Angry Weather, Friederike Otto. Vancouver: Greystone Books, 2020.
Summary: A description of the use of attribution science to assess the probability that anthropogenic-caused climate change is a factor in particular extreme weather events.
You’ve heard the discussions. An extreme drought results in unprecedented forest fires. A record and extended heatwave results in hundreds of heat-related deaths. A hurricane stalls over a major coastal city and dumps record amounts of rainfall resulting in extensive flooding, property damage, and deaths. Record spring rainfalls flood farmlands resulting in major crop losses. Commentators will cite these as yet more examples of climate change, while those denying climate change will argue that these are rare but naturally occurring events.
It turns out that many climate scientists are quiet during these discussions. Weather is complicated. Most climate scientists observe long term trends and the impacts these have as inputs to weather systems. But they are reluctant to opine on individual events. In the last decade, a new area of climate science has developed called attribution science that is used to determine to what extent anthropogenic climate change has contributed to the magnitude or probability of an individual event. Friederike Otto is one of the scientists on the forefront of this emerging field and this book serves as a description of this field and its uses for the lay reader interested in climate research. (For those wanting a more technical version of this material, this article, co-authored by this author, goes deeper into their research methodologies and studies of climate events.)
She uses her team’s real-time research of Hurricane Harvey that dropped over 40 inches of rain on the Houston metro area as an example of attribution science, which has also studied European heatwaves. She details how they isolated the variable they would look at, which in this case was rainfall amounts. Then there is the work of collecting, modelling and analyzing large amounts of data, both about this particular storm and weather data going as far back as possible, in many cases from 30 to 100 years. Using peer-reviewed mathematical modelling, within three weeks the team estimates that climate change makes an event like Harvey three times more likely at the current state of change. In Harvey’s case, this was an event that would occur every 9,000 years under historic conditions, but three times more probable due to climate change. That’s still very unlikely, but also signals the increased likelihood of lesser flooding events.
The account of their study of Harvey is interlaced with explanations about how rising global temperatures from CO2 emissions contribute to changes in weather patterns contributing to more extreme events. She also describes the fossil fuel industry’s spending to cast doubts on climate research. She is honest about the number of weather events they studied where climate change played little or no part and the kinds of events currently not amenable to this approach. One of the most valuable aspects of this research is the information it gives governmental bodies to take steps to prepare when once rare events–floods, storms, droughts, can be predicted to be more common. She describes steps taken in Europe for the sheltering of vulnerable populations during heat waves as an example. If flooding becomes more popular, permits for construction in what were once infrequent flood plains need to be re-evaluated.
There are aspects of this work that are controversial. For one thing, studies like the one on Harvey, are published in real-time, and only subsequently in journals that are peer-reviewed. The argument is that the models are peer-reviewed, as are subsequent articles, but that in the elapse of time, and given the obscurity of most academic journals, this information is most timely and helpful in policy discussions in the immediate context of an event rather than when it is in the rear view mirror.
The other controversial element is to use the results of attribution science in lawsuits for damages against fossil fuel companies who have contributed to climate change. She describes such efforts. I am concerned that these models, built on multiple variables and probabilities may be better to use in future planning than to assess damages arising from past actions, whether the actors were aware of or not of the possible consequences of the actions.
I don’t think the energy companies are without fault in all this, but there seemed a bit too much of a “go after ExxonMobil” in this book for my liking, and I think this can backfire on what seems to be an emerging and useful area of research. Far better it seems to me to use this research for good public policy decisions going forward. Also, the author notes how even 30 years of data is a bare minimum in climate research. This area of research is in its infancy, and while promising, will be proven out more definitively as they continue to produce studies of events, particularly ones with similar variables. But if I were a planner concerned with both the economic viability and disaster preparedness of my region, I would be paying attention.
Disclosure of Material Connection: I received a complimentary review copy of this book from the publisher via LibraryThing’s Early Reviewer Program. The opinions I have expressed are my own.