面向青藏高原的地表微波辐射建模及多年土壤水分反演

As the third pole of the Earth, Tibetan Plateau has a significant impact on the regional and global energy and water cycles. Tibetan Plateau is also the hot-spot area for the global environmental change studies. Surface soil moisture is the key parameter for the hydrology and climatology studies. Soil moisture is governed by the water and energy exchanges between land surface and atmosphere, and affects the global weather systems. However, due to the severe natural conditions of Tibetan Plateau, there is no long-term, high-accuracy soil moisture datasets available for describing the spatial-temporal distribution of the soil surface wetness of the region. Based on field experiments, this project will re-develop microwave emission models for a best representative of the vegetation and soil characteristics of the Tibetan Plateau. We will then develop high-accuracy soil moisture inversion algorithm for the L-band space-borne radiometers. The L-band soil moisture product should be accurate enough to calibrate AMSR-E inversion algorithm. The calibrated algorithm will be applied to the long-term AMSR-E and AMSR2 observations. Finally, multi-year soil moisture database will be generated for the Tibetan Plateau region with consistent spatial-temporal distributions.

青藏高原作为地球第三极，对东亚及全球能量循环、水循环有着重大影响，也是全球环境变化研究的热点区域。表层土壤水分是水文学和气象学研究中的关键变量之一, 影响着地表和大气之间的水和能量交换，最终影响到全球的天气系统。青藏地区由于其特殊的自然地理条件，尚缺少一套长时序、高精度的表层土壤水分数据集，缺少对其地表参数空间分布和时间演化特征的准确的描述和分析。本研究以地面实验为基础，根据青藏地区植被覆盖和土壤参数特点，发展、改进微波辐射模型；同时利用目前最适合土壤水分反演的星载L波段微波辐射计观测，发展高精度土壤水分反演算法；在此基础上，综合多传感器观测，修正AMSR-E及其后续传感器AMSR2的土壤水分反演算法，生成精确的、源于不同传感器观测但时空一致的青藏地区多年土壤水分反演数据集。

青藏高原作为地球第三极，对东亚及全球能量循环、水循环有着重大影响；同时青藏高原特殊的自然生态环境对全球变化十分敏感。对地表土壤水分时空分布及其变化的精确描述是模拟、分析高原生态环境变化的基础。本研究以地面实验为基础，根据青藏地区大气、地表冻融、积雪及植被、土壤参数的特点，发展、改进微波反演算法；并综合多传感器观测，生成长时序青藏地区土壤水分反演数据集。该数据集在青藏地区精度优于同类产品，为分析该地区的环境变化提供了数据支持。

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