A serially complete daily precipitation dataset for South America: quality control, gap-filling, and homogeneity

This study presents the Serially Complete Precipitation dataset for South America (SC-PREC4SA), a reliable daily precipitation dataset (1960-2015) that overcomes observational gaps and maintains temporal consistency across climates. SC-PREC4SA consolidates data from 7799 weather stations, employing advanced quality control, gap-filling, and homogenization methods to improve accuracy and reliability. The quality control process addressed common and overlooked issues, resulting in considerable improvements in data integrity. Gap-filling achieved a mean prediction accuracy of 70% (60%) for wet/dry days (wet-day magnitude). These findings illustrate the reliability of the gap-filling procedure, especially in mixed climates with sparse station networks. The homogenization approach which focuses mostly on wet days, effectively reduces inhomogeneities while preserving precipitation variability and resolving any biases created during the gap-filling. The compiled dataset captures daily precipitation patterns with moderate to high accuracy, enabling the temporal coherence required for climate research. The comprehensive SC-PREC4SA framework generates multiple outputs, making it useful for a variety of applications such as climate research, hydrological modeling, and water resource management, as well as addressing long-standing issues with precipitation data availability and quality in South America. By addressing limitations in observational datasets and strengthening spatiotemporal consistency, SC-PREC4SA sets a standard for future precipitation datasets in regions with diverse climates and complex terrain. The SC-PREC4SA data collection is publicly available on figshare: https://doi.org/10.6084/m9.figshare.c.7588178.