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Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000
Abstract
Interest in attributing the risk of damaging weather-related events to anthropogenic climate change is increasing. Yet climate models used to study the attribution problem typically do not resolve the weather systems associated with damaging events such as the UK floods of October and November 2000. Occurring during the wettest autumn in England and Wales since records began in 1766, these floods damaged nearly 10,000 properties across that region, disrupted services severely, and caused insured losses estimated at £1.3 billion (refs 5, 6). Although the flooding was deemed a 'wake-up call' to the impacts of climate change at the time, such claims are typically supported only by general thermodynamic arguments that suggest increased extreme precipitation under global warming, but fail to account fully for the complex hydrometeorology associated with flooding. Here we present a multi-step, physically based 'probabilistic event attribution' framework showing that it is very likely that global anthropogenic greenhouse gas emissions substantially increased the risk of flood occurrence in England and Wales in autumn 2000. Using publicly volunteered distributed computing, we generate several thousand seasonal-forecast-resolution climate model simulations of autumn 2000 weather, both under realistic conditions, and under conditions as they might have been had these greenhouse gas emissions and the resulting large-scale warming never occurred. Results are fed into a precipitation-runoff model that is used to simulate severe daily river runoff events in England and Wales (proxy indicators of flood events). The precise magnitude of the anthropogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.
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“There is now an increasingly strong body of literature which highlights the causal linkages between climate change and extreme weather events (see [45–50]).”
From Climate change and mental health: risks, impacts and priority actions (2018) · cites this paper as [49]
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“we do know that because of climate change, extreme weather is more generally on the rise, making extreme weather events more frequent, intense, and complex.”
From Climate change and mental health: risks, impacts and priority actions (2018) · cites this paper as [49]
In the citing paper
“while we cannot say with certainty that any one specific extreme weather event is directly caused by climate change”
From Climate change and mental health: risks, impacts and priority actions (2018) · cites this paper as [49]
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Self-citation
Metadata
- Authors
- Pall, P., Aina, T., Stone, D. A., Stott, P. A., Nozawa, T., Hilberts, A. G. J., Lohmann, D., & Allen, M. R.
- Affiliations
- University of Oxford (GB)
- Met Office (GB)
- National Institute for Environmental Studies (JP)
- Risk Management Solutions (United Kingdom) (GB)
- Corresponding author
- Pall, Pardeep
- Venue
- Nature
- Published
- 2011-02
- Volume
- 470
- Issue
- 7334
- Pages
- 382-385
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2060677109
- Cited by
- 871
- References
- 30
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- FWCI
- 70.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- CentAUR (University of Reading) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Natural Environment Research Council
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Environmental Science › Global and Planetary Change › Flood Risk Assessment and Management
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Keywords
- anthropogenic climate change, flood risk, event attribution, greenhouse gas emissions, climate model simulation, rainfall-runoff modeling, river discharge, heavy rainfall, distributed computing, hydrometeorology, climate change impacts on floods
- MeSH terms
- Disasters, England, Human Activities, Models, Theoretical, Rain, Seasons, Wales, Greenhouse Effect, Risk Assessment, Rivers, Floods, Global Warming
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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