Katharine Hayhoe knows that climate models are not perfect.
“The more you know about models, the less you trust them and the more you blow their tires,” says Dr. Hayhoe, co-director of the Climate Science Center at Texas Tech University.
Why we wrote this
When planning for the future, certainty can be hard to come by. This is certainly the case when it comes to climate change. Yet scientists still insist on confidence in their models. Why?
Yet she and thousands of scientists around the world are banking on these simulations as benchmarks for the future of the planet. What makes them so confident?
On the one hand, the models are constantly monitored and checked against observations: they are run in the distant past, in the recent past, on other planets. They enter into current conditions and are limited by the laws that govern the Earth’s climate system.
Rather than blindly trusting models, climatologists are constantly questioning them, trying to better understand what they are good at and where they are less certain.
Even these uncertainties hold lessons, says Duke University climatologist Drew Shindell.
“Uncertainty doesn’t mean you shouldn’t act because you don’t know the outcome,” he says. “That means you have to be very careful about extremes, because you can’t rule them out.”
Boulder, Colorado.
There is a common adage among scientists and statisticians: “All models are wrong, but some are useful.”
This is certainly true in the modern world, where – despite the fact that they are by nature mere shadows of real-world scenarios – computer models serve as vital benchmarks in some of the most complex and dangerous activities. of humanity, from building skyscrapers and bridges to air and space travel.
In the world of climate science, the models have come under particularly intense scrutiny, with some skeptics dismissing them entirely. At the same time, thousands of scientists are betting on these models as benchmarks for the future of the planet. What makes them so safe?
Why we wrote this
When planning for the future, certainty can be hard to come by. This is certainly the case when it comes to climate change. Yet scientists still insist on confidence in their models. Why?
“[Climate] models encapsulate everything we know about how the world works,” says Andrew Gettelman, senior scientist at the National Center for Atmospheric Research in Boulder, Colorado.
The equations that underlie them are the ones we use over and over again and are woven into the fabric of our lives. “If we didn’t understand thermodynamics and if we didn’t understand water and how water condenses, internal combustion engines wouldn’t work,” he says. “If we didn’t understand fluid dynamics, we couldn’t predict the weather, we couldn’t run pipe systems and run chemical plants. Nothing about the physics of climate models is new.
That said, today’s models are incredibly complex, taking into account a multitude of processes that affect climate, and uncertainty is part of their DNA. They offer a range of scenarios based on human actions – the choices we make around mitigating carbon emissions, for example – but there is also uncertainty in the predictions each model gives, and a difference in what what the best used models tell us.
Take the most basic: the long-term global temperature increase. Kate Marvel, a climatologist at NASA’s Goddard Institute for Space Studies, notes that what models predict ranges from a warming of 1.5°C to 4.5°C – and that gap hasn’t materially changed as models became more sophisticated.
“It’s kind of crazy,” says Dr. Marvel. “A degree and a half is not so bad, and 4 and a half degrees is totally catastrophic.”
But Dr. Marvel, and others, worry that communicating scientific uncertainty to the general public could be misinterpreted: “There is uncertainty, but there is also very, very great certainty,” says -she. “We ruled out ‘good’. ‘Good’ won’t happen.
Scientists generally welcome uncertainty, says Duke University climatologist Drew Shindell. The differences between climate models help show where they agree, and what we can really trust, and the range of results they give help us understand the risks of various actions.
“Uncertainty doesn’t mean you shouldn’t act because you don’t know the outcome,” says Dr. Shindell. “That means you have to be very careful about extremes, because you can’t rule them out.”
Simulated worlds
Much of the confusion about models stems from a misunderstanding of what they are and what they aim to do, says Dr. Gettelman. Models are not so much theoretical worlds as simulated worlds, constrained by the laws of physics and chemistry and constantly validated by observations, recent history and the deep past. Climate models are not designed to predict specific weather conditions or events, but they do predict the likelihood of weather and extreme weather conditions occurring.
Today’s models are extremely complex and require huge supercomputers to run them. The Community Earth System model that Dr. Gettelman is working on is based on some 1.5 million lines of code.
These simulations have come a long way from the basic energy balance model that Svante Arrhenius, a Swedish scientist, used to demonstrate the greenhouse effect in the 1890s. much more basic climates that scientists used four or five decades ago.
“In their hearts, [models] follow basic physical laws that are very well understood,” says Dr. Shindell. “We have theory and we have observation and we have real-world measurements that all hold together.”
Kick in the tires
Rather than blindly trusting models, climate scientists are constantly questioning them, says Katharine Hayhoe, co-director of the Climate Science Center at Texas Tech University.
“The more you know about role models, the less you trust them and the more you kick them,” says Dr. Hayhoe.
She knows what they’re good at, like simulating observed temperature changes and the jet stream. And she knows what they do less well, like modeling the rate at which ice caps melt or the rate at which Arctic sea ice is lost.
In these cases, as with extreme rainfall, many models actually underestimate how fast things are changing, says Dr. Hayhoe. Models are also better at predicting changes over a larger scale of time and space than they are at predicting those changes for smaller or shorter-term regions.
And, when it comes to the big differences between what the models are telling us, scientists have a better understanding of where that discrepancy comes from. One of the main reasons: the clouds.
The veiled view
Clouds have become a major concern for many climatologists due to the significant impact they have on climate. But cloud formations are incredibly complicated to model reliably.
Clouds have a warming effect, as they act as a blanket over the Earth. But they also have a cooling effect, as the white clouds reflect solar energy. The net effect of clouds on the planet tends to cool, says Dr Gettelman, and that’s a huge effect.
“Small changes in clouds can really amplify or dampen what we’re doing with carbon dioxide,” he says.
Given all of this, clouds are one of the most important things for a climate model, but also one of the most difficult.
The scale at which clouds form is minute: droplets of liquid water crystallize around a speck of dust. “It’s an incredibly small scale,” says Dr Marvel, “but of course climate models have to simulate the whole climate, which is the largest scale you can get, and those don’t fit very well. well together.”
To circumvent this problem, models approximate clouds in various ways, but this is an imperfect science, and much of the efforts of modellers these days are aimed at improving and refining these approximations. They are also beginning to incorporate other key elements of the climate system, such as the biological processes involved in the carbon cycle – how natural land and ocean carbon sinks might move in the future.
Build a virtual planet
Despite all these uncertainties, scientists point out that the models are consistent on the most basic points: The Earth is warming. We will have more days of extreme temperatures, with dangerous heat levels. And there will be more extreme precipitation events.
What is perhaps most disconcerting to many climatologists is the fact that with the most recent generation of models, which have worked hard to incorporate more processes and reduce structural uncertainties, many have started to work “warmer” – showing long-term temperature changes of 5 or 6 degrees C instead of 4 degrees – and it is not yet clear why.
These new models might be more accurate, Dr. Marvel says, but without fully understanding why what they’re telling us has changed, she doesn’t think their results can be fully accepted.
But what scientists point out time and time again is that the models they work with may not be perfect – and are almost certainly “wrong” on some level – but they give us the most complete and the most validated to understand the trajectory of our climate. That we have.
Essentially, models are the laboratories that climatologists use. Earth scientists can’t build anything in the real world that replicates our entire system, so “in order to conduct experiments on our planet, we have to build a virtual planet,” says Dr Hayhoe.
Climate models “are like alternate Earths on which we can conduct simulation experiments,” she continues, “which further underscores the fact that we are currently conducting an unprecedented, albeit inadvertent, experiment with our current planet, which is the only home we have.”
