How climate models got so accurate they earned a Nobel Prize

Climate predictions were treated with heavy skepticism just 30 years ago, but they've become our main window into how global warming works.

Climate modelers are having a moment.

Last month, Time Magazine listed two of them—Friederike Otto and Geert Jan van Oldenborg of the World Weather Attribution Project—among the 100 Most Influential People of 2021. Two weeks ago, Katharine Hayhoe of Texas Tech University was a guest on the popular CBS talk show Jimmy Kimmel Live! And on Tuesday, pioneering climate modelers Syukuro Manabe and Klaus Hasselman shared the Nobel Prize for Physics with theoretical physicist Giorgio Parisi—a recognition, said Thors Hans Hansson, chair of the Nobel Committee for Physics, that “our knowledge about the climate rests on a solid scientific foundation, based on a rigorous analysis of observations.”

Climate modelers are experts from earth or planetary science, often with experience in applied physics, mathematics, or computational science, who take physics and chemistry to create equations, feed them into supercomputers, and apply them to simulate the climate of Earth or other planets. Models have long been seen by climate change deniers as the soft underbelly of climate science. Being necessarily predictive, they have been tarred as essentially unverifiable and the result of flawed input producing unreliable results.

A 1990 National Geographic article put it this way: “Critics say that modeling is in its infancy and cannot even replicate details of our current climate. Modelers agree, and note that predictions necessarily fluctuate with each model refinement.”

However, more recent analyses, dating back decades, have found that many of even the earliest models were remarkably accurate in their predictions of global temperature increases. Now, as computing power increases and more and more refinements are added to modeling inputs, modelers are more confident in defending their work. As a result, says Dana Nuccitelli, author of Climatology versus Pseudoscience: Exposing the Failed Predictions of Global Warming Skeptics“there’s definitely been a shift away from outright climate science denial; because the predictions have turned out to be so accurate, it’s getting harder and harder to deny the science at this point.”

That 1990 article quoted Manabe—generally considered the father of modern climate modeling—as saying that, in some early models, “all sorts of crazy things happened … sea ice covered the tropical oceans, for example.” But in a seminal 1970 paper, the first to make a specific projection of future warming, Manabe argued that global temperatures would increase by 0.57 degrees Celsius (1.03 degrees Fahrenheit) between 1970 and 2000. The actual recorded warming was a remarkably close 0.54°C (0.97°F).

A 2019 paper by Zeke Hausfather of the University of California, Berkeley, Henri Drake, and Tristan Abbott of the Massachusetts Institute of Technology, and Gavin Schmidt of the NASA Goddard Institute for Space Studies analyzed 17 models dating back to the 1970s and found that 14 accurately predicted the relationship between global temperatures as greenhouse gases increased. (The estimates of two were too high, and one was too low.) That’s because the fundamental physics have always been sound, says Dana Nuccitelli, research coordinator at Citizens’ Climate Lobby and author of Climatology versus Pseudoscience: Exposing the Failed Predictions of Global Warming Skeptics.

“We’ve understood for decades the basic science that if you introduce a certain amount of carbon dioxide into the atmosphere we would get a certain amount of warming,” he says. “These predictions in the 1970s were remarkably accurate, but they were also using quite simplified climate models, in part because of our level of understanding of climate systems but also because of computation limitations at the time. It’s certainly true that climate models have come a long way.”

The more things change…

In the realm of climate modeling, “What hasn’t changed over the years is the overall assessment of just how much the world would warm as we increased CO2,” says Hayhoe, who is also Chief Scientist for the Nature Conservancy and author of Saving Us: A Climate Scientist’s Case for Hope and Healing in a Divided World. “What has changed is our understanding at smaller and smaller spatial and temporal scales. Our understanding of feedbacks in the climate system, our understanding of, for example, just how sensitive the Arctic really is.”

As that understanding has increased, she says, so it has allowed the development of what she refers to as “the cutting edge of climate science today”—individual event attribution, the specialty for which Otto and van Oldenberg were recognized in Time, which for the first time is able to draw strong links between climate change and specific weather events, such as heat waves in the western United States or the amount of rain deposited by Hurricane Harvey

“We couldn’t do that without models,” Hayhoe says, “because we need the models to simulate a world without people. And we have to compare an Earth with no people to the Earth we’re living on with humans and carbon emissions. And when we compare those two Earths, we can see how human-induced climate change has altered the duration, the intensity, and even the damages associated with a specific event.”

In Hayhoe’s case, the actual act of modeling involves “looking at thousands of lines of code, and it’s so intense that I often do it at night, when people aren’t emailing and the lights are off and I can focus on this bright screen in a dark room. Then I blink and it’s suddenly four-thirty in the morning.”

Much of the work, she says, requires trying to find things that are wrong in the models, to ensure they reflect reality. “If it doesn’t quite match up, we have to look harder because there’s something we didn’t quite understand.”

Whereas such discrepancies can be flaws in the models, they can sometimes reflect errors in observations. For example, a series of studies in 2005 found that satellite data which appeared to show no warming in the lower atmosphere, or troposphere, and which were used to cast doubt on global warming models, were themselves flawed. The models, supported by data from weather balloons, were right all along.

The irony, says Michael Mann, Distinguished Professor of Atmospheric Science at Penn State University and author most recently of The New Climate War, is that “climate scientists were dismissed as alarmists for the predictions that we made, but the predictions, if anything, turned out to be overly conservative and we’re seeing even greater impacts than we expected to see.”

The apparent looming collapse of the system that drives Atlantic Ocean currents is, he says, one such example. “It is something that we anticipated could happen, but it is not only happening, it is happening sooner than we expected, he notes.” Manabe, he points out, was one of those to first raise the possibility decades ago. “It just underscores that what’s happening in climate science is the worst thing that can actually happen to a climate modeler: to see your worst predictions come true.”

Modelers do acknowledge that the science isn’t perfect; even now, uncertainties remain, and not just one kind.

“Do we have all the physical processes in the model? And if we have them in there, are they correctly represented or not?” asks Hayhoe rhetorically. “Then there’s a second source of uncertainty called parametric uncertainty." Additionally, she says, some processes take place on such small scales—for example, among cloud particles—that they cannot be measured directly but must be inferred. Obviously that adds some uncertainty.” However, the greatest uncertainty, she says, lies not with the physics, but with our own collective behavior, and how much we are prepared to allow global levels of greenhouse gases to rise.

“If we didn’t know that carbon emissions produced all these impacts on us, that it isn’t just a curiosity of global temperature increase but is also our food, our water, our health, our homes, then we wouldn’t act,” Hayhoe says.

“That’s why I do what I do, and that’s why models are so important, because they show what’s happening right now that we’re responsible for, and what’s going to be happening in the future. I’m looking forward to the day when we can just use climate models to simply understand this incredible planet, but right now, these models are telling us, ‘Now is the time to act!’ And if we don’t, the consequences will be serious and dangerous.”

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