One study suggests Arctic rainfall will become dominant in the 2060s, decades earlier than expected. Another claims air pollution from forest fires in the western United States could triple by 2100. A third says a mass ocean extinction could arrive in just a few centuries.
All three studies, published in the past year, rely on projections of the future produced by some of the world’s next-generation climate models. [bold, links added]
But even the modelmakers acknowledge that many of these models have a glaring problem: predicting a future that gets too hot too fast.
Although modelmakers are adapting to this reality, researchers who use the model projections to gauge the impacts of climate change have yet to follow suit.
That has resulted in a parade of “faster than expected” results that threaten to undermine the credibility of climate science, some researchers fear.
Scientists need to get much choosier in how they use model results, a group of climate scientists argues in a commentary published today in Nature.
Researchers should no longer simply use the average of all the climate model projections, which can result in global temperatures by 2100 up to 0.7°C warmer than an estimate from the Intergovernmental Panel on Climate Change (IPCC).
“We need to use a slightly different approach,” says Zeke Hausfather, climate research lead at payment services company Stripe and lead author of the commentary.
“We must move away from the naïve idea of model democracy.” Instead, he and his colleagues call for a model meritocracy, prioritizing, at times, results from models known to have more realistic warming rates.
Overall, climate models remain incredibly successful research tools, and nothing about this “too hot” generation invalidates the tenets of climate science, says Kate Marvel, a climate scientist at NASA’s Goddard Institute for Space Studies and co-author of the commentary.
The greenhouse effect is still warming the planet. Ice is melting, seas are rising, and droughts are becoming more frequent in some areas. But the models are not perfect, Marvel says. “They’re not crystal balls.”
The problem of the too-hot models arose in 2019 from the Coupled Model Intercomparison Project (CMIP), which combines the results of the world’s models in advance of the major IPCC reports that come out every 7 or 8 years.
In previous rounds of CMIP, most models projected a “climate sensitivity”—the warming expected when atmospheric carbon dioxide is doubled over preindustrial times—of between 2°C and 4.5°C.
But for the 2019 CMIP6 round, 10 out of 55 of the models had sensitivities higher than 5°C—a stark departure.
The results were also at odds with a landmark study that eschewed global modeling results and instead relied on paleoclimate and observational records to identify Earth’s climate sensitivity.
It found that the value sits somewhere between 2.6°C and 3.9°C. The divergence in sensitivity estimates is a “sobering example of the complexity of the climate system,” says Christopher Field, a Stanford University climate scientist who focuses on impacts.
Researchers have since tracked down the causes of the too-hot models, which include those produced by the National Center for Atmospheric Research, the U.S. Department of Energy, the United Kingdom’s Met Office, and Environment and Climate Change Canada.
They often relate to the way models render clouds; one result has been excessive predicted warming in the tropics.
Still, many of these models render the world better than their predecessors, and the centers that produced them have been open about diagnosing the problem, Marvel says. “They’re to be commended.”
But it will take years before the centers can produce new projections for broad use.
The IPCC tried to compensate for this problem last year when it published its first working group report, which covers the physical basis of climate change.
The IPCC rated models on their skill at capturing past historical temperatures. Then, it used the skillful models to produce its official “assessed warming” projections for different fossil-fuel emissions scenarios.
When it came to studying the future changes to Earth, the IPCC reported results from all the models based on the degree of warming: 1.5°C, 2°C, and 3°C.
That allowed useful information from the hot models to be used, even if they reach those thresholds too fast.
Although IPCC rose to the challenge, it didn’t do a great job telling everyone about the actual problem, says Hausfather, himself an IPCC co-author.
“A large number of our colleagues had no idea that the IPCC did this,” he says. And since then, dozens of published studies have used projections based on the raw average of all CMIP6 models.
The outcomes, they note, are often “worse” than the IPCC projections—and that has drawn attention from those unaware of the underlying problems with the models.
“It’s not because anybody is acting in bad faith,” Marvel says. “It’s just because there’s no guidance.”
Climate impact researchers need to emulate the steps that the IPCC took, Hausfather and his co-authors say. First, they should avoid the dubious time-based scenarios and instead emphasize the effects of specific levels of global warming, regardless of the date those levels are reached.
They should also use IPCC’s own “assessed warming” projections for when those warming levels might arise.
And for studies where the details of the warming trajectory are important, they can use select models that capture the warming with relative accuracy, like those produced by NASA and the National Oceanic and Atmospheric Administration, among many others.
“I agree with almost everything that the authors say and suggest,” says Claudia Tebaldi, a climate scientist at Lawrence Berkeley National Laboratory and one of the leaders of CMIP’s climate projection scenarios.
However, she says, the recommendations may underestimate policymakers’ desire for time-based information, which in her experience is nearly always requested.
And some climate impacts, like sea-level rise, change depending on the time taken to reach a warming level, not just the absolute amount of warming.
Researchers should think about even going further, and examine whether certain models have, for example, big regional biases, says Reto Knutti, a climate scientist at ETH Zürich who has called for “model meritocracy” for more than a decade.
As more city planners and outside scientists turn to these projections, they should first be sure to consult a climate model expert.
“Given that these results guide climate adaptation and investments of billions of dollars, that seems like an effort worth doing,” Knutti says.
Read more at Science Magazine
People writing about the climate change issue have the advantage of selecting the models that best fit what they are advocating. No one selects INMCM5 which most closely matches real world data. Its prediction of 1.4 degrees of warming by 2100 is worthless for advocating extreme agendas. The extreme model RCP 8.5 is much more useful for advocating a climate emergency, net zero, carbon taxes, and the end of new fossil fuel cars by 2035.
In true science, if a theory doesn’t match real world data, it is either scrapped or modified. If climate change was a true science the authors of the hot models would modify them to align with the real world and there would be no “hot” models. The problem is that the climate change movement is totally political and those creating the models are doing so to support the agenda.
The Earth Not Fragile and there is no Delicate Balance of Nature and the so called models are only as good as those who create and design them and right now we have those who are cheating and fudging with the data to get what they want
Looks like the earth’s complex & chaotic climate system is tough enough to fully understand, let alone rely on modeling (at this stage) to make coherent national energy & environmental policy. Perhaps a STEP BACK and a more rational discussion rather than PANIC with the “Climate Crisis” is a more sensible course? Better VOTE OUT a big enough “chunk” of these progressive legislators in November before they take us over the cliff…