Journal article

Embracing the complexity of extreme weather events when quantifying their likelihood of recurrence in a warming world

Luke J Harrington, Sophie Lewis, Sarah E Perkins-Kirkpatrick, Andrew D King, Friederike EL Otto

Environmental Research Letters | Institute of Physics (IoP) | Published : 2019

Abstract

Global-average temperatures are a powerful metric for both long-term climate change policy, and also to measure the aggregate fluctuations in weather experienced around the world. However, here we show how the consideration of anomalies in annual temperatures at the global land-average scale, particularly during extremely hot years, tends to overestimate the perceived severity of extreme heat actually felt by local communities during these events. Thus, when global-mean temperatures are used as a proxy to infer the role of climate change on the likelihood of witnessing hot years, the component of extreme event risk attributed to human influence can also be overstated. This study suggests mul..

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University of Melbourne Researchers

Grants

Awarded by MaRIUS project: Managing the Risks, Impacts and Uncertainties of droughts and water Scarcity - Natural Environment Research Council


Awarded by Australian Research Council


Funding Acknowledgements

The authors acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and thank the climate modelling groups for producing and making available their model output. For CMIP the US Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. LJH acknowledges support from the MaRIUS project: Managing the Risks, Impacts and Uncertainties of droughts and water Scarcity, funded by the Natural Environment Research Council (NE/L010364/1). SP-K is supported by Australian Research Council grant number FT170100106. ADK is supported by Australian Research Council grant number DE180100638. SL is supported by Australian Research Council grant number DE160100092.