Central Italy Complete Daily Precipitation Series

The "Central Italy Complete Daily Precipitation Series" dataset provides a meticulously gap-filled daily precipitation record for 201 stations in Central Italy from 1951 to 2019. Using quantile mapping, spatial interpolation, machine learning, and multi-strategy merging techniques, the dataset ensures serial completeness and high accuracy. It incorporates data from neighboring stations and ERA5 estimates, validated through quality control measures such as Correlation Coefficient (CC), Root Mean Square Error (RMSE), Relative Bias, and Kling-Gupta Efficiency (KGE). This dataset is ideal for hydroclimatic modeling and projections. The dataset includes a CSV file with essential station information, such as station ID, latitude, longitude, elevation, and station name. The observed, estimated, and final Serially Complete Dataset are available in MAT format, with each column representing a time series of a station in the same order as in the CSV file. Additionally, the Nearby Info file provides the correlation coefficient (CC) and the distance between each target station and its assigned nearby stations, with each column corresponding to a target station in the same order as in the CSV file.‘意大利中部完整逐日降水序列’（Central Italy Complete Daily Precipitation Series）数据集提供了1951年至2019年间意大利中部201个气象站的经精细化缺失值填补的逐日降水记录。本数据集采用分位数映射（quantile mapping）、空间插值、机器学习及多策略融合技术，确保序列兼具完整性与高精度性。其整合了邻近气象站数据与ERA5再分析估算数据，并通过相关系数（Correlation Coefficient, CC）、均方根误差（Root Mean Square Error, RMSE）、相对偏差及克林-古普塔效率（Kling-Gupta Efficiency, KGE）等质量控制手段完成验证。该数据集适配水文气候建模与预估研究场景。 数据集包含一份CSV格式文件，内含气象站核心信息，包括站号、纬度、经度、海拔高度及站点名称。实测数据、估算数据与最终完整序列数据集均以MAT格式存储，各列按照与CSV文件一致的顺序，分别对应单个气象站的时间序列。此外，‘邻近站点信息’文件提供了各目标气象站与其匹配邻近站之间的相关系数（CC）与距离信息，各列同样按照与CSV文件一致的顺序对应各目标气象站。