Understanding the behavior of clouds is key to any accurate projection of future climate (as we’ve covered in the past) because of the complex, competing effects that clouds have on Earth’s energy budget.

Radiation from the sun in the form of visible light (which climate scientists refer to as "shortwave radiation") is reflected back into space by clouds. An increase in clouds (caused by increasing evaporation that comes with higher temperatures) will thus decrease temperatures by reducing incoming shortwave radiation. We call that a negative feedback—it acts to keep temperatures stable.

But water vapor is also a strong greenhouse gas. In fact, compared molecule for molecule, water vapor absorbs 100 times more outgoing infrared (or "longwave") radiation than does carbon dioxide. That means increasing evaporation will cause temperatures to increase even more. That’s a positive feedback—it acts to exacerbate rising temperatures.

(Despite its greenhouse potency, water vapor provides a feedback, not a forcing—it can’t initiate temperature increases because its presence in the atmosphere depends on temperature, unlike carbon dioxide or methane.)

If you want to project future climate change, you need a solid handle on how these competing feedbacks balance. What are the conditions where increasing evaporation will lead to more cloud formation? How much will cloud formation increase? Will it balance out the greenhouse effect of the water vapor?

These aren’t easy questions to answer, and this uncertainty accounts for much of the uncertainty seen in climate projections. Models that project a planet that is 1.7 to 4.4°C warmer by 2100 would give us a tighter range if we could model clouds more confidently.

Modeling problems

A recent paper in Geophysical Research Letters describes which facets of cloud behavior are giving the modelers problems; it does so by comparing the cloud feedbacks in twelve models cited in the most recent IPCC report. The researchers ran each model through to 2100 with the same emissions scenario and observed how the impact of clouds on Earth’s energy budget changed results by the end of the century.

First, the researchers considered the question of shortwave and longwave feedbacks. They found that the longwave feedback was pretty consistent across all models, and strongly positive (read: bad). The shortwave feedback was a different story—it ranged from a slightly negative to a strongly positive feedback and accounted for most of the difference among the models.

The authors also looked at the vertical distribution of clouds. Like the longwave feedback, high-level clouds showed a strongly positive feedback that was consistent across the models. Most of that positive feedback came from changes in the exact elevations of clouds, and not from changes in the amount or properties of those clouds. That's consistent with what’s known as the “Proportionately Higher Anvil Temperature”, or “PHAT,” hypothesis. (Don’t get that confused with the “Fixed Anvil Temperature”, or “FAT,” hypothesis )

The differences among models concerned low-level clouds. The authors note that the biggest differences in low-level cloud behavior occurred in "regions associated with low-level subtropical marine cloud systems," which brings up an important point: there's a huge amount of geographical variation in these processes. The researchers aren't considering simplistic and abstract scenarios where all clouds will universally behave in a certain way; they're looking at very complex interactions of climatic factors that vary widely from place to place. Changes in cloud behavior over the equatorial Pacific look much different than those over central Europe. This is where global simulations shine—no scientist could possibly keep track of all the related interactions in their head.

So it looks like the biggest factor in climate model uncertainty is the shortwave feedback of low-level clouds. In fact, the authors get even more specific, pointing to "regions of subtropical subsidence and marine stratocumulus and trade cumulus clouds" as the biggest question mark.

Knowing what we don't know will help direct future research that aims to reduce uncertainty in climate projections. Considering that a recent study found that climate models may be underestimating the positive feedback from clouds and that temperatures could therefore end up above the projected range, it’s critical that we nail down the role clouds will play in climate change.

Geophysical Research Letters, 2011. DOI: 10.1029/2011GL047632 (About DOIs).