1979-2019年北极地区10km多源融合雪水当量网格数据集

雪水当量(Snow water equivalent, SWE)是地表水文模型和气候模型的重要参数。本数据基于机器学习的岭回归算法融合了多种现有的雪水当量数据产品，形成了一套时间序列连续且精度较高的雪水当量数据产品。数据的空间范围为泛北极地区(北纬45°至北纬90°), 数据时间序列为1979-2019年。该数据集有望为水文模型和气候模型提供更为精确的雪水当量数据，为冰冻圈变化及全球变化提供数据支撑。Snow Water Equivalent (SWE) is a critical parameter for surface hydrological models and climate models. This dataset integrates multiple existing SWE products using the ridge regression algorithm from machine learning, producing a high-precision SWE dataset with continuous temporal sequences. Its spatial coverage spans the pan-Arctic region (45°N to 90°N), with a temporal range from 1979 to 2019. This dataset is expected to provide more accurate SWE data for hydrological and climate models, and offer data support for research on cryospheric changes and global changes.