Evidence map›Paper›PMID 40021700›Full record

ArticleScientific data2025

CETD, a global compound events detection and visualisation toolbox and dataset.

Cong Yin, Mingfang Ting, Kai Kornhuber, Radley M Horton, Yaping Yang, Yelin Jiang

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

6 authors.

Cong YinInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. cy2722@columbia.edu.
Mingfang TingLamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA.ORCID http://orcid.org/0000-0002-4302-4614
Kai KornhuberLamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA.ORCID http://orcid.org/0000-0001-5466-2059
Radley M HortonLamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA.
Yaping YangInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. yangyp@igsnrr.ac.cn.
Yelin JiangLamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Compound events (CEs) are attracting increased attention due to their significant societal and ecological impacts. However, their inherent complexity can pose challenges for climate scientists and practitioners, highlighting the need for a more approachable and intuitive framework for detecting and visualising CEs. Here, we introduce the Compound Events Toolbox and Dataset (CETD), which provides the first integrated, interactive, and extensible platform for CE detection and visualisation. Employing observations, reanalysis, and model simulations, CETD can quantify the frequency, duration, and severity of multiple CE types: multivariate, sequential, and concurrent events. It can analyse CEs often linked to severe impacts on human health, wildfires, and air pollution, such as hot-dry, wet-windy, and hot-dry-stagnation events. To validate the performance of CETD, we conduct statistical analyses for several high-impact events, such as the 2019 Australian wildfires and the 2022 European heatwaves. The accessibility and extensibility of CETD will benefit the broader community by enabling them to better understand and prepare for the risks and challenges posed by CEs in a warming world.

Identifiers

PMID40021700
PMCPMC11871071

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.