Litcius/Paper detail

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

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

2025Scientific Data13 citationsDOIOpen Access PDF

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.

Topics & Concepts

ToolboxVisualizationComputer scienceHuman healthMultivariate statisticsData scienceExtensibilityClimate changeEnvironmental scienceData miningEnvironmental resource managementEcologyMachine learningEnvironmental healthBiologyMedicineProgramming languageOperating systemFire effects on ecosystemsMeteorological Phenomena and SimulationsClimate variability and models