Climate Science Has Huge Error Bars
If one of your major model inputs is off by up to 50%, what does that do to the precision of your predictions about degrees of temperature change a century from now?
The politics of climate change rests on scientific models, about which the consensus voices audacious certainty. The press browbeats “climate skeptics” as denialists or worse, and pads their triumphant announcements with statistics on how many scientists agree that global warming is real, and is one of the biggest threats facing humanity.
Against that backdrop, look what Ohio State News announced this week: “How much snow accumulates in North America each year? More than scientists thought.” How much more? “If distributed evenly, 7.5 inches of snow would cover the entire continent.” That’s a lot of snow. And that’s a lot of error:
There’s a lot more snow piling up in the mountains of North America than anyone knew, according to a first-of-its-kind study.
Scientists have revised an estimate of snow volume for the entire continent, and they’ve discovered that snow accumulation in a typical year is 50 percent higher than previously thought.
In the journal Geophysical Research Letters, researchers at The Ohio State University place the yearly estimate at about 1,200 cubic miles of snow accumulation. If spread evenly across the surface of the continent from Canada to Mexico, the snow would measure a little over 7.5 inches deep. If confined to Ohio, it would bury the state under 150 feet of snow.
If the climate models are so reliable, one would think the inputs are reliable, too. The paper, however, begins, “Despite the importance of mountain snowpack to understanding the water and energy cycles in North America’s montane regions, no reliable mountain snow climatology exists for the entire continent.” Given America’s pre-eminent position in science, it seems likely that the snowfall estimates for Asia, Africa and the other continents are even less reliable.
Old estimates tended to focus on flat plains, but mountains (which are harder to get measurements from) hold the vast majority of snow. The Canadian Rockies and 10 other mountain ranges hold 60% of snowpack despite having only 25% of the land surface. The old estimates had things backwards:
Whereas scientists previously thought the continent held a little more than 750 cubic miles of snow each year, the Ohio State researchers found the total to be closer to 1,200 cubic miles.
They actually measure snow-water equivalent, the amount of water that would form if the snow melted—at about a 3-to-1 ratio. For North America, the snow-water equivalent would be around 400 cubic miles of water—enough to flood the entire continent 2.5 inches deep, or the state of Ohio 50 feet deep.
And while previous estimates placed one-third of North American snow accumulation in the mountains and two-thirds on the plains, the exact opposite turned out to be true: Around 60 percent of North American snow accumulation happens in the mountains, with the Canadian Rockies holding as much snow as the other 10 mountain ranges in the study combined.
The researchers realize this is extremely important to the proper understanding of climate change. Michael Durand, professor who oversaw the data collection by two grad students, came very close to calling this a ‘whoops’ moment for the global climate community:
“Each of these ranges is a huge part of the climate system,” Durand said, “but I don’t think we realized how important the Canadian Rockies really are. We hope that by drawing attention to the importance of the mountains, this work will help spur development in understanding how mountains fit into the large-scale picture.”
At least snow sits long enough for satellites and ground crews to take measurements if they can get to them. Some climate inputs are even more sketchy to measure: clouds, for instance, which are constantly changing. Temperature data points are always oscillating every day and night on every point on the globe and through the seasons. Exactly how reliable are climate models?
Climate change is off-topic for CEH, but the principle here applies to other matters of consensus. Like the Darwin Party consensus, the global-warming consensus tends to be audacious and overconfident, influencing governments of the world with their highly public warnings at global summits. Everyone assumes the models are correct or close to correct, but here is one input that was 50% wrong, and was wrong the wrong way. It makes the earth colder, not warmer! Climate science is mostly about observable, measurable data, except when researchers make assumptions about past climate millions of years ago, or try to predict future climate trends for decades or a century. How much more unreliable are Darwinian assumptions about the unobservable past? The only record of the past, the fossil record, shows mostly abrupt appearance, stasis and extinction – not evolution. This leads to a law of science: audacity in a consensus is directly proportional to uncertainty in the data.