Does rapid attribution stand the test of time?

Does rapid attribution stand the test of time?

A recent revisit of an attribution assessment of an extreme weather event carried out in late 2015 by climateprediction.net has found results similar to the 'real-time' analysis just after the event.

During the days immediately after an extreme weather event with large impacts, the question arises what role climate change has played in it. We can now give a first scientific assessment of the effect of climate change in a relatively short time. This updated analysis shows that the real-time estimates are robust for this kind of extreme weather event.

On 4-6 December 2015, the storm "Desmond'' caused very heavy rainfall in northern England and southern Scotland, which led to widespread flooding. A week after the event the climateprediction.net team, together with the World Weather Attribution team, provided an initial assessment of the influence of anthropogenic climate change on the likelihood of one-day precipitation events, averaged over an area encompassing northern England and southern Scotland, using data and methods available immediately after the event occurred.

The analysis was based on three independent methods of extreme event attribution: historical observed trends, coupled climate model simulations and a large ensemble of regional model simulations. All three methods agreed that the effect of climate change was positive, making precipitation events like this about 40% more likely, with a provisional 2.5-97.5% confidence interval of 5-80%.

A new paper [1] published this month in Environmental Research Letters revisits the assessment using more station data, an additional monthly event definition, a second global climate model and regional model simulations of winter 2015/16. The re-analysis of the real-time attribution event shows that it is possible to provide a robust first-guess quantification of the role of anthropogenic climate change in such an extreme event.

The overall result of the analysis is similar to the real-time analysis with a best estimate of a 59% increase in event frequency, but a larger confidence interval that does include no change. It is important to highlight that the observational data in the additional monthly analysis does not only represent the rainfall associated with storm Desmond but also that of storms Eve and Frank occurring towards the end of the month.

[1] Friederike E.L. Otto, Karin van der Wiel, Geert Jan van Oldenborgh, Sjoukje Philip, Sarah F Kew, Peter Uhe and Heidi Cullen: Climate change increases the probability of heavy rains in Northern England/Southern Scotland like those of storm Desmond – a real-time event attribution revisited.