ERA5 Land precipitation daily sum

Overview: era5.copernicus: precipitation daily sums from 2000 to 2020 resampled with CHELSA to 1 km resolution Traceability (lineage): The data sources used to generate this dataset are ERA5-Land hourly data from 1950 to present (Copernicus Climate Data Store) and CHELSA monthly climatologies. Scientific methodology: The methodology used for downscaling follows established procedures as used by e.g. Worldclim and CHELSA. Usability: The substantial improvement of the spatial resolution together with the high temporal resolution of one day further improve the usability of the original ERA5 Land time series product which is useful for all kind of land surface applications such as flood or drought forecasting. The temporal and spatial resolution of this dataset, the period covered in time, as well as the fixed grid used for the data distribution at any period enables decisions makers, businesses and individuals to access and use more accurate information on land states. Uncertainty quantification: The ERA5-Land dataset, as any other simulation, provides estimates which have some degree of uncertainty. Numerical models can only provide a more or less accurate representation of the real physical processes governing different components of the Earth System. In general, the uncertainty of model estimates grows as we go back in time, because the number of observations available to create a good quality atmospheric forcing is lower. ERA5-land parameter fields can currently be used in combination with the uncertainty of the equivalent ERA5 fields. Data validation approaches: Validation of the ERA5 Land ddataset against multiple in-situ datasets is presented in the reference paper (Muñoz-Sabater et al., 2021). Completeness: The dataset covers the entire Geo-harmonizer region as defined by the landmask raster dataset. However, some small islands might be missing if there are no data in the original ERA5 Land dataset. Consistency: ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past. Positional accuracy: 1 km spatial resolution Temporal accuracy: Daily maps for the years 2020-2020. Thematic accuracy: The raster values represent cumulative daily precipitation in mm x 10.概述： era5.copernicus：2000年至2020年逐日降水总和数据，经CHELSA重采样至1千米分辨率 溯源性（数据谱系）： 本数据集的生成数据源为1950年至今的ERA5-Land逐小时数据（哥白尼气候数据中心，Copernicus Climate Data Store）以及CHELSA月尺度气候学数据集。 科学方法学： 本数据集采用的降尺度方法沿用了Worldclim与CHELSA等已成熟应用的标准流程。 可用性： 本数据集在空间分辨率上的显著提升，结合每日一次的高时间分辨率，进一步优化了原始ERA5-Land时间序列产品的可用性。原始ERA5-Land产品已广泛应用于各类陆面相关场景，如洪水或干旱预报；本数据集的时空分辨率、覆盖时段，以及全周期统一的分发网格，可为决策者、企业与个人提供更为精准的陆面状态信息。 不确定性量化： 与所有数值模拟数据集一致，ERA5-Land数据集的估算结果存在一定程度的不确定性。数值模型仅能近似还原地球系统各组分所遵循的真实物理过程，精度存在局限。一般而言，模型估算的不确定性随时间回溯而增大，这是因为用于构建高质量大气强迫场的观测数据随时间推移而减少。当前，ERA5-Land的参数场可与对应ERA5场的不确定性信息结合使用。 数据验证方法： 相关参考论文（Muñoz-Sabater等人，2021）已展示了本数据集与多套原位观测数据集的验证结果。 完整性： 本数据集覆盖了陆面掩膜栅格数据集所定义的全部Geo-harmonizer区域。但若原始ERA5-Land数据中无对应区域的观测值，则部分小型岛屿可能未被包含在内。 一致性： ERA5-Land是一套再分析数据集，相较于原始ERA5，其分辨率得到提升，可连续展现数十年间陆面变量的演变特征。该数据集通过回放ECMWF ERA5气候再分析的陆面分量生成。再分析技术基于物理定律，将全球数值模式数据与全球观测数据融合为一套完整且一致的全球数据集，可回溯至数十年前，精准刻画过去的气候状态。 位置精度： 空间分辨率为1千米。 时间精度： 2000年至2020年的逐日格点降水数据。 主题精度： 栅格值代表以毫米×10为单位的逐日累积降水量。