SC-PREC4SA: A serially complete daily precipitation dataset for South America

作者：Adrian Huerta, Roberto Serrano‐Notivoli, Stefan Brönnimann · 发表于：Scientific Data · 年份：2025 · DOI：10.1038/s41597-025-05312-1 · 被引用次数：8 · 研究领域：Precipitation Measurement and Analysis、Climate variability and models、Soil Moisture and Remote Sensing

This study introduces the serially complete precipitation dataset for South America (SC-PREC4SA), a daily precipitation dataset (1960-2015) designed to address observational gaps and ensure temporal consistency across diverse climates. The raw dataset underwent quality control, gap-filling, and homogenization procedures. Applied robust quality control highlighted common but also overlooked issues, enhancing data reliability. Gap-filling achieved a mean accuracy of 70 % (60 %) in the prediction on wet/dry days (wet-day magnitude). These metrics highlight the reliability of the gap-filling process, particularly in mixed climates, where station networks are sparse. The homogenization algorithm, focused primarily on wet days, effectively reduced inhomogeneities while preserving precipitation variability across South America. By integrating a unified framework and multiple outputs from 7794 stations, SC-PREC4SA provides a robust dataset that captures daily precipitation patterns with high to moderate accuracy and consistency. It offers a valuable resource for climate research, hydrological modeling, and water resource management, addressing longstanding challenges in precipitation data availability and quality for South America.