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Attributing a deadly landslide disaster in southeastern Brazil to human-induced climate change

Barbosa, Maria Lucia Ferreira ORCID: https://orcid.org/0000-0002-4702-2974; Veiga, Rafaela Quintella; Quevedo, Renata Pacheco; Dutra, Débora Joana; Pessôa, Ana Carolina Moreira; de Medeiros, Thaís Pereira; Burton, Chantelle; Liu, Yuexiao; Armond, Nubia Beray; de Abreu, Rafael C.; Li, Sihan; Lott, Fraser C.; Bortolozo, Cassiano Antonio; Sparrow, Sarah ORCID: https://orcid.org/0000-0002-1802-6909; Anderson, Liana Oighenstein. 2025 Attributing a deadly landslide disaster in southeastern Brazil to human-induced climate change. Weather and Climate Extremes, 50, 100811. 15, pp. 10.1016/j.wace.2025.100811

Abstract
Petrópolis was hit by a devastating disaster in February 2022, when it rained 252.8 mm within 3 h, leading to 200 lost lives and hundreds of people being displaced. Here, we aimed to attribute the extreme rainfall event that led to several landslides in Petrópolis, assess how Land Use and Land Cover changes (LUCC) from 1985 to 2021 contributed to it, and quantify their socioeconomic impacts. For this, we compared natural-only forcing (NAT) and natural and anthropogenic forcing combined (ALL) scenarios of the HadGEM3 ensemble models with observation data. We computed the trends in LUCC and quantified the landslide's socioeconomic impacts from official datasets. Human-induced climate change made this extreme event 45 % and 71 % more likely in short and long-term rainfall, respectively. Recurrence period dropped from 2.36 years (NAT) to 1.63 years (ALL) in the short-term and from 5.66 years (NAT) to 3.31 years (ALL) in the long-term. Landscape trends show an increase in forest formations, but unprotected hilltops that collapsed presented more than 40 % of their area as farming. The total economic loss was more than USD 22 million, with 1 078 people directly affected. The study's findings are valuable in understanding how changes in extreme weather events and land use are affecting our society. We highlight the need for adaptation measures and for more research addressing the attribution of extreme events, especially those associated with disastrous landslides.
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