Editor’s Note: Today we welcome Katie Pflaumer to the WWAT writing team.
The most recent ice age lasted tens of thousands of years—but there were times when you wouldn’t have known it. As glaciers advanced and retreated, you could sometimes find a whole Game of Thrones-level ice sheet just hanging out in New York or Minnesota. But then suddenly, boom, the temperature would skyrocket, and you’d be left with just mud, lakes, and rocks of suspicious origin to show where the monstrous ice had been.
You’d get a nice break from the frozen world for a bit… Until the ice crept back again, grinding down the landscape and ruining the wooly mammoth bikini industry.
We call these balmier times interstadials, because they’re in between stadials (i.e., glacial periods). Why are they called stadials? If you figure that out, let me know. The best I could find is that a “stade” used to be a term for a stage in time. Or a measure of the length of a stadium, which is less helpful.
The transition from glacial to interstadial periods could happen within decades, with ice cores documenting a sudden average temperature increase of around 10°C in the Arctic. The return of the ice, on the other hand, usually took hundreds or thousands of years.
Climatologists call this rapid temperature switch a Dansgaard-Oeschger (DO) event, because it’s important that any fast process have a name that takes a long time to say.
Understanding interstadials may help us understand the tipping points we’ll see with our own changing climate. But it’s been hard to pinpoint the exact cause of these events, because there are a lot of different climate processes that can have opposite effects. For example, ice on the surface of lakes and oceans can act as a blanket, keeping the water below warmer than it’d be without the ice. And melting ice can weaken ocean circulation, shutting down heat flow to the Arctic thus causing cooling. All this—when put together—makes for a mess for scientists to untangle. Which, when you look at a temperature chart of the last ice age … sounds about right.
No one factor can totally explain the pattern of DO events, but a new model created by Keno Riechers, Georg Gottwald, and Niklas Boers (published in the Journal of Climate) may have managed to elegantly put it all together.
They built a computer model that makes assumptions about how moving from glacial to interstadial time might work. Running the model showed a pattern very similar to the one seen in real-life records from Greenland ice—abrupt shifts to “warm” mode, followed by a gradual shift back to cool, with a sudden dip back to extreme cold at the end. The similarity suggests that the assumptions in their model may be right.
The key is sea ice—and noise. They authors suggest that the ice age featured intense natural variability (“noise”) which sometimes had an outsize effect during this extremely cold period. In their model version of the ice age, when that variability pushes sea ice levels down past a certain critical threshold, in the words of the authors, “the system takes a prolonged excursion in state space with a two-stage relaxation process, of which the first stage can be identified with interstadial climate conditions.”
An excursion sounds like fun for the whole family, at least until the kids get hangry. But what the authors mean is: when sea ice in the model reaches “supercritical” low levels due to climate noise, it launches the whole climate system into a major shift into warmer temperatures.
Less ice means the Earth is less reflective of the Sun’s energy, so the ocean and atmosphere absorb more heat. That leads to rapid warming for a while: an interstadial. But the ocean slowly starts losing heat again, now that it’s missing its nice, insulating ice blanket. The temperature creeps down, the ice starts to recover, and: cold snap. We’re back to glaciers—at least until all that gosh darn noise means we need to take another excursion.
All these shifts back and forth weren’t enough to end the ice age–they were just interruptions in the pattern. But they might help us understand larger, longer-lasting shifts in climate too—including those on the horizon for us.
And Now for Something Completely Different
Researchers studied about 9,000 tweets related to an outbreak of severe storms across Ontario, Canada, that occurred in September 2016. They found the tweet authors could be categorized into two groups: key stewards (weather professionals, enthusiasts, media, etc.) who shared warnings and updates; and citizens who tended to retweet and share information the stewards were posting. What didn’t happen was a discussion about the storm. There was relatively little back-and-forth and Q&A. The dialog was mostly announcements (by the stewards) and signal amplification (by the followers). This points to an opportunity to design better social media around extreme weather events to do more than announce information but also foster discussion and learning.
We acknowledge additional contributions from Dr. Aaron Price.