The severity and speed of climate change will depend on the quantity of greenhouse gases we emit into the sky, but also on how sensitive the climate is to those gases.
One uncertainty is how clouds will respond as the atmosphere heats up. Tapio Schneider, a climate scientist at Caltech, and his colleagues from Caltech, the Naval Postgraduate School, JPL, and MIT are building a climate model that will use machine learning, powerful computing, and petabytes of data to help resolve some of the unknowns around how, why, and where clouds form, produce precipitation, or dissipate. The goal: to cut the uncertainty in current predictions of carbon dioxide’s impact on the planet in half.
Science journalist Mallory Pickett sat down with Schneider to find out how his research will do this, and why it matters.
There is a measurement called “climate sensitivity.” It’s the global mean surface temperature increase that you get after doubling CO2 concentrations and letting the system equilibrate. With current climate models, the climate sensitivity for doubling CO2 ranges somewhere between two degrees [Celsius] warming up to five degrees warming.
Take the two-degree target of the Paris agreement. We’ve had about one degree of warming already, so it’s one more degree to go. How much more CO2 can we put into the atmosphere before we have warmed Earth another degree?
For a model that has a climate sensitivity of around two degrees, you can get to CO2 concentrations of close to 600 parts per million. We’re at 410 parts per million, so even if we continue emitting a lot, we won’t reach 600 before 2060 or so. In a model that has a climate sensitivity closer to five degrees, [one more degree requires] about 480 ppm, so that’s only about 70 to go. That’s something we’ll reach in the next two decades or so.
The single biggest contributor is uncertainties about clouds, and specifically about low clouds in the tropics. Low clouds over tropical oceans reflect sunlight because they are white, and this cools the Earth. We don’t know if we’ll get more or fewer of them as it warms, and that’s the key uncertainty in climate predictions.
One other important piece is how much carbon is being taken out by the biosphere. Right now only about half the carbon that humans emit ends up in the atmosphere. The rest is taken up by oceans and the land biosphere, and we don’t quite know where it goes.
When you put more CO2 or other greenhouse gases in the atmosphere, they absorb thermal radiation. What happens if you put more of these greenhouse gases in the atmosphere is that everything else being equal, you ought to warm the surface. The physics of that’s completely clear, undisputed by any serious scientist.
Where the uncertainties come in is to say, well, how much warmer will it get? What happens to these little clouds? They reflect a lot of sunlight. If we get more of them and more sunlight will be reflected, it will be less warming. If you get fewer of them, you have an amplifying feedback effect where you get more warming.
I think the evidence in recent years—for example, from studies looking at cloud variations over the past decades—points more toward higher climate sensitivity.
We want to use the data we have available: terabytes per day coming down from satellites. We want to assimilate those data into the model. That’s a computationally challenging task, but it’s just doable now and will give you a model that simulates a present climate better.
I would be very worried. It would mean higher heat extremes, especially in summer. It means more extreme precipitation in places like the [US] Northeast. It is possible the climate sensitivity is on the high end of what models predict, and if that’s right then we’ll experience severe impact in our lifetime, certainly in our children’s lifetimes. Simply put, the higher the climate sensitivity, the more worried we should be.