融合被动微波和可见光遥感估算青藏高原地区雪深算法研究

Snow cover in Qinghai-Tibet plateau plays an important role in the climate system and hydrological cycles, but there is no reliable snow depth or snow water equivalent product. Uneven distributed station observation cannot provide spatial continuous data. Although passive microwave remote sensing is an efficient way to retrieve spatial continuous snow depth, the coarse spatial resolution hindered its use in the Tibet plateau snow cover characterized by patch distribution of snow cover. The existing retrieval algorithms of snow depth with high spatial resolution failed to reflect the snow depth variance in space. Therefore, in this study, the dynamic snow depletion curve and the microwave emission model of snowpack will be used to combine the optical snow cover fraction and passive microwave remote sensing data to develop the high spatial resolution snow depth retrieval algorithm in Qinghai-Tibet plateau. The field observation in different snow period will be carried out and the snow data from stations during the recent ten years will be analyzed to summarize the a priori snow characteristics which will be used in the microwave emission model of snowpack to improve the simulation accuracy. The dynamic snow depletion that can reflect the spatial variance of relationship between snow depth ans snow cover fraction will be determined through field observation and optical snow cover fraction. Therefore, the dynamic snow depletion curve and the microwave emission model of snowpack can be used to estimate snow depth with high spatial resolution and high accuracy, and then provide data for climate and hydrological research in Qinghai-Tibet plateau.

青藏高原积雪在气候和水文系统中占据着重要的角色。但是青藏高原台站数据稀少，且分布不均，观测数据无法代表整个高原的积雪信息；而被动微波积雪产品分辨率较粗，且精度不高；已有的高分辨率雪深反演方法也没有体现雪深分布不均的现象。本研究将针对这些问题利用积雪衰减曲线和积雪辐射传输模型融合被动微波和可见光遥感，发展青藏高原高分辨的雪深反演方法。通过不同时期的积雪特性观测和分析多年的台站积雪观测获取积雪特性先验信息，在积雪辐射传输模型中引入积雪特性先验信息提高模拟精度。通过样方的雪深观测和遥感积雪面积比例确定动态积雪衰减曲线参数，反应积雪面积和雪深关系的时空变化性。并利用积雪辐射传输模型和动态积雪衰减曲线融合被动微波亮度温度和可见光积雪面积比例提取青藏高原高分辨率、高精度的雪深，为青藏高原气候和水文研究提供数据基础。

青藏高原积雪在气候和水文系统中占据着重要的角色。但是青藏高原台站数据稀少，且分布不均，观测数据无法代表整个高原的积雪信息。被动微波遥感成为唯一有效获取雪深的方法。但是被动微波积雪产品分辨率较粗，且在青藏高原出现严重高估。因此本研究利用站点观测、野外考察以及可见光遥感积雪面积等数据对青藏高原被动微波雪深进行评价，分析其高估的原因，发现冻土温度与青藏高原积雪面积的高估存在很好的关系。并针对这些问题综合MODIS积雪面积比例和地表温度产品以及被动微波亮度温度数据开展了500m分辨率雪深反演研究。该方法提高了青藏高原雪深空间分辨率同时也降低了被动微波高估率。通过野外考察数据和站点观测数据对其进行验证表明通过引入地表温度后，反演雪深精度提高，并且积雪面积越小精度提高得越大。