Climate truth-tellers

“Strange times are these in which we live in... And the person that dares to tell the truth is called at once a lunatic and fool.” This fabled remark supposedly made by the ancient Greek philosopher Plato still holds true, at least in parts. Coal prices are near record highs in 2021, at a time when countries across the globe are speaking about carbon neutrality. Also, not long ago, climate modellers warning about global warming were being dubbed “alarmists” — the politest of all the adjectives used for them.

But climate modellers are having their day in the sun, finally. “...Our knowledge about the climate rests on a solid scientific foundation, based on a rigorous analysis of observations,” stated Thors Hans Hansson, chair of the Nobel Committee for Physics. This year, half the prize went to Syukuro Manabe of Princeton University and Klaus Hasselmann of the Max Planck Institute for Meteorology for “the physical modelling of Earth’s climate, quantifying variability and reliably predicting global warming”. The other half went to Giorgio Parisi of Sapienza University for finding patterns in complex systems1, from atomic to planetary scales.

Also recently, Friederike Otto and Geert Jan van Oldenborgh of the World Weather Attribution Project were listed among the 100 Most Influential People of 2021 by TIME.

So, what are climate models? They are computer simulations of weather patterns over time, under different conditions. Climate models, as explained by the Massachusetts Institute of Technology, must reflect the real properties of a planet’s climate, including physical laws like the conservation of energy and the ideal gas law. They must also take into consideration variables, such as air pressure and temperature. All of these are expressed as equations and solutions to these equations produce threedimensional pictures that show climate patterns like changing seasons and precipitation.

When Manabe and Richard T Wetherald became the first to use a computer model to explore the impact of increasing atmospheric CO2 on Earth’s climate and published “Thermal Equilibrium of the Atmosphere with a Given Distribution of Relative Humidity” in the Journal of the Atmospheric Sciences in 1967, they concluded that “a doubling of the CO2 content in the atmosphere has the effect of raising the temperature of the atmosphere (whose relative humidity is fixed) by about 20C”. In 2015, leading scientists from the Intergovernmental

Panel on Climate Change judged this paper the “most influential climate change paper of all time”.

For long, climate change deniers rejected these models as unverifiable and results of questionable inputs. Since the development of the very first climate models, the troposphere had been projected to warm along with Earth’s surface because of the rise in greenhouse gases. This expectation did not significantly change even with major advances in climate models later. But in the 1990s, observations didn’t show the troposphere, particularly in the tropics, was warming, even as surface temperatures were rising. These observations were then used by many to doubt the reliability of climate models. Much later it was found that those observations — and not climate models — were inaccurate.

Among early sceptics of climate modelling were climate modellers themselves, as they conceded that predictions fluctuated with the refinement of each model. But as we moved closer to the current timeline, many of those decades-old models were found to be accurate.

According to a 2019 paper by Zeke Hausfather of the University of California, Berkeley, and others, of the 17 climate models published between the early 1970s and the late 2000s, 14 were accurate in predicting the average global temperature in the years after publication.

So, what changed in climate modelling over the years? “What hasn’t changed over the years is the overall assessment of just how much the world would warm as we increased CO2,” Katharine Hayhoe of Texas Tech University and author of Saving Us: A Climate Scientist’s Case for Hope and Healing in a Divided World, was quoted as saying by National Geographic. “What has changed is our understanding at smaller and smaller spatial and temporal scales.”

Still, modellers acknowledge that the science isn’t perfect yet as all the physical processes are yet to be incorporated in models, besides there is “parametric uncertainty” — uncertainty in the model parameter values because of uncertainties in the data or the calibration process used.

Despite these challenges, the prediction of climate change without accompanying understanding of it, as put by Manabe (www.nobelprize.org), is “no better than the prediction of a fortune teller”.

1. Complex systems are systems where the collective behaviour of their parts entails the emergence of properties that can hardly, if not at all, be inferred from properties of the parts. It is best explained by the phrase: “(Something is) more/greater than the sum of its parts”