Jülich Research Center GmbH, Institute of Bio- and Geosciences: Agrosphere (IBG 3), Jülich, 52425, Germany.
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, Jülich, 52425, Germany.
Sci Data. 2020 Apr 3;7(1):111. doi: 10.1038/s41597-020-0450-6.
High-resolution soil moisture (SM) information is essential to many regional applications in hydrological and climate sciences. Many global estimates of surface SM are provided by satellite sensors, but at coarse spatial resolutions (lower than 25 km), which are not suitable for regional hydrologic and agriculture applications. Here we present a 16 years (2000-2015) high-resolution spatially and temporally consistent surface soil moisture reanalysis (ESSMRA) dataset (3 km, daily) over Europe from a land surface data assimilation system. Coarse-resolution satellite derived soil moisture data were assimilated into the community land model (CLM3.5) using an ensemble Kalman filter scheme, producing a 3 km daily soil moisture reanalysis dataset. Validation against 112 in-situ soil moisture observations over Europe shows that ESSMRA captures the daily, inter-annual, intra-seasonal patterns well with RMSE varying from 0.04 to 0.06 mm and correlation values above 0.5 over 70% of stations. The dataset presented here provides long-term daily surface soil moisture at a high spatiotemporal resolution and will be beneficial for many hydrological applications over regional and continental scales.
高分辨率土壤湿度 (SM) 信息对于水文学和气候科学中的许多区域应用至关重要。许多卫星传感器提供全球表面 SM 估计，但空间分辨率较低（低于 25km），不适合区域水文和农业应用。在这里，我们展示了一个 16 年（2000-2015 年）的高分辨率、时空一致的欧洲表面土壤湿度再分析数据集（ESSMRA）（3km，每日），该数据集来自土地表面数据同化系统。使用集合卡尔曼滤波方案将粗分辨率卫星衍生土壤湿度数据同化到陆面模式（CLM3.5）中，生成 3km 每日土壤湿度再分析数据集。对欧洲 112 个原位土壤湿度观测的验证表明，ESSMRA 很好地捕捉了每日、年际和季节内的变化模式，RMSE 在 0.04 到 0.06mm 之间变化，70%以上站点的相关值高于 0.5。本文提出的数据集提供了长期每日表面土壤湿度，具有高时空分辨率，将有益于区域和大陆尺度的许多水文应用。
