Honister Pass, Cumbria, 13.44 inches (341.4 mm) of rain fell between 6:30 pm on Dec. 4th to 6:30 pm on Dec. 5th – a new national record for rainfall accumulation in a 24-hour period. The U.K. Met Office issued a rare red “take action” warning — the first since February 12, 2014 — for parts of Cumbria and the Scottish Borders as a result of this powerful storm.
The excessive nature of this record rainfall event, which led to flooding of more than 5,000 homes and businesses and left over 60,000 people without power, has led many to question whether climate change played a role, especially since there have been several large floods over the last decades.
Recent advances in the science of extreme event attribution now make it possible for scientists to, using peer-reviewed methods, rapidly provide an objective, quantitative initial estimate of the relative contribution of global warming to specific classes of extreme weather events. As a result, these analyses provide estimates of the return-time period of the event both today and in the past — before there was a strong human influence on the climate system. The ratio of these is a measure of the extent to which climate change affected the likelihood of the event. Overall, extreme event attribution can provide valuable information to decision-makers faced with tough questions about changing risks and to underpin adaptation strategies at a more local level.
To assess the potential link between the U.K.’s record rainfall and man-made greenhouse gases in the atmosphere, we conducted independent assessments using three peer-reviewed approaches. These approaches involve statistical analyses of the historical temperature record, the trend in a global coupled climate model, and the results of thousands of simulations of possible weather with a regional climate model. Applying multiple methods provides scientists with a means to assess confidence in the results.
Based on these three approaches – all of which are in agreement – the team found that global warming increased the likelihood of the heavy precipitation associated with a storm like Desmond. The increase is small but robust. It should be noted that a positive attribution for an extreme rainfall event like Desmond is still somewhat rare. Evidence of this can be found in a summary of the events analysed as part of the annual BAMS Special Issue on Explaining Extreme Events from a Climate Perspective (pdf, 5,4 MB). Whereas the vast majority of heat events studied found a climate change signal, less than half of the papers looking at extreme rainfall events found a human influence.
By comparing recent extreme events with the historical record and climate model simulations, the team found that an event like this is now roughly 40% more likely due to climate change than it was in the past, with an uncertainty range of 5% to 80%. It is important to note that this analysis only considers externally driven changes in precipitation. It does not take into account other factors that influenced the flooding. While our analysis provides evidence that climate change has aggravated the flood hazard in this part of the world, risk is also determined by trends in exposure and vulnerability. As events like this become more common in the U.K., it will be important to discuss both changing risks associated global warming and the overall adequacy of flood defences.
Data from NASA’s Integrated Multi-satellitE Retrievals for GPM (IMERG) were used to estimate rainfall for the period from November 30 to December 7, 2015. This analysis found that some rainfall near the Irish Sea measured over 392 mm (~15.4 inches) during this period. As much as 304 mm (~12 inches) of rain were reported to have fallen in only 24 hours. Credits: SSAI/NASA/Hal Pierce.
24 hour maximum precipitation
Results were checked against local station data. Over the large area, the ECMWF analysis gives an average precipitation of 36.4 mm on 5 December (0–0 UTC)
ECMWF 24-hour precipitation forecast; ECA & D
Global coupled model: EC-Earth 2.3 model (16 runs, 1861–2015) 100 km resolution
weather@home HadRM3P at 50km resolution over Europe, driven by HadAM3P & OSTIA SSTs
5% to 80% more frequent
Method #1 (KNMI)
Method #2 (KNMI)
Global Coupled Model: 10%-80%
Method #3 (Oxford)
Regional Large-ensemble: 5%-50%
This analysis is available from Hydrology and Earth System Sciences (HESS) (pdf, 806 KB).