Long-Term Spatial Precipitation Dataset for the Coastal Basin of Paraná, Brazil Authors/Creators

Dataset Description This dataset provides quality-controlled daily precipitation time series from 147 rain gauge stations distributed across the coastal hydrographic region of Paraná State, southern Brazil, spanning the period from 1981 to 2024. The stations include both conventional (manual) and telemetered (automatic) instruments operated by ANA (Agência Nacional de Águas) and COPEL (Companhia Paranaense de Energia). Data Processing & Quality Control A rigorous three-level quality control (QC) framework was applied to the data: Basic QC: Removal of co-located duplicates and scale-factor correction for six COPEL UHE/CGH telemetered stations that presented a known encoding error (a ÷10 correction was applied for the 2015–2020 period). Absolute QC: Removal of physically impossible precipitation values. Relative QC: A spatial consistency check against neighboring stations within a 74.2 km influence radius, adapted from Llabrés-Brustenga et al. (2019). Each daily record is classified with a specific quality flag: V = Valid D = Doubtful N = Not valid I = Insufficient neighbors ET = Extreme event Note: For most analytical applications, filtering the dataset to include only V (Valid) and ET (Extreme event) flags is highly recommended. Gridded Product In addition to station data, monthly precipitation totals from the validated series were spatially interpolated onto a regular 5 km × 5 km grid using the Inverse Distance Weighting (IDW) method based on the four nearest stations. The resulting grids represent the long-term mean monthly climatology. Dataset Contents The repository is organized into the following directories and files: data/01_series_corrigidas/: Contains 147 daily series after Basic QC. (Columns: date, prec_mm) data/03_qc_relativo/: Contains 147 daily series after the full QC framework. This is the primary data product. (Columns: date, prec_mm, flag) grids/: Contains 12 CSV files representing the monthly climatology grids (one file per calendar month at 5 × 5 km resolution, expressed in mm/month). metadata/estacoes_plu_1981_2024.csv: Includes metadata for all stations (coordinates, elevation, instrument type, and data source). pipeline/: Contains all Python scripts required for full pipeline reproducibility. Related Publication Reference / DOI to be added upon acceptance.