Quantifying and characterizing uncertainty is among the most important contributions that scientists make to the advancement of knowledge and understanding. Mischaracterizing uncertainty and using it to mislead public audiences is among the most common tricks of those who oppose climate policy.
Scientists work hard to understand sources of uncertainty and to accurately characterize that uncertainty. It is often the central goal of scientific research and, done well, leads to peer-reviewed articles—often highly valued ones—which are the foundation for researchers’ professional advancement.
One great example of rigorous uncertainty characterization is climate sensitivity, which many scientists have worked very hard to understand and quantify over multiple decades. Climate sensitivity, in a nutshell, is the amount of warming that will occur in response to a doubling of carbon dioxide concentrations, all else equal, once the climate system has fully adjusted to the new atmospheric composition. It is important because it helps us understand how much climate change we can expect in the future from our greenhouse gas emissions.
The latest IPCC assessment estimated climate sensitivity as being likely between 1.5-4.5°C, as extremely unlikely to be below 1.0°C, and as very unlikely to be greater than 6.0°C (see pages 1110-1112 of AR5 to read it yourself). Here is a translation for anyone not familiar with IPCC’s language about assessed likelihoods (which is described in section 1.4 on pp. 138-142). There is at least a 2 in 3 chance that climate sensitivity is inside the 1.5-4.5°C range (i.e., at most a 1 in 3 chance that it is either below 1.5°C or above 4.5°C). In addition, there is at most a 1 in 20 chance that climate sensitivity is below 1.0°C and at most a 1 in 10 chance that climate sensitivity is above 6°C.
Those who use uncertainty to mislead combine two separate claims both of which relate directly to climate sensitivity. The first claim is that there is much larger uncertainty surrounding key aspects of climate science than the relevant expert community realizes or publicly acknowledges. The second claim is that this hidden uncertainty means that climate change poses less risk to society than most subject matter experts think.
The first claim is at odds with enormous amounts of evidence. Even if the first claim were correct, the second claim would not follow logically from it.
Climate sensitivity is among the most heavily studied topics in climate science. Assessments of climate sensitivity, like the one from IPCC above, are based on decades of research and numerous independent sources of evidence. Some of that evidence comes from the distant past (e.g., changes that occurred during transitions within and between ice-age and interglacial periods). Some evidence is from the more recent past (e.g., changes that coincide with changing greenhouse gas concentrations and with other known drivers of change such as volcanic eruptions and variation in solar output). Some evidence comes from computational models, which scientists use to rigorously test a wide range of plausible assumptions—from the most optimistic to the most pessimistic—about how climate feedbacks might play out.
That combination of sources of evidence spans numerous disciplines and involves the work of thousands of scientists. As a result, the uncertainty surrounding climate sensitivity has been studied, rigorously quantified and characterized. So new insights that radically change the assessment of climate sensitivity could happen but aren’t likely because they would be at odds with enormous amounts of evidence.
Experts know this because they are familiar with the decades of research focused on climate sensitivity, the evidence that has resulted, and the scrutiny that evidence has faced from independent experts. Public audiences generally don’t know any of that.
It is a clear sign of trouble anytime someone makes a technical claim to public audiences that is at odds with comprehensive assessments made and reaffirmed by experts who are familiar with the relevant evidence.
Second, and perhaps even more importantly, the claim that uncertainty is greater than we think does not lead to the conclusion that the risks of climate change are lower than we think. This is because greater uncertainty would mean that it is harder to say how large climate changes will be. It would not mean that we know that climate changes will be small. Knowing that climate changes will be small requires less uncertainty, not more.
Greater uncertainty would mean that we are less sure about the role of natural factors in recent climate changes. Those natural factors could be responsible for more of the warming than a comprehensive examination of the evidence suggests. If so, that would mean that climate sensitivity is lower than we think and future emissions will therefore lead to less climate change. But more uncertainty cuts both ways so the opposite is also true. Natural factors could be exerting a cooling influence that is masking some of the warming our greenhouse gases are causing. That would imply that climate sensitivity is higher than we think and that our future emissions will lead to larger changes in climate.
Those who use uncertainty to say climate change doesn’t pose potentially serious risks are performing a two-step. They talk about uncertainty to dismiss phenomenally rigorous scientific assessments but they don’t apply uncertainty to their own weakly supported hypotheses that climate sensitivity is low. That’s the climate uncertainty shuffle. Or maybe it’s merely a hustle.