Evidence map›Paper›PMID 40517157›Full record

ArticleScientific data2025

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

Adrian Huerta, Roberto Serrano-Notivoli, Stefan Brönnimann

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Adrian HuertaOeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland. adrhuerta@gmail.com.ORCID http://orcid.org/0000-0002-2415-3402
Roberto Serrano-NotivoliDepartamento de Geografia y Ordenación del Territorio, Instituto Universitario de Ciencias Ambientales (IUCA), Universidad de Zaragoza, Zaragoza, Spain.ORCID http://orcid.org/0000-0001-7663-1202
Stefan BrönnimannOeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID40517157
PMCPMC12167379

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.