In my previous post, I explained how we can move from “one size fits all” thinking to solutions that help us design buildings, where we spend 90% of our time, to keep us safer and healthier in a world that, due to increasing pandemics and climate change, is unlike any we’ve experienced before. Here, I’ll give a first lesson about why high-level summary numbers like averages can be dangerously—even fatally—misleading.

If you’re like me, you might find it hard to translate tiny changes in temperatures from one year to the next to the cataclysmic impact that many scientists tell us that we’ll see from climate change. We’re told that a climate increase of five degrees per decade will create massive global issues, but here in Denver where I currently live, we can see temperatures swing from below freezing to over 70°F in a single day: a tremendously larger amount. How can that tiny fraction of a degree per year possibly matter?

It turns out that the reason that the one degree matters is due to an over-simplification that can hurt us not only when thinking about climate, but also pandemics, income inequality, and many other domains. It has to do with the fact that big but rare events aren’t very well captured by an average.

Extreme but very rare events.

Why should the townspeople of
Pompeii be concerned about
natural phenomena that only
changes the annual average air
temperature by less than 3
°F?

Consider the town of Pompeii during the year 79 AD. As a balmy seaside town nestled against the slope of Mount Vesuvius in the picturesque Bay of Naples, its inhabitants enjoyed an average annual air temperature of somewhere around 65°F. But on August 24 of that year, Vesuvius erupted sending burning gases with temperatures of around 1000°F through the town incinerating everything in their path. As devastating as this was, a single day of 1000°F only raised the year’s average daily air temperature by about 2.5°F. If annual averages were the only information we considered, 79 AD in Pompeii was a slightly warmer year than usual—hardly a situation worthy of serious concern. As you can see with this example, averages, when assessing outlier risks, often make very bad metrics.

Small changes in the average create big impact on deaths

As you can see in the blue line in the chart below, the average annual temperature is expected to increase only a few degrees from 2010 through 2050. But the impact that this change in temperature has on the number of days above 95 degrees is much greater, as shown with an orange line. This is because that average measurement obscures the fact that temperatures bounce around.

And, even worse, the impact that this change in temperature has on the likelihood of deaths is even greater, as shown in grey.

Source: Union of Concerned Scientists, Quantellia LLC

We can diagram this in a simple causal model:

Source: Quantellia LLC

My next post dives deeper into this dynamic, specifically the effect of critical thresholds and nonlinear effects.