Marylou Athanase, Antonio Sánchez-Benítez, Eva Monfort, Thomas Jung, Helge F. Goessling
{"title":"How climate change intensified storm Boris’ extreme rainfall, revealed by near-real-time storylines","authors":"Marylou Athanase, Antonio Sánchez-Benítez, Eva Monfort, Thomas Jung, Helge F. Goessling","doi":"10.1038/s43247-024-01847-0","DOIUrl":null,"url":null,"abstract":"Disentangling the impact of climate change on environmental extremes is of key importance for mitigation and adaptation. Here we present an automated system that unveils the climate change signal of the day in near-real-time, employing a set of innovative storyline simulations based on a coupled climate model. Its potential to complement probabilistic assessments is showcased for storm Boris, which brought record-breaking rainfall over Central and Eastern Europe in September 2024, leading to devastating floods. Our near-real-time storylines suggest that storm Boris deposited about 9% more rain due to human-induced warming. The area impacted by the same storm’s extreme rainfall (>100 mm) was 18% larger and would continue expanding in a future warmer climate. Results from our prototype storyline system are disseminated publicly via an online tool. The case of Storm Boris demonstrates the potential of near-real-time storylines for rapid evidence-based climate change communication. Rapid and relatable climate change information for the attribution and projection of extreme events such as the devastating rainfall in Europe in September 2024 can be provided with an automated storyline approach within days of the event.","PeriodicalId":10530,"journal":{"name":"Communications Earth & Environment","volume":" ","pages":"1-5"},"PeriodicalIF":8.1000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43247-024-01847-0.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications Earth & Environment","FirstCategoryId":"93","ListUrlMain":"https://www.nature.com/articles/s43247-024-01847-0","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Disentangling the impact of climate change on environmental extremes is of key importance for mitigation and adaptation. Here we present an automated system that unveils the climate change signal of the day in near-real-time, employing a set of innovative storyline simulations based on a coupled climate model. Its potential to complement probabilistic assessments is showcased for storm Boris, which brought record-breaking rainfall over Central and Eastern Europe in September 2024, leading to devastating floods. Our near-real-time storylines suggest that storm Boris deposited about 9% more rain due to human-induced warming. The area impacted by the same storm’s extreme rainfall (>100 mm) was 18% larger and would continue expanding in a future warmer climate. Results from our prototype storyline system are disseminated publicly via an online tool. The case of Storm Boris demonstrates the potential of near-real-time storylines for rapid evidence-based climate change communication. Rapid and relatable climate change information for the attribution and projection of extreme events such as the devastating rainfall in Europe in September 2024 can be provided with an automated storyline approach within days of the event.
期刊介绍:
Communications Earth & Environment is an open access journal from Nature Portfolio publishing high-quality research, reviews and commentary in all areas of the Earth, environmental and planetary sciences. Research papers published by the journal represent significant advances that bring new insight to a specialized area in Earth science, planetary science or environmental science.
Communications Earth & Environment has a 2-year impact factor of 7.9 (2022 Journal Citation Reports®). Articles published in the journal in 2022 were downloaded 1,412,858 times. Median time from submission to the first editorial decision is 8 days.