Kemi Badenoch’s announcement that the Conservatives are no longer committed to the net zero target in 2050 represents a massive breach in fifteen years of bipartisan consensus. It was greeted with predictable hostility by other parties, but also by pro-net zero forces within the Conservative party too. The Conservative Environment Network commented: ‘Abandon the science and voters will start to doubt the Conservative Party’s seriousness on the clean energy transition’.
Is the power of the demand to ‘follow the science’ losing its effect after Covid, lockdowns and the growing realisation that net zero is likely to be hugely expensive?
The very idea of ‘following the science’ is meaningless
Of all Donald Trump’s presidential appointments, one of the most striking was Jay Bhattacharya to head the National Institute for Health (NIH) as a successor to the same Francis Collins who described him as a ‘fringe epidemiologist’ who needed a ‘quick and devastating published takedown’. This is probably the most extraordinary turn around in the leadership of science ever seen.
Unlike many of Trump’s appointments, Bhattacharya seems unpartisan (it’s not at all clear he is a Republican), but also has a very clear vision of what he is trying to achieve. The scale of his victory is not only the appointment itself – Trump enjoys rubbing his opponents’ noses in it by putting forward outrageous appointments. Rather what was not covered at the hearing. Not a single Democrat mentioned the Great Barrington Declaration [lockdown letter the scientist signed]. None challenged Bhattacharya on his opposition to once-consensus opinions on lockdowns, masking, and school closures. It is as if defeat has been tacitly conceded.
In his opening statement, Bhattacharya noted how far confidence in science had fallen, including that a November 2024 Pew study reported that only 26 per cent of the American public had a great deal of confidence in scientists to act in the public’s best interest; 23 per cent have not much or no confidence at all.
He pointed to the crisis of replication in science, but also the erosion of open debate:
If confirmed, I will establish a culture of respect for free speech in science and scientific dissent at the NIH. Over the last few years, top NIH officials oversaw a culture of coverup, bias, and a lack of tolerance for ideas that differed from theirs. Dissent is the very essence of science. I’ll foster a culture where NIH leadership will actively encourage different perspectives and create an environment where scientists, including early-career scientists and scientists that disagree with me, can express disagreement respectfully.
It is easy to see Bhattacharya over the coming months systematically releasing data setting out the background for the exceptional measures taken during the pandemic, the lack of a scientific basis for them, and the steps that were taken to seek to suppress debate. And reissuing, with the Centre for Disease Control, revised advice on a proper scientific basis covering contentious areas like vaccines for children, school closures and masks. Hopefully it will spark the debate in the UK that has been lacking despite the lumbering Covid enquiry.
It will be interesting to see what impact this has on the climate debate, where intolerance of dissent has an even longer track record. For many years, climate sceptics have struggled with the ‘climate denier’ term, not least because they are themselves divided between those who genuinely doubt the existence of manmade global warming at all, and others who are sceptical about its scale, or do not believe the proposed policy response makes sense.
One response from sceptics has often been to challenge the idea of ‘settled science’ here or anywhere else. Attempting to come up with a concept of ‘settled science’ or give a percentage of scientists supposedly supporting received opinion sits oddly with the traditional view of science as an area where assumptions are constantly being tested and challenged.
There is, however, a second objection to the idea of ‘following the science’ on net zero. The complexity of the reasoning from coming up with a theoretical case for man-made global warming, measuring it, assessing the impact and then working out how best to tackle the problem covers so many scientific disciplines that no single group of scientists can claim a monopoly. And the latter stages are really about trade offs which don’t belong in the realm of science at all – with the people best placed to actually judge politicians with a democratic mandate. Perhaps climate scientists demanding politicians live up to particular policy choices should be named ‘politics deniers’.
There are four stages in the process of analysing climate change and assessing the appropriate policy response. Nobody is likely to be an expert in all of them, meaning that the very idea of ‘following the science’ is meaningless.
The first question is: all other things being equal, do man made carbon dioxide emissions lead to higher global temperatures? This seems to be basic physics. Denying this probably is questioning basic science – but it’s not clear anybody actually does doubt this. Much of the controversy seems to be about the scale of the effect, and how it interacts with natural variability.
Secondly, can we model the likely impact on the climate of emissions continuing at the current rate, or under various alternative scenarios?
This is a science too, but considerably more sophisticated. It requires an assessment of the impact of different scenarios, taking account of possible positive and negative feedback loops. For example some argue increased temperatures could release methane stored in the tundra, which would itself accelerate climate change further. Others, on the other hand, argue that warmer temperatures could lead to greater cloud cover which could itself reduce the impact of warming.
In addition, this modelling needs to determine how much of a factor man-made warming is compared to wider potentially very long term trends, for example in solar activity. Global warming could cancel out a wider cooling trend leaving the net temperature unchanged. Or it could exacerbate an existing warming trend with potentially dramatic consequences.
The modelling here is presumably a speciality of atmospheric science – but a huge range of disciplines need to feed in their insights given the number of different elements which could affect temperature.
What can a layperson contribute to this? Well, without any expertise in developing models, the common sense thing to do is to look at the assumptions feeding in to see if they make sense, and which scenarios are being used to communicate the results. It it noticeable how fond scientists and global warming communicators are of using the highest carbon scenario and describing it as ‘business as usual’.
Secondly, a layperson can reasonably ask the scientists to demonstrate how well the model fits not only the recent past, but the more distant past too – and, as time goes by, whether the modelling continues to fit the data as time passes and new data is available. This for me was what was so interesting about the ‘medieval warm period’ which was eliminated altogether in the main ‘hockey stick’ graph used to popularise the scale of the problem in the early years of this century. This did enormous damage to the credibility of climate scientists in the eyes of those, like myself, who know nothing about atmospheric physics but a reasonable amount about Roman and medieval history, whether about the population of Greenland and Iceland, glaciers in the Alps, or hundreds of other data points that were hard to reconcile with the ‘hide the warm period’ approach (which now seems to have been quietly dropped by the IPCC).
What is the right amount to spend now for the possible benefit of future generations?
The third question is what is likely to be the impact of different temperature changes forecast by the model in the last stage. How serious a problem is this? There is still a lot of work in this category for the climate scientists to do. What is the impact of higher temperature on, for example rainfall? What is the relationship between raised temperatures and local extreme weather like hurricanes?
But to come to a sensible feel for the scale of the damage, I would say that once we have reached this category, the analysis explodes into a huge range of other scientific disciplines. The impact of weather on crop yields falls to agronomists, temperature’s impact on health and disease to the medical sciences. Economics starts rearing its head too. Even with agreed temperature impacts, the harm they might do is often mediated through economic trends too. For example, as societies get wealthier we seem increasingly to live in areas vulnerable to hurricanes, but houses are ever more robust and less likely to be destroyed by them.
The job of brokering these contributions from all over science becomes increasingly challenging, and no scientist can possibly have a robust grasp of all the underlying research. As for a layperson, the priority again is to understand and kick the tyres of the underlying modelling. For example, is the model taking account of both harms and benefits from temperature increases? Heat deaths are one thing, but far more people die globally of cold.
There are also some basic health checks in the way data is presented. By choosing the ‘preindustrial baseline’, we are choosing to measure the warming from one of the coldest periods for thousands of years. And here again, historical temperatures are of keen interest. It is hard to argue rising temperature is catastrophic if it brings us to similar temperatures that were associated with periods of flourishing in the past. When I was at school, the period now called the ‘Holocene Climate Maximum’ was generally known as the ‘Holocene Climate Optimum’.
The final stage is the policy response. Given a position on the likely future trends in global climate and our best assessment of how damaging man-made climate change will be, what is the right policy to follow?
These policy options are largely economic and technical – how much will individual policies cost? What will the knock-on effects elsewhere be, including the costs and benefits (say of increasing the cost of energy for low income households’ heating choices). This is a classic issue of public policy – for policy advisers to work on and ultimately for politicians to make the trade off. Large sums of money spent on net zero are a classic opportunity cost – they mean money which is not being spent on the NHS, tax cuts or international aid. There is a complex moral question too about intergenerational relationships. What is the right amount to spend now for the possible benefit of future generations?
Bjorn Lomberg has set out interesting arguments about the ‘bang for buck’ for net zero policies compared to the sums which would be needed to tackle other global problems. There is nothing that says electorates need to follow strictly economically logical choices – they are weighing up other factors including fear and risk which are even harder to quantify.
But politicians, administrators and indeed the general public need to recover their self -confidence and push back on claims that climate policy is an area that should be uniquely governed by science. The ongoing collapse in the ‘follow the science’ narrative from the Covid era helps – particularly when, as in the UK, the very same people like Patrick Vallance have moved seamlessly from lockdowns to the climate emergency. There is no scientific answer to climate change policy. They are tough political decisions in a world where, as Thomas Sowell always says, there are no solutions, only trade offs.
This article was originally published on Stephen Webb’s substack Wallenstein’s Camp.
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