Fans of Judith Curry: the uncertainty monster is not your friend

I think that uncertainties in global surface temperature anomalies is substantially understated.

Judith Curry

People often see uncertainty as a failing of science. It's the opposite: uncertainty is what drives science forward.

Dallas Campbell

Imagine you are driving on a curvy forest road and it gets more foggy. Do you slow down or do you keep your foot on the pedal? More fog means more uncertainty, means less predictability, means that you see the deer in your headlights later. Climate change mitigations sceptics like talking about uncertainty. They seem to see this as a reason to keep the foot op the pedal.

While this is madness, psychology suggests that this is an effective political strategy. When you talk about uncertainty people have a tendency to become less decisive. Maybe people want to wait deciding until the situation is clearer? That is exactly what the advocates for inaction want and neglects that deciding not to start solving the problem is also a decision. For someone who would like to see all of humanity prosper deciding not to act is a bad counter-productive decision.

Focusing on uncertainty is so common in politics that this strategy got its own name:

Appeals to uncertainty to preclude or delay political action are so pervasive in political and lobbying circles that they have attracted scholarly attention under the name “Scientific Certainty Argumentation Methods”, or “SCAMs” for short. SCAMs are politically effective because they equate uncertainty with the possibility that a problem may be less serious than anticipated, while ignoring the often greater likelihood that the problem may be more deleterious.

Meaning of uncertainty

Maybe people do not realise that uncertainty can have multiple meanings. In case of climate change "uncertainty" does not mean that scientists are not sure. Science is very sure it is warming, that this is due to us and that it will continue if we do not do anything.

When we talk about climate change, "uncertainty" means that we do not know exactly how much it has warmed. It means that the best estimate of the man made contribution is "basically all", but that it is possible that it is more or that it is less. It means that we know it will warm a lot the coming century, but not exactly how much, if only because no one knows whether humanity gets it act together. It means that the seas will rise more than one meter, but that we can only give a period in which this threshold will be crossed.

Rather than talking about "uncertainty" I try to talk about "confidence intervals" nowadays, that conveys the idea of this latter kind of uncertainty much better. Science may not know the exact value, but the value will most likely be in the confidence interval.

That the term uncertainty can be misunderstood is especially a problem because scientists love to talk about uncertainties. A value is worth nothing if you do not have an idea how accurate it is. Thus most of the time scientists work on making sure that the uncertainties are accurate and as small as possible.

More uncertainty means higher risks

The damages of climate change rise with its magnitude (let's call this "temperature increase" for simplicity). I will argue in the next section that these damages rise faster than linear. If the relationship were linear, twice as much temperature increase would mean twice as much damages. Super-linear means that damages rise faster than that. Let us for this post assume that the damages are proportional to the square of the temperature increase. Any other super-linear relationship would show the same effect: that more uncertainty means higher risks.

In this case, if there were no uncertainty and the temperature in 2100 will increase by 4 degrees Celsius. For comparison, the temperature increase in 2100 is projected to be between 3 and 5.5°C for the worst scenario considered by the IPCC; RCP8.5. With 4 degrees warming the damages would be 16*D (4²*D) dollar or 16*H human lives.

In the case with uncertainty, the temperature in 2100 would still increase by 4 degrees on average, but it could also be 3°C or 5°C. The damages for 4 degrees are still 16*D dollar. At 3 degrees the damage would be 9*D and at 5 degrees 25*D dollar, which is on average 17*D. The total damages will thus be higher than the 16*D dollar we had for the case without uncertainty.

If the uncertainty becomes larger, and we also have to take 2 and 6 degrees into account we get 4*D (for 2°C) and 36*D (for 6°C), which averages to 20*D dollar. When we are less certain that the temperature increase is near 4°C and uncertainty forces us to take 2°C and 6°C into account, the average expected damages become higher.

Judith Curry thinks that we should take even more uncertainty into account: "I think we can bound [equilibrium climate sensitivity] between 1 and 6°C at a likely level, I don’t think we can justify narrowing this further. ... [T]here is a 33% probability that that actual [climate] sensitivity could be higher or lower than my bounds. To bound at a 90% level, I would say the bounds need to be 0-10°C."

If the climate sensitivity were zero, the damages in 2100 would be zero. Estimating the temperature increase for a climate sensitivity of 10°C is more challenging. If we would still follow the carbon-is-life scenario mitigation skeptics prefer (RCP8.5), we would get a temperature increase of around 13°C in 2100^**. It seems more likely that civilization will collapse before, but 13°C would give climate change damages of 13²*D, which equals 169*D. The average damages for Curry's limiting case are thus 85*D, a lot more than the 16*D for the case were we are certain. If the uncertainty monster were this big, that would make the risk of climate change a lot higher.

Uncertainty is not the friend of people arguing against mitigation. The same thinking error is also made by climate change activists that sometimes ask scientists to emphasis uncertainty less.

Super-linear damages

Accumulated loss of regional species richness of macro-invertebrates as a function of glacial cover in catchment. They begin to disappear from assemblages when glacial cover in the catchment drops below approximately 50%, and 9 to 14 species are predicted to be lost with the complete disappearance of glaciers in each region, corresponding to 11, 16, and 38% of the total species richness in the three study regions in Ecuador, Europe, and Alaska. Figure RF-2 from IPCC AR5 report.

The above argument rests on the assumption that climate change damages rise super-linearly. If damages would rise linearly, uncertainty would not matter for the risk. In theory, if damages would rise less fast than linear (sub-linear), the risk would become lower with more uncertainty.

I am not aware of anyone doubting that the damages are super-linear. Weather and climate are variable. Every system will thus be adjusted to a small temperature increase. On the other hand, a 10°C temperature increase will affect, if not destroy, nearly everything. Once a large part of civilization is destroyed, the damages function may become sub-linear again. Whether the temperature increase is 10 or 11 degrees Celsius likely does not matter much any more.

What is a small temperature increase depends on the system. For sea level rise, the global mean temperature is important and the average temperature over centuries to millennia. This did not vary much, thus climate change quickly shows an influence. For the disappearance of permafrost, the long-term temperature is also important, but the damage to the infrastructure build on them depend on the local temperature, which varies more than the global temperature. On the local annual scale the variability is about 1°C, which is the global warming we have seen up to now and where new effects are now seen, for example nature moving poleward and up mountains (if it can). In summary, the more temperature increases, the more systems notice the change and naturally the more they are affected.

Damages can be avoided by adaptation. Both natural adaptation to the vagaries of weather and climate, as well as man-made adaptation in anticipation of the mess we are getting into. In the beginning there will still be low-hanging fruit, but the larger the changes will become, the more expensive adaptation becomes. More uncertainty also makes man-made adaptation more costly. If you do not know accurately how much bigger a centennial flood is, that is costly. To build bigger flood protections you need to have a best estimate, but also need to add a few times the uncertainty to this estimate, otherwise you would still be flooded half the time such a flood comes by.

An example of super-linear impacts is species loss for glacier catchments when the glaciers disappear. The figure above shows that initial small reductions in the glaciers did not impact nature much yet, but that it rises fast near the time the glacier is lost.

The costs of sea level rise rise super-linearly as a function of the amount of sea level rise. Data from Brown et al. (2011).

Another example are the super-linear costs of sea level rise. This plot to the right was generated by sea level rise expert Aslak Grinsted from data of a large European scientific project on the costs of climate change. He added that this shape is consistent across many studies on the costs of sea level rise.

Those were two examples for specific systems, which I trust most as natural scientist. Economists have also tried to estimate the costs of climate change. This is hard because many damages cannot really be expressed in money. Climate change is one stressor and in many cases damages also depend on many other stressors. Furthermore, solutions can often solve multiple problems. As economist Martin Weitzman writes: "The “damages function” is a notoriously weak link in the economics of climate change

The climate change damages functions of Weitzman (2010b) and Nordhaus (2008). For a zero temperature change Ω(t)=1Ω(t)=1 (no damage) and for very large temperature changes it approaches 0 (maximum damage).

Consequently, the two damages functions shown to the right differ enormously. Important for this post: they are both super-linear.

Unknown unknowns

If there is one thing I fear about climate change, then it is uncertainty. There will be many surprises. We are taking the climate system out of the state we know well and are perform a massive experiment with it. Things are bound to happen, we did not think of. Some might be nice, more likely the surprises will not be nice. As Judith Curry calls it: climate change is a wicked problem.

Medical researchers like to study rare deceases. They do so much more than the number of patients would justify. But seeing things go wrong helps you understand how things work. The other way around this means that until things go wrong, we will often not even know we should have studied it. Some surprises will be that an impact that science did study turns out to be better or worse; the known unknowns. The most dangerous surprises are bound to be the unknown unknowns, which we never realised we would have had to study.

The uncertainty monster is my main reason as citizen to want to solve this problem. Call me a conservative. The climate system is one of the traditional pillars of our society. Something you do not change without considering long and hard what the consequences will be. The climate is something you want to understand very well before you change it. If we had perfect climate and weather predictions, climate change would be a much smaller problem.

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Gavin Schmidt

I think the first thing to acknowledge is that there will be surprises. We’re moving into a regime of climate that we have not experienced as humans, most ecosystems have not experienced since the beginning of the ice age cycle some three million years ago. We don’t know very well what exactly was happening then. We know some big things, like how much the sea level rose and what the temperatures were like, but there’s a lot of things that we don’t know. And so we are anticipating “unknown unknowns”. But, of course, they’re unknown, so you don’t know what they’re going to be.

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One irony is that climate models reduce the uncertainty by improving the scientific understanding of the climate system. Without climate models we would still know that the Earth warms when we increase greenhouse gasses. The greenhouse effect can be directly measured by looking at the infra red radiation from the sky. When you make that bigger, it gets warmer. When you put on a second sweater, you get warmer. We know it gets warmer from simple radiative transfer computations. We know that CO2 influences temperature by studying past climates.

The climate models have about the same climate sensitivity as those simple radiative transfer computations and the estimates from past climates. It could have been different because the climate is more complicated than the simple radiative transfer computation. It could have been different because the increase in greenhouse gasses goes so fast this time. That all those climate sensitivity estimates fit together reduces the uncertainty, especially the uncertainty from the unknown unknowns.

Without climate models it would be very hard to estimate all the other changes in the climate system. The increases in precipitation and especially increases in severe precipitation, in floods, in droughts, in the circulation patterns, how fast sea level rise will go. Without climate models these risks would be much higher, without climate models we would have to adapt to a much wider range of changes in weather and climate. This would make adaptation a lot more intrusive and expensive.

Without climate models and climate research in general the risks of changing our climate would be larger. We would need to be more careful, the case for reductions of greenhouse gas emissions would have been stronger.

Especially for mitigation sceptics advocating adaptation-only policies, climate research should be important. Adaptation needs high-quality local information. For a 1000-year event such as the downpour in South Carolina earlier this year or the record precipitation this week in the UK, we may have to life with the damages. If this will happen much more often under climate change, we will have to change our infrastructure. If we do not know what is coming, we will have to prepare for everything. That is expensive. Reductions in this uncertainty save money by reducing unnecessary adaptation measures and by reducing damages due to effective adaptation.

People who are against mitigation policies should be cheering for climate research, rather than try to defund it or harass scientists for their politically inconvenient message. Let's be generous and assume that they do not know what they are doing.

In summary. Uncertainty makes the risk of climate change larger. Uncertainty makes adaptation a less attractive option relative to solving the problem (mitigation). The more we take the climate system out of known territories the more surprises (unknown unknowns) we can expect. In a logical world uncertainty would be the message of the environmental movement. In the real world uncertainty is one of the main fallacies of the mitigation skeptics and their "think" tanks.

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Related reading

Tail Risk vs. Alarmism by Kerry Emanuel

Stephan Lewandowsky, Richard Pancost and Timothy Ballard making the same case and adding psychological and sociological explanations why SCAMs still work: Uncertainty is Exxon's friend, but it's not ours

Talking climate: Communicating uncertainty in climate science

European Climate Adaptation Platform: How to communicate uncertainty?

Dana Nuccitelli: New research: climate change uncertainty translates into a stronger case for tackling global warming

Uncertainty isn’t cause for climate complacency – quite the opposite

Michael Tobis in 1999 about uncertainty and risk: Wisdom from USENET

References

Botzen, W.J.W. and J.C. van den Bergh, 2012: How sensitive is Nordhaus to Weitzman? climate policy in DICE with an alternative damage function. Economics Letters, 117, pp. 372–374, doi: 10.1016/j.econlet.2012.05.032.

Nordhaus, W.D., 2008: A Question of Balance: Weighing the Options on Global Warming Policies. Yale University Press, New Haven.

Brown, Sally, Robert Nicholls, Athanasios Vafeidis, Jochen Hinkel and Paul Watkiss, 2011: The Impacts and Economic Costs of Sea-Level Rise in Europe and the Costs and Benefits of Adaptation. Summary of Results from the EC RTD ClimateCost Project. In Watkiss, P. (Editor), 2011. The ClimateCost Project. Final Report. Volume 1: Europe. Published by the Stockholm Environment Institute, Sweden, 2011. ISBN 978-91-86125-35-6.

Lewandowsky, Stephan , James S. Risbey, Michael Smithson, Ben R. Newell, John Hunter, 2014: Scientific uncertainty and climate change: Part I. Uncertainty and unabated emissions. Climatic Change, 124, pp. 21–37, doi: 10.1007/s10584-014-1082-7.

Tomassini, L., R. Knutti, G.-K. Plattner, D.P. van Vuuren, T.F. Stocker, R.B. Howarth and M.E. Borsuk, 2010: Uncertainty and risk in climate projections for the 21st century: comparing mitigation to non-intervention scenarios. Climate Change, 103, pp. 399–422. doi: .

Weitzman M.L., 2010a: What is the damages function for global warming and what difference might it make?
Climate Change Economics, 1, pp. 57–69, doi: 10.1142/S2010007810000042.

Weitzman, M.L., 2010b: GHG Targets as Insurance Against Catastrophic Climate Damages. Mimeo, Department of Economics, Harvard University.


Acknowledgements.
* Thanks to Michael Tobis for the foggy road analogy, which he seems to have gotten from [[Stephen Schneider]].

** Judith Curry speaks of the equilibrium climate sensitivity begin between 0 and 10°C per doubling of CO2. The TCR to ECS ratio peaks at around 0.6, so an ECS of 10°C could be a TCR of 6°C. Since doubling of CO2 is a forcing of 3.7 W/m² and RCP8.5 is defined as 8.5 W/m² in 2100, that would mean a warming of 8.5/3.7 x 6 = 13°C (Thank you ATTP).

For comparison, the IPCC estimates the climate sensitivity to between 1.5 and 4.5°C. Last IPCC report: "Equilibrium climate sensitivity is likely in the range 1.5°C to 4.5°C (high confidence), extremely unlikely less than 1°C (high confidence), and very unlikely greater than 6°C (medium confidence)"

*** Top photo by Paige Jarreau.