定量化研究青藏高原地区土壤水分的趋势与变化，有助于更好理解青藏高原在亚洲季风和全球大气循环过程中的作用机制，为应对未来的气候变化提供预警和应对策略。一套准确的多年青藏高原地区土壤水分数据能够为该地区的“陆表-大气交互作用”和数值模型模拟等研究，提供重要的观测信息和初始输入数据。AMSR-E提供的多年连续地表亮温数据（2003.06-2011.10），非常适合反演青藏高原地区的土壤水分数据。 降水量决定区域的水分和热量状况，是气候分析，水资源评价，水分循环与平衡等研究中必不可少的参数。华北地区是我国重要的工业区和农业基地，也是水资源匮乏地区之一，水资源的供需矛盾已经成为制约其经济持续发展的主要因素。降水是华北地区最重要的水资源来源，因此高空间分辨率的降雨数据对于该区域降水的时空分布研究及水资源调查具有重要意义。 在青藏高原地区位于不同气候带的三个土壤水分验证区，对四种AMSR-E土壤水分（NASA，LPRM，JAXA和IRSA）进行验证，评价四种土壤水分在青藏高原地区不同气候区的表现。验证结果表明：四种土壤水分产品在半干旱、干旱区（那曲和CAMP/Tibet验证区）的精度整体优于在半湿润区（玛曲验证区）；在季风期，升规的土壤水分产品整体上优于降规产品；除了非季风期的降规产品表现较差，IRSA产品整体上优于其它三种产品，说明IRSA算法在青藏高原地区有一定程度的改进。 结合TRMM降雨和Modis地表温度数据，采用四种AMSR-E土壤水分产品，分析青藏高原地区土壤水分时空分布和变化趋势。NASA，LPRM和IRSA三种产品，在年平均土壤水分的空间分布上整体一致，土壤水分自东南向西北逐渐降低，JAXA产品与其它三种差异较大，不能区分出干旱区与半干旱区；青藏高原地区土壤水分的季节变化明显，整体上高原外围土壤相对较湿，中部相对较干，随着季风的到来土壤高湿度地区分别从藏东南向藏西北，从塔里木盆地向藏东北扩展，随着冬季的来临，土壤高湿度地区分别向藏东南和塔里木盆地收缩，季节变化以及区域分布特点总体上与高原的水分输送路径和降雨分布比较一致；从土壤水分多年变化趋势的空间分布来看，整体上青藏高原存在中南部变干，西北部变湿的倾向，整体变化趋势与降雨变化趋势的空间分布相吻合；土壤水分和降雨存在显著变化趋势的区域相对于整个青藏高原比例很小，青藏高原大部分地区的土壤水分没有显著的变化。 针对TRMM-3B43产品，发展了一种新的降尺度方法。新方法以降雨与植被（NDVI）和地形（DEM）之间的经验关系构建TRMM降雨降尺度模型，在回归拟合模型系数时，采用一种局部统计方法即地理权重拟合方法（GWR）。GWR方法在回归拟合模型变量之间的关系时，考虑了变量的空间位置，回归系数构建的模型能够描述降雨与NDVI和DEM之间关系的空间变异性。新方法利用粗分辨率（0.25°）的TRMM 3B43产品，高分辨率（1km）的DEM和NDVI数据能够得到高分辨率（1km）的降雨数据。采用降尺度方法，生成了华北地区2008年~2011年四年的分辨率为1km的高分辨率降雨数据，并采用研究区范围内的49个气象站点对降尺度后的降雨数据进行验证。验证结果表明，在2008年~2011年这四年，新发展的降尺度方法在R2，RMSE和Bias这三个统计指标上，普遍优于现有的降尺度方法。 |
| 英文摘要 | Water cycle links material exchange and energy budget between multiply spheres of the Earth's surface. Its change affects the structure of global water system and the evolution of environmental system and eventually will influence social development. In the context of global change, the role of the water cycle in the global climate change and ecological environment, has attracted more attention, which was listed as common issue in several scientific programs. As key variables in the global water cycle study, soil moisture and rainfall are currently hot research field of remote sensing. By controlling the infiltration and evaporation, surface soil moisture affects the water and energy exchange between the surface and atmosphere, ultimately affects the global weather system. The ‘Third Pole’ of Tibet Plateau has great impact on the Asian monsoon and the global atmospheric circulation. Quantitative research of the change and trend of soil moisture in the Tibet Plateau, helps to understand the process mechanism of the Tibetan Plateau in the Asia monsoon and global atmospheric circulation, and provides early warning and response strategy for the climate change. A set of accurate multi-year soil moisture data in Tibet Plateau provides important observation information and initial data for land-atmosphere interaction research and numerical model simulation. The AMSR-E’s continuous surface bright temperature data is very suitable for producing soil moisture data for the Tibet Plateau. Precipitation decides region’s moisture and heat condition and provides essential parameters for the climate study and water resources assessment. As China's important industrial and agricultural base, the North China is also one of water scarcity areas. Precipitation is the most important source of water resources in this area, so the rainfall data with high spatial resolution is very useful for the precipitation spatial-temporal distribution research and water resources survey in this area. In three experimental areas locatd in different climate zone of Tibet Plateua, four sets of AMSR-E soil moisture products were validated. Results follows: (a) In semi-arid and arid areas, four kinds of soil moisture products have the better precision than that in the semi-humid zone; (b) In monsoon, soil moisture of ascending swath is better than descending swath; (c) Except for descending swath product in winter, the IRSA product performs overall better than the other three, which indicates IRSA algorithm has a certain degree of improvement in the Tibet Plateau. Combined with TRMM rainfall product and the Modis land surface temperature data, the spatial-temporal distribution and multi-year trend of Tibet Plateau soil moisture was analysed. In the spatial distribution of annual average soil moisture, three of NASA, LPRM and IRSA were consistent on the whole, which the soil moisture gradually reduced from the southeast to northwest. The spatial pattern of JAXA was different with the other three, which can’t distinguish the arid area and half arid area. Seasonal variation of soil moisture showed the soil moisture of plateau periphery was relatively wet and in the middle was relatively dry. With the arrival of the monsoon, the wet region expanded from the southeast to norhtwest and from Tarim Basin to the northeast plateau, respectively. As the winter coming, the wet region shinked towards the opposite direction. The overall seasonal variation and regional distribution characteristics of moisture was consistent with the transmission path and the distribution of plateau’s rainfall. The Spatial distribution of soil moisture multi-year trend showed that central and southern part of plateau existed drying trend and north-west part existed wetting trend, which confromed with the overall spatial pattern of rainfall’s changing trend. Compared with the whole Tibet Plateau, the area with significant changing trend of soil moisture and rainfall was very small, so in most pa |
| 中文关键词 | 青藏高原 ; 土壤水分 ; 时空分析 ; 变化趋势 ; 降雨降尺度 |
| 英文关键词 | Tibet Plateau Soil Moisture Spatial-Temporal Analysis Precipitation Downscaling |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 地图学与地理信息系统 |
| 来源机构 | 中国科学院遥感与数字地球研究所 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/287453 |
| 推荐引用方式 GB/T 7714 | 刘强. AMSR-E土壤水分分析和TRMM降雨降尺度研究[D]. 中国科学院大学,2014. |
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