多源雪深数据在中国的空间特征评估

积雪的年际和年内变化强烈地影响着区域及全球的水量平衡，同时，积雪反照率反馈也显著地影响着气候变化。目前长时间序列的格网雪深数据主要来自被动微波遥感及再分析资料，但不同数据之间存在着明显差异。基于多源雪深数据的评估，特别是空间特性的评估还很缺乏。因此，本研究选取了AMSR-E、WESTDC、GlobSnow、RA-Interim及MERRA2这5种雪深数据，以站点观测数据为参考真值，对它们进行了中国地区的空间误差对比及基于误差排序的相对表现分析。评估结果初步显示：①WESTDC在我国西北及东北积雪区表现较好，适合用于我国北方的雪深研究；②MERRA2在西北和东北积雪区也有较好的表现，但由于其分辨率较粗，缺乏细节的空间信息，因此认为比较适用于大区域的统计分析；③AMSR-E在我国中部和东南地区表现最好，因此认为适合我国中部及东南部的雪深研究。

Evaluation on the Spatial Characteristics of Multiple Snow Depth Datasets over China

Snow cover is of great significance to both global water balance and the climate system, due to its significant variability, as well as snow albedo feedback. Current grid snow depth datasets of long time series are mainly derived from passive microwave remote sensing and reanalysis, but apparent inconsistencies exist among them. Nevertheless, the assessment on multi-source snow depth datasets is still inadequate, especially assessment on their spatial characteristics. Therefore, 5 snow depth datasets, including AMSR-E, WESTDC, GlobSnow, ERA-Interim and MERRA2, were evaluated against ground observations on their spatial uncertainties and relative performances. Preliminary results were: (1)Due to the fine performances at northwest and northeast part of China, WESTDC is quite suitable in snow depth study over northern China; (2)MERRA2 shows general good performances in northwest and northeast part of China, while it lacks of detailed information due to the coarse resolution, it is recommended to conduct statistical analysis over large regions. (3)AMSR-E performs best in middle to southeast part of China, which makes it a good choice in snow depth analysis over mid-southeast part of China.