Climate change is shaping extreme heat and rain. To what degree human activity has increased the risk of high impact events is of high public concern and still heavily debated. Recent studies attributed single extreme events to climate change by comparing climate model experiments where the influence of an external driver can be included or artificially suppressed. Many of these results however did not properly account for model errors in simulating the probabilities of extreme event occurrences. Here we show, exploiting advanced correction techniques from the weather forecasting field, that correcting properly for model probabilities alters the attributable risk of extreme events to climate change. This study illustrates the need to correct for this type of model error in order to provide trustworthy assessments of climate change impacts.

This work has been supported by the EUropean CLimate and weather Events: Interpretation and Attribution (EUCLEIA) project, funded by the European Union’s Seventh Framework Programme [FP7/2007–2013] under Grant agreement no. 607085 as well as the Horizon 2020 EUCP EUropean Climate Prediction system under Grant agreement no. 776613 and by the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 grant reference RYC-2017-22964. We thank Antje Weisheimer and Tim Palmer from the University of Oxford for their support to conduct this research. We are further indepted to Fraser Lott, Jonas Bhend, Stefan Siegert, Karsten Haustein, and Myles Allen for their help on the analysis and interpretation. O. Bellprat is the corresponding author (omar.bellprat@env.ethz.ch) and carried out the core analysis and writing of the paper. V. Guemas, F. Doblas-Reyes, and M. Donat have all either contributed in the study design or the interpretation of the analysis as well as the writing of the paper

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