The science-society interface

I came across an interesting paper by Dietram Scheufele on Thirty Years of science-society interfaces: What’s next, which focusses mostly on science communication. Although – as the article mentions – this isn’t the only possible science-society interface. Since I have an interest in this myself, I thought I might add some reflections of my own, but from the perspective of a scientist who is trying to communicate, rather than from the perspective of a scholar who studies the science-society interface.

In my experience there are, broadly speaking, two groups of scholars who focus on science communication. There are those who are actively trying to find ways to help scientists communicate more effectively. For example, the group at George Mason University, which included John Cook from Skeptical Science, with whom I’ve done some work. John has since moved to the Climate Change Communication Research hub at Monash University.

The other group are those who seem to regard their role as analysing the interface between science and society, critiquing how scientists engage publicly, and – in some sense – almost defining the appropriate manner in which scientists should interact with the broader public. The author of the above paper seems to belong more to this group, than to the former group.

Unfortunately, my interaction with the latter group of scholars has often been less than positive, which may of course reflect more on me than on them. However, I sometimes find the premise of their scholarship a little arrogant, as if they’re in some special position where they get to critique other scholars without seeming to recognise an equivalence between themselves and those they’re choosing to critique. There can also be a tendency to generalise about scientists, and to be rather dismissive of feedback coming from scientists. There are also some who have, in my view, actively hampered attempts to communicate science.

There can also be an element of irony in what is often presented by these scholars and this is somewhat evident in the article mentioned above. A common claim is that scientists who engage publicly suffer from what is referred to as deficit model thinking. The basic idea is that scientists think that science communication acts to fill some knowledge deficit which then leads to the public understanding the basic issue and accepting the policies that might derive from the scientific information. Of course, this is not how things work in reality. It is clearly much more complex, and there are many factors that infuence whether or not someone will accept a scientific position and what they would be willing to do even if they did.

However, it often seems that the scholars who criticise scientists for deficit model thinking end up doing something very similar themselves. They will imply that their field has developed a deep understanding of the science-society interface, that this is not being considered by scientists who engage publicly, and that if scientists did pay more attention to it, the interaction between scientists and society would be greatly improved. It may not be exactly deficit model thinking, but it seems pretty close. It’s almost as if these scholars don’t quite believe what their own scholarship seems to imply.

I also wanted to add something else about deficit model thinking. I’m a scientist who has spent quite a lot of time engaging in various forms of science communication. The reason I focus on trying to explain the “science” is that I enjoy doing so, I feel comfortable doing so, and because it allows me to focus on topics in which I think I have some relevant expertise. I’m not doing it because I think that all that needs to happen in order to solve various complex socio-political issues is for people to understand, and accept, the scientific information that I’m choosing to present. I’m well aware that it’s more more complex than that. I sometimes wonder if those who criticise scientists for deficit model thinking have really considered this from the perspective of those scientists who are choosing to engage publicly.

Okay, this is getting rather long, so I should wrap up. I do think that these are important issues and I do think that it is a topic that scholars should interrogate. However, if those who do so are essentially suggesting that scientists at the science-society interface should reflect on how they engage, then there may be merit in them doing some reflection themselves. To be fair, the article above does include some reflection, which is good to see. However, as I suspect such scholars would acknowledge, if your audience isn’t accepting your message, then maybe this indicates some issue with what you’re presenting, or how you’re doing so, rather than an indication that the audience is ignoring an obvious “truth”.

The Greenhouse Effect

I’ve ended up in a rather silly discussion/debate on Twitter about the Greenhouse Effect. I realise it’s rather pointless, in that those who dispute it are very unlikely to accept its reality. However, it’s still interesting to think about how to construct an argument, and it gave me an opportunity to highlight some papers and articles that might be of interest to others. I thought I might repeat some of it here.

Credit: Stephens et al. (2012)

One of the arguments being made is that noone has demonstrated that CO₂ can provide the backradiation that heats the surface. Firstly, it’s not simply CO₂, it’s emission back to the surface from the lower atmosphere. Also, given an average surface temperature of around 288K, we know the surface must be radiating almost 400 Wm². It also loses just over 100 Wm² through evapo-transpiration and thermals (see energy balance figure on the right).

However, the surface receives less than 200 Wm² from the Sun. Hence, to be in energy balance, there must be an additional energy flux, with a magnitude of over 300 Wm². This is the back-radiation from the lower atmosphere. If it wasn’t there, the surface would be losing much more energy than it was receiving and would rapidly cool. This clearly is not happening, hence there must be some backradiation. I should add, that it has also been measured.

Another argument is that the effect of CO₂ is now saturated. This is an old argument that has been addressed a good number of years ago. It illustrates a rather fundamental misunderstanding of the Greenhouse effect. What’s not always well understood is that convection in the lower atmosphere (troposphere) is important. Convection plays a role in the atmospheric temperature decreasing with increasing altitude; it gets colder as you go up in the atmosphere.

The presence of greenhouse gases in the atmosphere prevents all of the energy from being radiated to space directly from the surface. Instead some of the energy is radiated to space from within the atmosphere. Since the system will tend to energy balance, and since temperature decreases as you go to higher altitudes, this means that the surface has to be warmer than it would be in the absence of an atmosphere; the Greenhouse effect.

Credit: Rasmus Benestad, Realclimate

Also, as illustrated very nicely in the Figure on the right, taken from this Realclimate post, adding more greenhouse gases to the atmosphere increases the altitude at which energy is radiated to space. Again, since the temperature decreases with altitude, this would then require that the lower atmosphere and surface would have to warm to return the system to energy balance; the enhanced Greenhouse effect. This is what we’re doing now with our emissions of CO₂, and other greenhouse gases.

A final claim is that most of our recent warming is due to increases in absorbed solar radiation, which contradicts what’s expected from the Greenhouse effect. This is a somewhat subtler point but, again, illustrates a misunderstanding of how the Greenhouse effect actually works.

A somewhat simplistic view of the Greenhouse effect is that adding greenhouse gases to the atmosphere reduces the outgoing longwave flux, which then recovers as the system warms back to equilibrium. However, as I explain in this post, there are both short- and long-wavelength feedbacks. The outgoing longwave flux actually recovers quite quickly. However, the shortwave feedback (mostly due to changes in clouds) leads to an increase in absorbed solar radiation, which causes the system to keep warming, increasing the outgoing longwave flux to above the level it had before the greenhouse gas concentrations increased.

So, in a sense, this continued warming is due to an increase in absorbed solar radiation, but this doesn’t mean that this wasn’t caused by the initial increase in greenhouse gases in the atmosphere. It doesn’t somehow contradict what we expect from the Greenhouse effect.

Anyway, I think it’s useful to think about these things even if arguing about it on Twitter is mostly pointless. A key point, which I’ve probably highlighted before, is that if someone thinks they’ve encountered some simple, and obvious, reason why a well accepted scientific argument is flawed, maybe they should first check that they properly understand the scientific argument they claim to have overthrown.

Nine years

WordPress has reminded me that I started this blog 9 years ago today. I feel that I should commemorate that in some way, but I’m not sure how, or really what to say.

As you can tell, the blog has been somewhat quiet, even though I do write posts everyone now and again, mostly when I feel that I have something to say. I don’t suspect this is going to change anytime soon.

I had a quick look at the blog stats, and there have been 1261 posts, of which I’ve written 1191. That seems a reasonable legacy, even if not everyone agrees 🙂

Anyway, it’s been an interesting 9 years, during which I’ve learned a lot, even if I have ended up slightly more confused about some things than I was when I started. Hope it’s also been of interest to some others.

Scenarios

Just before the release of the IPCC’s AR6 WGIII report (Mitigation of Climate Change) Joeri Rogelj had a Carbon Brief guest post on how not to interpret the emission scenarios in the IPCC report. It might have been to try and pre-empt some of the simplistic narratives that some have promoted about emission scenarios, but I can’t be sure about that being the motivation.

The key point being made was that

Scenarios can be thought of as stories of what could happen in the future. What they are not, it is important to note, are forecasts or predictions for the future.

As the article goes on to say, scenarios are essentially “what if” thought experiments that help us to answer some questions about what might happen in the future. They do not, however, encompass all possible futures, and are not predictions of the future.

However, the issue of scenario plausibility has been a bit of a hot topic and is something I’ve been thinking about a bit myself. I haven’t managed to really draw any strong conclusions, but the beauty of a blog is that I can present some ideas that others can challenge/clarify in the comments.

I tend to think that scenarios should be plausible in the sense of not violating some fundamental laws of physics, or the essentials of chemistry. I don’t necessarily think they need to pass some kind of societal plausibility test, at least in the sense of them being what we will probably do. They could be “what ifs”, or “what could have been” or even “what might be”. Of course, I do think the motivations, and assumptions, should be made clear when communicating the results of any analysis based on a particular scenario, but I don’t think they have to pass some kind of societal plausibility test.

However, one of the key talking points about scenarios is whether or not their plausibility should be more explicit. I can see some merit to this, but I can also see why this may not be appropriate. If scenarios are “what if” thought experiments, rather than forecasts or predictions, then we should be cautious of suggesting that they are more the latter than the former.

There’s also the issue of independence. If the point of scenarios is to understand the impact of various possible futures, then assigning something like a probability to a scenario might then influence the outcome. For example, if we claim that a particular scenario is impossible, we may then either give up trying to achieve it, or assume that we no longer need to do anything to avoid it. In a sense, the probability of a scenario emerging in reality could be influenced by the probability assigned to that scenario, which would then undermine the intention of these being policy relevant, rather than policy prescriptive.

A potentially interesting issue, though, is the self-consistency of scenarios. In most cases a scenario is developed and then that scenario is used as input to some kind of model to assess the potential impact of that scenario. However, rarely do these models then include how these impacts might influence the scenario itself.

This can have a number of potential consequences. It could be that the impact of following a particular scenario could be so severe that it essentially precludes anything like that scenario from actually emerging. On the other hand, if we don’t consider how the impacts might influence the scenario itself, we might conclude that everything will still essentially be fine even under some extreme scenarios. So, I think it’s important to make clear that these scenarios are often not really self-consistent.

As usual, this has got rather long. I do think we should mostly treat scenarios as “what ifs” and should let society decide what to do, or not do, given what these scenarios might be suggesting. Of course, I do think we should be very clear about the motivations, and assumptions, behind these scenarios, but – IMO – we should be cautious about explicitly defining the plausibility of these scenarios. However, I would also be interested to know what others think.

Techniques of climate denial

Steve Koonin, who I’ve written about before, had an op-ed in the Wall Street Journal a few months ago claiming that Greenland’s melting ice is no cause for climate-change panic. The article uses a graph of mass loss rate to argue that the rate now is the same as it was in the 1930s, that it has actually been decreasing recently, and that natural influences are much more important than human influences.

I’ve just come across a seminar that was essentially a debate between Steve Koonin and David Romps, who is a Professor of Climate Physics at Berkeley. I’ve posted the video below and it should start when David Romps presents his rebuttal to Steve Koonin’s Wall Street Journal article.

I thought David Romp’s presentation was very interesting, especially given that Steve Koonin was in the room. He didn’t pull any punches. He showed how you could cherry-pick the region you focus on, how you could cherry-pick the data set you use, how you could choose what analysis to present, and how you could then underplay uncertainties, and ignore periods that don’t suit your narrative.

Steve Koonin, of course, disputed that he’d made any suspicious choices, but that’s hardly a surprise. I don’t know if David Romps’ presentation will convince any of those who find Steve Koonin’s presentation appealing, but it was well done nonetheless.

Ignoring the Economists?

Andrew Dessler had an article in Rolling Stone suggesting that [t]he first step to saving the planet is ignoring the economists. Stoat has already written about it and, as you might imagine, doesn’t seem to like it. Even if suggesting that we ignore economists is a bit hyperbolic, I think Andrew makes some good points. Or, maybe, points I happen to agree with.

Andrew’s specific focus is economists who assess climate policy on the basis of cost-benefit analyses. The problem with this in the climate context is that we have the potential to substantially change the climate and to do so on geologically fast timescales. It’s extremely difficult to estimate the impact of such changes, and hence cost-benefit analyses are going to be extremely uncertain. They’re also quite simple calculations that don’t even come close, as far as I’m aware, to self-consistently modelling the evolution of the world’s economy in the presence of climate change. They also require many judgements that are clearly not value free.

Also, some of these analyses produce rather strange results. For example, suggesting that the damage will be relatively modest even for very large amounts of global warming, or suggesting that the optimal pathway would be one that leads to about 3.5^oC of warming. This is another issue with some of these analyses. A lot of recent work has suggested that we’re currently heading along a pathway that will probably lead to between 2^oC and 3^oC of warming. How can a recent CBA suggest that the optimal pathway is one that would probably lead to about 3.5^oC of warming, when we’re already probably heading for less than 3^oC of warming^*? The answer is probably that they haven’t properly assessed their no-policy baseline, but it still illustrates a potential issue with these analyses.

So, what could we do instead of a cost-benefit analysis? Well, we could determine what it would it take to achieve a normatively determined warming target. Not only does this also have deep economic roots, it’s essentially what the world’s governments have already agreed to try and do. So, it’s not as if this alternative to a simple cost-benefit approach is somehow an outrageously extreme suggestion, or one that would somehow be wildly at odds with the fundamentals of mainstream economics.

Of course, there also isn’t an objectively correct way to assess the ideal target. However, it seems clear that the more we warm, the greater the impact, and that the changes will probably be irreversible on human timescales. Rather than trying to work out some optimal pathway, why not do our best to limit how much we will eventually warm, with some goal of at least trying to meet some warming target, such as < 2^oC? We might not meet the target, but just missing it will probably be a lot better than heading along some kind of optimal pathway and then discovering that the impact is far greater than estimated by these rather simple cost-benefit analyses.

Footnote:

^* I realise that there are uncertainties that mean that even though our current trajectory is probably taking us towards somewhere between 2^oC and 3^oC, we can’t really rule out that it might end up being well above 3^oC. However, the same uncertainty applies to the cost-benefit optimal pathway.

Links:

The first step towards saving the planet is ignoring the economists – Rolling Stone article by Andrew Dessler.
The flower of poor thinking is to lack influence – Stoat’s post.
The impact of climate change, and the cost of climate policies – one of my earlier posts.
Economics and Values – another of my posts.
Moving beyond benefit-cost analysis of climate change – paper by Jonathan Koomey.

Moral models

I thought I would highlight a recent video presentation by Eric Winsberg, called Moral Models, Crucial Decisions in the Age of Computer Simulations. Some may remember that Eric co-wrote a post here about extreme weather event attribution.

The theme of Eric’s presentation is the moral significance of models and their influence on society. Eric makes a number of points that I largely agree with. A key point is that science doesn’t make decisions, people do. Models can inform decision making, but can’t define it.

Eric focuses particularly on the models used to understand the spread of the COVID-19 virus. Eric is rather critical of some of the modelling, in particular the influential Imperial College model. Eric highlights that some of the early models didn’t do much in the way of sensitivity tests and didn’t really consider the broader implications of their assumed interventions. I’m aware of an attempt to do a sensitivity analysis of the Imperial College model, but I didn’t think it was particularly useful.

What Eric stresses is that the assumptions that go into these models are not value-free. For example, in the case of COVID modelling, modellers will need to decide which potential interventions to consider, and they can almost certainly not do this in an entirely value-free way. What Eric suggests is that the modellers should have given more thought to how the interventions they chose to consider might influence other sectors of society, in particular those sectors with which the modellers probably have no association.

Eric also criticised the models for not considering the broader implications of the potential interventions. How would closing schools influence school children, and their parents? How would closing sectors of the economy influence those who might not be able to easily work from home? etc. Although these are perfectly valid concerns, this is where I somewhat disagree with Eric.

I think it’s very challenging to self-consistently include these impacts in the models and this may well go beyond what these models are designed to do, or should even try to do. Also, I think these are issues that policy makers should be aware of. They should be getting advice from other experts about the economic, and social, impacts of the various possible strategies. I do think we should be careful of suggesting that it was the responsibility of the modellers to provide this broader perspective.

However, I do think that modellers should be as clear as possible about the limitations of their models. This is partly simply because it’s the right thing to do, but also because it’s key to stress that models only inform decision making, not define it. If I was ever in a position to provide advice to policy makers, I would be pretty worried if I thought their decisions were based only on the information I presented. I would want policy makers to be informed by a broad range of experts. It’s key, in my view, to stress that the responsibility for making decisions lies with them, not with modellers/scientists.

Anyway, as usual I’ve written more than I had intended. Eric’s video presentation is below. Even if you don’t agree with it all, it certainly presents some ideas that are worth thinking about.

A coupled climate-social system

I came across an interesting paper by Frances Moore and colleagues that considers [d]eterminants of emissions pathways in the coupled climate–social system. In the context of climate science, models that consider both the climate and society tend to not be coupled. For example, global climate models will use emission, or concentration, pathways as input, but these will be pre-defined and will not be influenced by the resulting climate change. Similarly, economic models might use a simple climate model to estimate damages, or to do some cost-benefit analysis, but the latter essentially determines the optimal pathway, but doesn’t really self-consistently couple the climate-social system.

This new paper seems to be the first, or one of the first, that couples a climate-social system. There are quite a large number of factors, but essentially the model estimates the response to various factors and how that might then infuence emissions, and – consequently – climate change. For example, as alternatives become cheaper, their uptake will increase. Similarly, as social norms change, this might influence people’s behaviour in ways that influence emissions. There could be the implementation of policies and laws that will also have an influence. Additionally, our perception of climate change might also directly influence people’s behaviour and the implemention of new policy/laws.

They then run a large suites of models, sampling the various parameters, to produce a suite of outputs that they then group into categories. The main results are shown in the figure below.

Policy (left-hand panel) and emission trajectories (right-hand panel) from a large suite of runs of a coupled climate-social model. (credit: Moore et al. 2022).

The basic result is that a large fraction of their model runs suggest emissions will peak in about 2030, and then fall sharply, leading to warming of about 2.3^oC by 2100. There are also some where emissions fall more sharply and warming is closer to 2^oC, and others where emission reductions are delayed and warming is closer to 3^oC. Overall, most of their models suggest warming of between 2^oC and 3^oC, but the overall range is from 1.8^oC and 3.6^oC.

This, however, doesn’t include the full range of climate sensitivity and other possible climate feedbacks, so it can’t quite rule out warming above 3.6^oC. However, this does seem to be another paper suggesting that the most likely trajectories suggest warming of between 2^oC and 3^oC, but that we can’t yet rule out that warming could be kept below 2^oC, or that it might exceed 3^oC. In some sense this is positive (we can still limit warming to below 2^oC) but also somewhat concerning (we can still follow a trajectory that could lead to > 3^oC of warming).

From a modelling perspective, this does seem very interesting. The model may rely on a large number of parameters that may not be easy to precisely define, but it is still good to see that some are trying to develop these coupled models that try to self-consistently determine the evolution of the climate-social system.

Links:

Determinants of emissions pathways in the coupled climate–social system, Moore et al. (2022), Nature.

A couple of highlights

Since it has been a bit quiet, I thought I might highlight a couple of things the regulars might find of interest.

Climate blogging in a post-truth era:

Thanks to Stoat, I’ve become aware that Giorgis Zoukas finished his PhD on Climate blogging in a post-truth era: opportunities for action and interaction. Mainstream scientist-produced climate blogs as a climate science communication niche. Some may remember that Giorgis had a guest post here where he invited people to participate in his research project.

The project involved interviewing climate bloggers who were also “mainstream” scientists (this blogger included) and also people who commented on these blogs, including some who are regulars here. I haven’t read it all, but did read some and found it very interesting. It was interesting to read some of my perspectives from a few years ago, which I don’t think have changed all that much.

I should also add that Giorgis first contacted me when I was still blogging anonymously. It gave me a bit of a start at the time because he was a PhD student at my university and I initially thought that maybe he’d contacted me because he knew who I was. He didn’t, but we did then meet in person.

Anyway, I thought others who have been involved in climate blogging, or commenting on climate blogs, may also be interested in looking through Giorgis’ thesis.

Short- and long-lived GHGs

Since I’ve written a number of posts about methane, I thought I would also highlight a recent paper arguing that we should [i]ndicate separate contributions of long-lived and short-lived greenhouse gases in emission targets. It’s partly interesting because the list of co-authors is quite extensive and includes some who haven’t (from what I’ve seen) always agreed about how to incorporate short-lived and long-lived GHGs into emission targets.

If you’ve read some of my earlier posts you’ll know that I largely agree with the suggestion in this paper. Short-lived and long-lived GHGs do behave differently and the association between emissions and warming is different for short- and long-lived GHGs. Combining them to produce a single emission target can hide a lot of complexity. For example, Zeke Hausfather points out that net-zero all GHGs (based on CO₂-equivalence) probably implies net-negative actual CO₂ because it’s probably impossible to remove all emissions for some species.

So, treating these different species separately makes these differences clear and allows us to better understand what is actually required in order to achieve some of our stated targets.

An international solar geoengineering non-use agreement

I wrote about Solar Radiation Managment, or solar geoengineering, earlier this year. It’s become a rather contentious topic, with some regarding it as worth exploring, and others almost seeming to regard it as something we should avoid at all costs. The latest saga involves a group of scholars signing a letter arguing for an international solar geoengineering non-use agreement, which is partly based on this paper. Their main reason for proposing this is that they regard it as being virtually impossible to develop a suitable governance framework.

As a result of this, I ended up in a brief Twitter discussion with Dan Miller, who then asked me to join their clubhouse discussion that took place yesterday evening. It was an interesting discussion, but a little tricky as I was there to partly defend the call for a non-use agreement, which I hadn’t signed and don’t completely agree with. I do, however, share many of their concerns.

On the other hand, Dan and his colleagues, Stacey and Ely, seem fairly convinced that there is a high risk of us crossing a tipping point soon and that this means that we should be seriously considering actually implementing some kind of solar radiation management now.

Although I don’t completely agree with all of what seems to be being proposed in the call for a non-use agreement, I do not think that we should be seriously considering the use of solar geoengineering. One reason is that even though I agree that there are risks of us crossing some tipping points, I think these become much more likely if we warm beyond 2^oC. Consequently, I think our focus should be on limiting emissions so that we give ourselves a good chance of keeping warming below 2^oC, rather than implementing some kind of solar geoengineering.

The other reason is because of the risk of what is called a termination shock. If we were to implement solar geoengineering now so as to keep global warming close to today’s level while continuing to emit CO₂ into the atmosphere, solar geoengineering could end up masking quite a lot of unrealised warming. If for some reason we were unable to sustain this solar geoengineering, this unrealised warming could then materialise on a timescale of a few years, which could have catastrophic consequences.

So, I do think we should be very cautious of actively implementing such technology. In fact, I would suggest that we really shouldn’t be aiming to implement anything like this at the moment, or any time soon. I also think the governance issues highlighted in the letter are valid concerns, and there may well be no easy way to overcome them. On the other hand, I think it’s probably still worth understanding this option, even if it is something we never actually want to use. In some sense, the cat is already out of the bag (we know that there are ways to artificially cool the planet) so it’s probably better to be informed, than not.

Links:

Solar geoengineering non-use agreement
Solar geoengineering: The case for an international non-use agreement, paper by Biermann et al.

Update:

As highlighted by Alastair McIntosh on Twitter, solar geoengineering also doesn’t directly address ocean acidification, which is another reason for focussing on emission reductions, rather than implementing something like solar radiation management.