欧亚大陆长时间序列雪深数据集（1980-2016）

欧亚大陆雪深数据集采用被动微波遥感反演方法制作，数据覆盖时间从1980年到2016年，时间分辨率为逐日，覆盖范围为欧亚大陆，空间分辨率为0.25°。遥感反演方法采用动态亮温梯度算法，算法考虑积雪特性在时空和空间上的变化，建立了不同频率亮度温度差与实测雪深在空间和季节上的动态关系。长时间序列星载被动微波亮度温度数据来自SMMR、SSM/I和SSMI/S三个传感器。为保证不同传感器亮度温度在时间上的一致性，在雪深提取之前对不同传感器亮度温度进行了交叉订正。通过实测站点的验证表明欧亚大陆雪深数据相对偏差在30%以内。数据据每一天存放一个txt文件，每个文件由文件头（投影方式）和720*332的雪深矩阵组成，每个雪深代表一个0.25°* 0.25°的格网。

The Eurasian Snow Depth Dataset was developed using passive microwave remote sensing inversion methods. It covers the period from 1980 to 2016, with a daily temporal resolution, and spans the entire Eurasian continent at a spatial resolution of 0.25°. The remote sensing inversion adopts the dynamic brightness temperature gradient algorithm, which considers the temporal and spatial variations of snow cover properties, and establishes the dynamic relationships between brightness temperature differences at different frequencies and in-situ snow depth across both spatial and seasonal scales. The long-time series space-borne passive microwave brightness temperature data are sourced from three sensors: SMMR, SSM/I, and SSMI/S. To ensure the temporal consistency of brightness temperature data across different sensors, cross-calibration was performed on the brightness temperature data from each sensor prior to snow depth extraction. Validation using in-situ station measurements shows that the relative bias of the Eurasian snow depth dataset is within 30%. Each day's data is stored as a separate TXT file. Each file consists of a file header (indicating the projection method) and a 720×332 snow depth matrix, where each snow depth value corresponds to a 0.25°×0.25° grid cell.