> One reason for this is that in Herrington’s words, “the scenarios do not significantly diverge until 2020.” After that point, the scenarios start to diverge drastically ... This sounds more like a selection bias. If any model drastically diverged from reality earlier, then it would have been already discarded, and we won't be talking about it. So, we'll be only talking about models that start to diverge around 2020…
I am a huge fan of Nassim Taleb and his book Fooled By Randomness really impacted the way I look at a lot of doom and gloom scenarios. His notion of fat tailed events/tail risks along with survivors confirmation bias is a central theme of many of the risks he describes. So as an example, if in October 2019 someone said a virus outbreak that could be largely prevented would be lead cause of over 100k deaths over clima…
Firstly, why would someone laugh? Pandemics with a 100k death toll are a fairly regular occurrence, even in modern society. OTOH if you said 1M + most of the world under some form of home quarantine, lockdown or travel restrictions for well over a year, that would have been laughed at.
Second, it's hard to attribute deaths to climate change directly. Natural disasters kill people every year. Who can say with absolute certainty that the death toll in this or that incident would have been lower if not for climate change?
Third, on a longer timescale climate change absolutely has the potential to kill more people than Covid.