Part 4

This will be the final installment of this mini-debate about climate change and health effects, following a typical format of each person getting to make a statement and a response. Scott makes a lot of complaints about tone, format and fairness while simultaneously trying to shield himself from any similar criticism. I am going to ignore this aspect of his response, and also anything dealing with the media. Rather I am going to focus on logic and evidence.

First I have to point out that Scott did not refute in any way my primary criticism of his logic – the notion that if climate change is having any negative effects it should be seen in the raw data. Rather, when one factor is part of a complex set of factors we can use statistical analysis to tease out its effect, even if the net effect of all factors are not in the same direction. This is the fatal flaw in his premise and methods, and he just dismissed my criticism and doubled down on this strategy. Saying he is quoting the IPCC is not a defense, when he is simply misinterpreting what they said. They are talking about “contributions” from climate change. He doesn’t want to talk about logic, and wants to force us to accept this incorrect framing. Nope – the framing is wrong, and therefore all of his arguments are not valid.

But let’s also delve into the specific claims. The first meaty claim is that climate models are running hot (a now long-debunked climate denying trope). Climate models are used for various things, including estimating climate sensitivity (the amount of warming that would result from a doubling of pre-industrial atmospheric CO2 levels). There are other ways to estimate climate sensitivity, including using historical data. Estimates have become increasingly precise, and now the consensus of evidence is that sensitivity is between 1.5 and 4.5C. The “hot model problem” that Scott is referring to is that the latest evaluation of climate models from CMIP6 shows that 10 of the 55 models looked at estimated sensitivity at >4.5 C (up to 5.6 C), i.e. “running hot”. The other 45 models are fine, and agree with historical data.

The eventual solution to this problem was two-fold. First, many experts recommended not treating all models as equal but selecting and weighting them based on their “skillfulness” – which is how accurately the models align with past warming. If we eliminate the less skillful models, the “running hot” problem goes away. Second, researchers have already found out the cause of the hot model problem, the way clouds were being rendered by the models. Clouds are the most difficult thing to deal with in climate models, and older models didn’t even attempt to deal with them. When cloud modeling was introduced, it made some models runs hot. This has now essentially all been fixed.

Meanwhile, reviews show that climate models are really good at predicting actual warming. But like all science, it’s messy, it’s complicated, and different methods may produce different results. Science grinds forward by looking at all the evidence, incrementally improving our evidence and theories, and resolving apparent contradictions. This is a good example of science at work (and a good example of why it takes so much more space to explain a misleading claim than to make one).

Regarding forest fires and heat waves, Scott writes:

“While I appreciate your reference to increasing forest fires globally, the great majority (70%) of the fires reported in this study exist in the northern boreal area of Russia/Siberia. The p value for this series happens to be non significant (p>0.05 look closely at the graph).”

Why does it matter that the majority of forest fires are in Siberia? The data clearly shows that forest fires are increasing globally, but of course not evenly distributed. Climate change and the effects of climate change are not evenly distributed. Scott claimed, misleadingly, that “burn area” has been decreasing, but this is clearly due to reduced fires on plains and savannas due to agricultural development. Meanwhile, forest fires are increasing. Scott’s claim that the data is not significant is straight-up wrong. The graph he links to shows red areas which have an increase in forest fires with p < 0.05 – that’s significant. There are some areas that show a trend but not significant, and others with no trend. If you look at the graph you will also notice a good correlation to economic development and also hotter regions of the world. They also broke down the data by canopy cover percentage, with greater statistical significance for higher coverage.

Regarding heat related deaths Scott claims a Lancet report provides no data to back up their claim of increasing risk due to climate change, and says their reference has “nothing to do” with the claim. Bu9t the reference does, concluding:

“Across all study countries, we find that 37.0% (range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change and that increased mortality is evident on every continent.”

Again Scott dismisses this as mere modeling, but even this is not true. First, the number of days and intensity of heat waves are increasing. These are raw numbers, not modeling. Second, the raw numbers of deaths associated with excess heat are also increasing, mostly (of course) in hotter regions of the world. What requires modeling is what percentage of these deaths can be attributed to human-caused global warming. These excess deaths also follow the regions with the greatest increase in heat waves.

Scott’s position is simply not supported by basic logic or facts. His framing is flawed and biased, and it’s easy to see how it twists all of his arguments. Under scrutiny, however, they do not stand up.