On the attribution of the impacts of extreme weather events to anthropogenic climate change
[1];
[4];
[3];
[6];
- Univ. of New South Wales, Canberra, NSW (Australia); Univ. of New South Wales, Sydney, NSW (Australia)
- National Institute of Water and Atmospheric Research (NIWA), Wellington, Aotearoa (New Zealand)
- Univ. of Bristol (United Kingdom)
- Univ. of Melbourne (Australia)
- Geological and Nuclear Sciences Institute (GNS Science), Wellington (New Zealand)
- Victoria Univ. of Wellington (New Zealand). New Zealand Climate Change Research Institute
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Investigations into the role of anthropogenic climate change in extreme weather events are now starting to extend into analysis of anthropogenic impacts on non-climate (e.g. socio-economic) systems. However, care needs to be taken when making this extension, because methodological choices regarding extreme weather attribution can become crucial when considering the events’ impacts. The fraction of attributable risk (FAR) method, useful in extreme weather attribution research, has a very specific interpretation concerning a class of events, and there is potential to misinterpret results from weather event analyses as being applicable to specific events and their impact outcomes. Using two case studies of meteorological extremes and their impacts, we argue that FAR is not generally appropriate when estimating the magnitude of the anthropogenic signal behind a specific impact. Attribution assessments on impacts should always be carried out in addition to assessment of the associated meteorological event, since it cannot be assumed that the anthropogenic signal behind the weather is equivalent to the signal behind the impact because of lags and nonlinearities in the processes through which the impact system reacts to weather. Whilst there are situations where employing FAR to understand the climate change signal behind a class of impacts is useful (e.g. ‘system breaking’ events), more useful results will generally be produced if attribution questions on specific impacts are reframed to focus on changes in the impact return value and magnitude across large samples of factual and counterfactual climate model and impact simulations. We advocate for constant interdisciplinary collaboration as essential for effective and robust impact attribution assessments.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- Australian Research Council; Ministry of Business, Innovation, and Employment of Aoteaora New Zealand; NERC; USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1855366
- Journal Information:
- Environmental Research Letters, Journal Name: Environmental Research Letters Journal Issue: 2 Vol. 17; ISSN 1748-9326
- Publisher:
- IOP PublishingCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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