Anyone who tries to keep up with climate science will know that the biggest question mark concerns the most important aspect of forecasting future warming—the computer climate models. And if you are a glutton for punishment and read (as I do) the chapters on climate models in the periodic reports from the Intergovernmental Panel on Climate Change you will know that the single biggest problem for climate models is understanding and predicting cloud behavior (and water vapor generally). Because clouds both trap heat—but also reflect heat—and come in many different kinds, the sign of cloud “forcing” (that is—is their effect positive or negative on temperature) is highly variable, depending on circumstances. Even the time of day clouds form and dissipate can have a large effect on temperature. Hence the IPCC reports always say that the level of confidence in our grasp of cloud dynamics is “very low.” (But never forget—The science is settled! Shut up and pay up.)

This is what makes all the more interesting a new study in Nature that came out just before Christmas, and might have disappeared if Princeton University didn’t publicize it this week because its authors are Princeton researchers. The full study is called “Diurnal cloud cycle biases in climate models,” and you can see from the title why it might be missed. Here’s the abstract:

Clouds’ efficiency at reflecting solar radiation and trapping the terrestrial radiation is strongly modulated by the diurnal cycle of clouds (DCC). Much attention has been paid to mean cloud properties due to their critical role in climate projections; however, less research has been devoted to the DCC. Here we quantify the mean, amplitude, and phase of the DCC in climate models and compare them with satellite observations and reanalysis data. While the mean appears to be reliable, the amplitude and phase of the DCC show marked inconsistencies, inducing overestimation of radiation in most climate models. In some models, DCC appears slightly shifted over the ocean, likely as a result of tuning and fortuitously compensating the large DCC errors over the land. While this model tuning does not seem to invalidate climate projections because of the limited DCC response to global warming, it may potentially increase the uncertainty of climate predictions.

You will see the abstract is very careful at the end to say that they aren’t saying that projections are large warming aren’t necessarily wrong, just merely that the uncertainty may be even larger than we thought. (But never forget—The science is settled! Shut up and pay up.)

The Princeton Environmental Institute’s write up of the study is written in much plainer English, and highlights this very important point:

Porporato and first author Jun Yin, a postdoctoral research associate in civil and environmental engineering, found that not accurately capturing the daily cloud cycle has the sun bombarding Earth with an extra 1-2 watts of energy per square meter. The increased carbon dioxide in the atmosphere since the start of the Industrial Age is estimated to produce an extra 3.7 watts of energy per square meter. “The error here is half of that, so in that sense it becomes substantial,” Porporato said.

In other words, not getting cloud timing right could lead to an overestimate of solar radiative forcing, which is a big deal. To continue:

Yin and Porporato undertook their study after attending a seminar on cloud coverage and climate sensitivity. “The speaker talked a lot about where the clouds are, but not when,” Yin said. “We thought the timing was just as important and we were surprised to find there were fewer studies on that.” Clouds change during the day and from day-to-day. Climate models do a good job of capturing the average cloud coverage, Yin said, but they miss important peaks in actual cloud coverage. These peaks can have a dramatic effect on daily conditions, such as in the early afternoon during the hottest part of the day. “Climate scientists have the clouds, but they miss the timing,” Porporato said. “There’s a strong sensitivity between the daily cloud cycle and temperature. It’s like a person putting on a blanket at night or using a parasol during the day. If you miss that, it makes a huge difference.”

Prediction: This study, and whatever follow ups it generates, is going to figure prominently in the next IPCC climate modeling chapter.

But never forget—The science is settled! Shut up and pay up.