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Nature Communications is an open access journal that publishes research from all areas of the natural sciences. Papers published by the journal represent important advances of significance to specialists within each field.
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The Sendai Framework Voluntary Commitments (SFVC) online platform allows stakeholders to inform the public about their work on DRR. The SFVC online platform is a useful toolto know who is doing what and where for the implementation of the Sendai Framework, which could foster potential collaboration among stakeholders. All stakeholders (private sector, civil society organizations, academia, media, local governments, etc.) working on DRR can submit their commitments and report on their progress and deliverables.
Items: 61
This study is built around conceptualising and developing the process-based links between the edge effects of land fragmentation on observed land surface and human ignition variables that can conceivably affect fire probability and behaviour.
This study estimates heat-related mortality at different scales, such as regional heat risk during a specific heatwave, annual and nationwide heat risk, or future heat risk under climate change scenarios in Germany.
Using statistical models trained on a large multi-country household survey dataset, this study projects AC adoption and energy use to mid-century at fine spatial resolution worldwide.
This study investigated the 519 most destructive wildfires in the contiguous U.S. between 1999 and 2020, examining direct and indirect pathways of wildfire-driven impacts on human migration.
The authors provide a methodology that quantifies physical risks on geolocalized productive assets, considering their exposure to chronic and acute impacts (hurricanes) across the scenarios of the Intergovernmental Panel on Climate Change.
This study estimates the mortality attributable to extreme heat and cold events, which dominate the UK health burden from weather hazards, in England and Wales in the period 2020-2022, during which the COVID-19 pandemic peaked in terms of mortality.
This study proposes a high tide flood (HTF) thresholding system that leverages machine learning (ML) techniques to estimate SLR and HTF thresholds at a relatively fine spatial resolution (10 km) along the United States’ coastlines.
In this study researchers demonstrate a comprehensive floodplain inundation hindcast of the 2021 European Summer Flood illustrating these possibilities for better disaster preparedness, offering a 17-hour lead time for informed and advisable actions.