Meeting Report 26th Swiss Global Change Day

Prein starts by letting the audience guess the average annual precipitation in Switzerland. The answer options range between 700 mm and 2400 mm. The right answer is 1300 mm, and climate models are actually really good at projecting that. However, this number is really odd, he says, because it does not match what we observe. In the driest place in Switzerland (Visper Valley), there is only about half as much average annual precipitation (543 mm) whereas only 25 km away, the region of the Jungfrau Aletsch glacier has more than 3m of average annual precipitation. This example impressively demonstrates why high-resolution modelling is necessary to show these regional differences, which cannot be represented in 100-km grid cells. This is of high importance not only to understand observed differences at present times, but also how they change in the future to estimate e.g. future water scarcity.

After giving an introduction into climate models and the topographical differences of different resolutions, Prein starts by pointing out the importance of high-resolution modelling (1-2 km grid spacing) for resolving topography effects and improving the representation of atmospheric dynamics. Starting at 3 km grid spacing, models are much better able to represent deep convective clouds as they no longer have to be parametrized, which is very important for weather forecasting but also has many benefits for climate models. But why, then, is not everyone using these hig resolution models? While being particularly helpful to include local phenomena, high-resolution models also have a high computational cost. Hence, high resolution models are spatially and temporally very limited. If you had the same computational resources, you could run a global model (CESM2(CAM6)) for 13000 years (back to the Younger Dryas) whereas you could run a new model (MPAS global) with 3.75 km grid spacing for only two years (end of Eras Tour by Taylor Swift). This shows that very different types of questions can be answered with these two types of models. A further issue is that high resolution model informations is only available over a few regions in the world, predominantly in the Global North, where there are a lot of resources, but not the main impacts of climate change.

CMIP models, however, have inherent biases such as too-zonal jets, too little blocking in key sectors, and insufficient ridge amplification. And these weather patterns with e.g. meandering jet streams can have very big impacts such as floodings. This is where high-resolution models might come into play, because they are better able to represent these weather patterns. «We are now in a situation where we can run kilometer-scale models globally. A new era of climate modelling is starting that allows us to look at mesoscale processes and their role in the climate system!», Andreas Prein happily announces. This is what the ETH has done now in this research project where they run a global model with a resolution of 2.5 km for four years. They also compared different grid spacing and their respective abilities to simulate heavy rainfall, which also determines how well a model can forecast storms. At 40 km resolution, the model performed poorly. Starting at 5 and 2.5 km grid spacing, the model was much better able to simulate the observed cyclone than traditional weather forecast, which is a promising result. Wrapping up, Prein does not fail to mention: just increasing the resolution is not enough! You also have to heavily invest in model development. The high-resolution models will not replace causal resolution models as the two types have complementary strengths and together improve our overall picture.

On the supply side, Lewandowsky points out how much money flows into climate disinformation to strategically push for certain political agendas and protect vested interest in the fossil fuels industry. More concretely, U.S. conservative think tanks that engaged in climate denial had an annual income of around 900 million dollars, and around 2 billion US dollar were spent lobbying congress against climate change legislation between 2000–2016. In Europe, the scale is a bit different but the picture is the same: around 71-87 million euros were spent lobbying the EU Commission against climate legislation. And the disinformers’ strategy seems to be working: media and politicians adapted their rhetoric to the storylines of these conservative think tanks and disinformers, as Lewandowsky point out.

But why does the story we are being told by disinformers seem to be more convincing? Lewandowsky dives into the specific rhetoric being used by climate sceptics and why it works better to convince people of their arguments than the rhetoric being used by scientists. A study is presented where it was found that the NIPCC (the Nongovernmental International Panel on Climate Change by the Heartland Institute) uses much clearer certainty language than the IPCC (Intergovernmental Panel on Climate Change by the UN). Disinformers further practice a tactic called cherry-picking, where they take out only a certain small part of the data that supports their claim while disregarding the general trend. To prove that the claims made by disinformers are objectively wrong, Lewandowsky and colleagues performed an experiment in which they took climate data and representative contrarian statements, removed the climate context by translating the same statistical logic into other domains, and then asked statisticians whether the claims made about the data were true. Reassuringly, the claims made by deniers were identified as wrong, the ones made by mainstream science were identified as true. So even if the topic is different, scientists are objectively able to tell that claims made by deniers are wrong.

Lastly, Lewandowsky wants us to understand which types of people reject (climate) science and why. His research finds a strong link between conservatist beliefs and (climate) science denial. But what has science done for conservatists to make it so hard for them to support it? Lewandowsky claims that science has increasingly dismantled the idea that humans are a special species (which is a belief closely tied to religion and conservatism). Another argument he makes is that the norms of science (disinterestedness, communism, universalism etc.) are not compatible with conservatism. What to do? Even though deference to consensus can be epistemically justified (for reasons of social calibration, concilience of evidence, and social diversity), Lewandowsky argues that it is important to communicate the overwhelming consensus on climate change that exists in the global research community. He also argues that the best way to protect science is to protect democracy.

Concerning the first thesis, Claudia Brühwiler, who is an expert on the US, argues that it is important to distinguish between science as an ideal vs. a scientific institution in this discussion. What is happening in the US right now is, according to her, much rather an attack on institutions in general. US universities have historically been places of the dissident left, where countermovements, or what the conservatists have been calling the “corrosion of morals”, have formed. What we are witnessing now is the culmination of this rejection of institutions and of the so-called corrosion of morals with an attack on universities by the current government, she states. Tobias Brosch, a psychologist at University of Geneva, argues that compared to the US, Swiss scientists live in paradise. They have a lot more freedom in terms of deciding where and what they want to investigate, as well as relatively independent institutions allocating funding. However, he is starting to see concerning tendencies, e.g. an imbalance between social and natural sciences in who gets funding from the national government. They also decide on the overall research budget, which has been cut recently. Even though these developments might seem minor and feel like complaining at a high level, we need to keep an eye on them to be able to counteract them, he argues. Viktoria Cologna, group leader of the Climate and Societal Change Group at EAWAG, adds her research found that a majority of the public actually doesn’t support budget cuts in research and when the government cuts the budget for research nonetheless, this has a trickle-down effect on the public’s trust and belief in science.

Is disinformation the result of a media crisis in Switzerland? Brosch starts by pointing out the difficulty of measuring disinformation in the first place. He says even though there is some misinformation in Switzerland, there are no big institutions promoting it like in the US. And also the public is less susceptible to it, because it is more strongly involved in the democratic context because of the frequent votes it is encouraged to participate in. Toralf Staud adds that yes, media concentration and monopolisation in Switzerland do have something to do with the ad revenue crisis. However, he is convinced that the lack of regulation for social media, or algorithm-driven media as he calls it, plays a bigger role. He argues that there is a big mismatch between responsible reporting through the two types of media, which results in disinformation. We can observe that public debates become less informed as a result of it, he points out. Cologna adds that most people are able to distinguish fake news from real news, but that they in general have a tendency to reject news or be sceptical of them. Generally speaking, people with a higher trust in science also have a better media literacy.

But how do we counter this disinformation trend? Brosch questions the efficacy of debunking. He poses that strategic construction might have a boomerang effect. So instead of debunking disinformation or misinformation, to we need to engage in prebunking (i.e. prime people that they might be misinformed in the future? He argues that all these strategies tend to have effects, but that they tend to be relatively small. We are currently lacking the right systemic solutions and how to combine these different approaches, he states. The most promising ways to counter disinformation according to him are media literacy trainings, and regulations on the information source (i.e. regulating social media). Last but not least, he points to the importance funding for public media outlets in order to have credible alternatives.

Should scientists just simply become better communicators and the problem will be solved? Yes, argues Cologna, the public has new and different expectations towards scientists to engage in the science-policy interface. Staud puts this statement into perspective: Scientists are much rather one solution amongst many. He argues by talking about uncertainty, scientists are sending the wrong message to the public and that there is a lack of a clear voice from science. Brosch, on the other hand, thinks that the disagreement is not in the facts about climate change anymore, but much rather what to do about it.

Now it’s the public’s turn to ask questions. Karin Ingold makes the start by asking that yes, people expect scientists to play a bigger role in policymaking, but do scientists actually want to impact policy more? Cologna answers that with this new role of scientists, scientific institutions need to assist scientists in this translation work and names the Einstein School of Public Policy as an example. Brosch goes one step further to ask what are the roles that scientists can and should have? He argues for a clear distinction between being a knowledge broker and an activist as a scientist. Knowing that science and facts only make for one third of decision-making, scientist should not advocate for specific outcome, but much rather show the different options at hand.

The Arctic warms at a pace 3-4 times faster than the global average. However this warming pattern is not regular across the arctic. There has been record-high circumpolar greenness; the arctic tundra has entered a historically unprecedented state.The flora has changed from dry communities causing almost no methane emissions to moist communities. This, in turn also makes for higher greenhouse gas concentrations, which then again reinforce the observed warming trend. Hence, vegetation is an important predictor for arctic summer surface energy fluxes. Permafrost people are starting to understand that they have to include vegetation type in their energy flux calculations. More concretely, a new Arctic means a new era of bioclimatic extremes, such as floods, droughts and fires. This impacts no only local research stations, but more importantly indigenous peoples and wild animals inhabiting these areas. Schaepman-Strub further highlights that we might be reaching another tipping point as the tundra vegetations stops to recover and the fires accelerate the cycle into shifting into shrub-dominated ecosystmes. The developments in the Arctic are happening so fast as to cause researchers to consider making an exception to apply geoengineering in the Arctic in order slow down the warming of this region and to save arctic ice. The latter is not only important for the local ecosystem, but also has global effect because of the albedo changing, further accelerating warming trends. However, geoengineering remains a very controverse issue. There are also calls to involve more indigenous knowledge. While these efforts are commendable, it is also important to consider how hard it is to have one voice represent very diverse indigenous communities. In her concluding remarks, Schaepman-Strub points to the international polar year 2032-33, which she is hopeful will help to ramp up research being done in this very important field.

Masson-Delmotte’s insights into the internal workings of the IPCC prove the current political challenges in climate change research: for instance, the IPCC member states have still not come to an agreement on the timeline of publication of the reports of the Seventh Assessment Cycle. Instead, there have been strong political discussions whether the publication should take place before or after the second global stocktake, which is planned for COP33 in 2028. Masson-Delmotte states that she has seen the motivations to study climate sciences change: now it is not only the physical science basis that sparks young researchers’ interest, but also the desire to contribute to global sustainability transformations. The sees the role of researchers threefold: they are responsible for 1. the creation of facts, 2. co-construction, 3. assuming a watchdog role (when things derail). To illustrate how obstruction is making climate research more difficult, she gives the example of how scientists can establish when warming threshold is reached? A seemingly straight-forward task, but there are many, partially political decisions you need to make: you need to consider which reference period you’re comparing to, you need to consider different models and you need to see how many years on average you take. Furthermore, future warming depends on future emissions. And here, the uncertainty is growing, which is at least partially due to political obstruction (i.e. national emission reduction plans can change abruptly and radically). Climate obstruction can be understood in different ways, but according to Mason-Delmotte includes strategies to minimze env. Degradation, reject clean tech and societal transformations, manipulations strategies, control of media through e.g. social network algorithms and training of AI, joint attacks on environmental protection, public regulation agencies, and related sciences (as can be currently observed in Argentina and the US). The challenges raised by these obstruction tactics are numerous: some countries might be losing one generation of climate scientists, many essential climate variables depend on one country for monitoring ( and if we lose ability to monitor them, we are flying blind), there might be too high of a reliance on technological solutions such as Carbon Dioxide Removal strategies without addressing the multiple ethical challenges that come with it, and there is, more generally speaking, the risk of the economy of promises.

To counter obstruction, she highlights the importance of science unions (to support scientists facing layoff but also to promote work in international organisations when governments cuts funding) and of collective initiatives. Other solutions she mentions are: diversify science communication, tailoring communication and communicating through local communities and newspapers, forge strategic alliances (such as public health and climate alliances highlighting connected topics and co-benefits), stimulate non-partisan political debate, crowdfunding for science, and the proclaiming of a new understanding of science where what we do here also depends on the ability to provide resilience in other places of the world. She concludes by stating that we need to make science personal and political and support science activism.