Government Climate Policy and Ambiguous Data
Do we understand what's driving changes in extreme weather event frequency and severity?
Understanding large, complex systems is hard. That, after all, is why they call them “complex”. And there’s probably nothing more complex than the interplay between our physical environment, the billions of human beings who live in it, and the global economy.
It’s perfectly reasonable to ask whether human actions are changing the environment, whether environmental trends are changing the way human beings live (and die), and how all of it is is impacted by the economy. It’s probably not reasonable to expect clear and unambiguous answers. And it’s probably equally unreasonable to base expensive government programs on ambiguous data.
I’m not going to try to address the big-picture questions. Even fully understanding what’s already happened is well beyond my humble capacity, and predictions are completely out of scope. But I would like to discuss the oft-repeated claim that, in relation to historic norms, extreme and destructive weather events are becoming measurably more frequent.
To be honest, there are many strongly-held opinions and nearly as many large datasets flying around relating to this topic. Historical hurricane and tropical storm data produced by the Geophysical Fluid Dynamics Laboratory of the US Government's National Oceanic and Atmospheric Administration (NOAA), for example, suggests that there has been no statistically significant change in the frequency or intensity of Atlantic hurricanes over the past century. But that’s just one dataset covering just one event category. And it’s only tangentially relevant to what’s happening in Canada.
So let me introduce you to Public Safety Canada’s Canadian Disaster Database (CDD). The database attempts to enumerate and describe all the disasters impacting Canada over the past 120 years. To build a picture of trends over time, I selected the approximately 900 meteorological and hydrological events beginning in 1900 that involved significant destruction.
The data isn’t perfect. As the maintainers themselves warn:
The CDD may not be suitable for comparative analysis because of differences in jurisdictional responsibilities, the type of data that is available, and how it is collected and used over time.
With that in mind, let’s see what the data at least appears to show us. Here’s a chart displaying the number of annual disaster-level events as measured in decade averages.
Although it would be hard to see from the graph, the numbers themselves show us that fully 25% of the events took place just since 2008.
The scope of the dataset we’re working with would seem to be large enough to accurately represent statistical trends. And the frequency of events is certainly rising. But does it necessarily follow that changing climate conditions are fully responsible for all this? Perhaps there are some other contributing factors to consider, including:
Innovations in detection and reporting - including improved record keeping protocols and developments in satellite imagery and communications - might mean we’re missing fewer events than we used to.
The growth of urban settlement might mean that weather events that, in the past would have been unremarkable, now impact vulnerable regions and infrastructure.
Urbanization itself could increase our vulnerability to flood damage through reduced drainage and poorly managed waterways.
I dove deeper into the data to see if it could help us understand things better.
Fatalities
Perhaps the most important metric is the number of deaths caused by weather events. Well as it turns out, when it comes to events that cause at least one fatality, 25% happened between 1950 and 1980 (a period of 30 years), 25% between 1980 and 1999 (19 years) and 25% between 1999 and 2020 (11 years). The fatality-event rate is clearly increasing.
The total number of weather event-related fatalities reported in the database since 1900 is 4,662. But 3,007 of those (64%) happened in events before 1960 - even though the period between 1900-1960 represents only half of the total years being reported. So we can conclude that, although there were more reported events in later years, they were increasingly less deadly. That’s good news.
Curiously, the first 80 years of the 20th Century saw an average of 17.8 weather-related injuries or infections each year. Since 2000, that rate was similar: 19.8 per year. But the 20 years in between (1980-1999) saw a total of 2,350 injuries, which translates to 117.5 per year! I have no idea what was going on there, but I’m grateful I made it through.
Financial Costs
Using the CDD’s normalized estimates for the financial costs of weather event disasters, here are the numbers for those decades with sufficient reported data:
These clear cost increases might indeed represent the impact of more severe weather events. But they could also at least in part reflect the vulnerability of our growing infrastructure footprint. In other words: we’ve got more delicate stuff out there to destroy. More widespread reliance on insurance coverage - and the easy-access to insurance claim data - might also influence what we’re seeing.
Utility Outages
This graph represents 16 years’ worth of service outages specifically due to weather events. The numbers measure individual utility customers effected. As you can see, the trend line indicates very modest increases.
The spikes in 2015 and 2016 are largely due to a few mega-events. 1.5 million customers in the BC Lower Mainland lost power due to a storm on August 29, 2015. And 750,000 customers in Ontario, Quebec, and the Maritimes lost power in a storm beginning on February 24, 2016.
But why did numbers drop in subsequent years? Where those 2015-6 events outliers? Or did utilities just get better at protecting their equipment?
Disaster Types
Have specific categories of disaster noticeably increased? Well, the data tells us that there were only eight heat events recorded across Canada in the past 120 years, and they were pretty evenly distributed in time. Large scale wildfires, as you can see from this graphic, are another story:
These dangerous and expensive events are clearly trending up. Although, as before, there’s considerable debate over the primary causes. There are those who argue that at least some of the intensity and frequency of recent fire seasons can be blamed on forestry mismanagement, leading to an over-availability of consumable fuel (i.e., dead trees and older growth).
My point with all this is not to discount the possibility that a changing climate has led to changing weather patterns. Rather, let’s consider the complexity of the systems we’re observing, the imperfect data we’re working with, and the not-infrequent presence of multiple interpretations of that data. And then consider the scope of government spending meant to solve problems that we don’t really understand.
Does the first consideration justify the second?
I’m not a data guy so apologies if I’m misunderstanding something but on your first chart the first increment on the y axis is 0 which makes it seem like your trend line starts in the negative. I notice that you also started the utility chart in a similar way. Is there something about the data that led you to set up the chart that way?
Thank you, Sir!
I am a climate sceptic. Please note: a sceptic but not a denier. You have very simply summarized why I am a sceptic: "It's complicated!"
I keep hearing that "The science is settled!" when speaking about climate. So, I then ask if the relationship between carbon dioxide and global warming is PROVEN scientifically and the most intelligent response that I get is that 97% of all "scientists" [more on "scientists" below] agree that that is the case. In turn, I have tried to chase down from whence that 97% number arises and I am (not) surprised to find that it is nebulous at best and is based on a real, real, real small data set that has been misinterpreted. Certainly, a group of people amounting to 97% did say SOMETHING (it is very interesting just what they said!) but did that justify all the hoopla? Not really.
So, I am skeptical when the assertion of an absolute relationship is made. That does not mean that there is no relationship but, as you note, it's complicated!
As to "scientists" I am aware that there are many people with academic credentials who claim to be climate "scientists" and that is fine. I am also aware that there are many, many more people who have solid technical credentials in various related fields who have raised questions and sometimes objections about the "settled" climate science. Finally, I am aware that where solidly credentialed academics have questioned the "settled" climate science many times they have been shouted down by the mainstream, have been denied funding for studies, have been denied the ability to publish findings, etc. Not at all a good way to deal with "science" as science is all about questioning and challenging ideas. So, again, it's complicated!
I could, of course, go on and try to defend my "position" - which is not a position but a questioning - but all I want to do is to agree with you: it's complicated! And the setting of government policy on a foundation of sand is, to me, acceptable for small, exploratory kinds of actions but it is not whatsoever a good way to set grand, expensive, bold and society changing kinds of things.