#7 - Dr Friederike Otto special - Real Time Attribution

This week I was super lucky to hear from Dr Friederike Otto and this post is entirely inspired by our discussion. Lead scientist on the international project  World Weather Attribution (WWA) – Dr.Otto aims to speed up the analysis and communication of the impact climate change has on extreme weather events under a new science: Real Time Attribution.



So isn’t this essentially EEA? – Indeed this science follows the same principles we discussed in EEA, but it just tries to do so far more rapidly.

Dr.Otto then directed me to the incredible overview of the real-time peer-reviewed studies they have already done, and I suggest you take 30 seconds to have a quick scroll (all open-access and on the website). She said that not all the listed studies were real-time, so to check out the European heat waves, floods in Paris, storm Desmond and the Kenyan and Somalian drought (…remember this from last week?)

One thing we learnt from the EEA post is that attribution for hurricanes and other cyclones is hardly a simple exercise, so the fact that the WWA has already completed a real-time study only 3 months after Hurricane Harvey hit Texas is a tribute to the potential of this science...now just waiting for peer-review. 

The most exciting part of our exchange was actually when Dr.Otto said they had only very recently published a paper proving the robustness of real-time analysis; they re-performed the real-time study on Storm Desmond (2015) this year with more data and more information. So, lets have a quick look.



Storm Desmond Fact File

  • 4-6th December, 2015
  • North England and South Scotland
  • An Atlantic Storm that provisionally set a new record for the greatest amount of rainfall recorded in the UK in 24 hours (341.1mm - Cumbria).
  • A rare 'red action' was issued
  • Caused severe floods, affecting 5000 homes and businesses, causing power-cuts for 60,000 people and killing at least 3 people

It was the excessive nature of the rainfall event that led to media and the public asking the question "was this event caused by climate change?", a question Dr.Otto is very familiar with. Normally, answers given are guesses with no relevant scientific basis, but with Desmond the story was very different.

I googled "Storm Desmond climate change" and the first hit was this:



Science was able to give reliable answers within 5 days of the extreme event!

So what did the team find?

Using the multi-method approach discussed in the EEA post (if different models answer the same question, scientists can better identify model uncertainty), the analysis was focussed on the combined effect of thermodynamically (heat) driven increase in precipitation and potential changes in the atmospheric circulation producing this type of event. It was found a thermodynamic increase (so more moisture in the air) was “purely” responsible, caused by a half a degree warming of the upstream North Atlantic. So, was this caused by us?:

The real-time attribution study concluded anthropogenic climate change increased the likelihood of the event by 40 percent, and in the re-analysis study 2 years later, anthropogenic climate change was found to have increased the likelihood of the event by 59 percent. They believed the similarity in the results are certainly proof of the competence of real-time, with differences accountable to the initial limitation of available data.

Some challenges, however, were flagged, and are very similar to those discussed in the EEA post:

  1. The paper is limited as it only takes into account trends in precipitation, not other factors like existing flood defences and the increasing exposure of flood prone-areas as development continuously grows (So very similar to the issues discussed in the EEA post).

  1. Model Resolution: the study area is mountainous so there was heavy precipitation recorded at some stations and none in those nearby.

  1. Capturing the nature of precipitation in such 'hilly' regions requires high resolution models, but the large ensembles of regional climate models only covered a 50km resolution. The model has been shown to be bias to low precipitations, and because of the terrain, a resolution of under 10km was needed.

  1. Framing of the question was also shown to be an issue, with the differences that did arise from results of each of the three methods owing in part to the different framing of the attribution questions. The team said this could not be avoided as the different methods were reconstructing different scenarios. 

Taking this all into account, I think this is fantastic work. Of course, this only shows attribution capability for extreme precipitation events in temperate climate zones, but it wonderfully case-studies the amazing potential of the new science ‘real-time’ attribution!



Until then next time...


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