Scientists have to look at today's clouds to understand how they work. But, accurately capturing clouds' impact on the climate in computer climate models has proved to be notoriously difficult. A new study in the Proceedings on the National Academy of Sciences suggests why. Either the models are failing to capture clouds in sufficient detail, or the tiny airborne particles that help trigger cloud formation, called aerosols, are now so pervasive in the atmosphere thanks to modern-day pollution that their specific effects on clouds are hard to pin down.
Researchers from Pacific Northwest National Laboratory found at least two ways to potentially improve how the clouds are simulated in climate models. One is to better differentiate cloud types in models to account for their variability. Another would be to study clouds that are not influenced by the pollution that humans have been putting out since the Industrial Age started.
"We might have to find clouds far away from civilization," said study author Steve Ghan PNNL atmospheric modeler. "There are parts of the world that are pretty darn clean."
To see how well cloud and aerosol measurements are represented in today's climate models, PNNL's Ghan and colleagues compared different models to each other and to measurements and examined how they re-created the past and present. They did this by essentially taking apart the simulations and testing the pieces. The team looked at the results of individual components of the equations that make up the simulations. The relationship between the pre-industrial and present day values of any given component, say, the changes in the concentrations of cloud droplets resulting from a change in aerosols, should be the same across the nine different computer models they tested and should be reflected in data from observations.
The team found, however, that pre- and post-industrial values didn't agree, and in some cases the there was even a difference in sign (that is, one model yielded a positive value while another yielded a negative one).
That indicated they could not model pre-industrial clouds using measurements that have been collected in a post-industrial world.
"Present day variability doesn't apply to pre-industrial times because everything's different now that we've been putting greenhouse gases and pollutants in the air for so long," said Ghan.
It's just a fact of a climate researcher's life: there are either no scientific observations from pre-industrial days, or the data that can be gathered may be marked with the brush of modern times. So it is with trying to understand today's cloudy skies. To know how much clouds have changed over the centuries, researchers need to understand what clouds looked like before humans pumped decades of pollution into the skies.
Why do the researchers care so much about clouds? Clouds—if they unlock their secrets—could tell a remarkable story about what goes into the atmosphere, what happens when it gets there, and how it affects the very basic needs of humankind: warmth and cooling, climate, precipitation, and breathable air. Research turns to models to solve these problems because working out how they behaved before the Industrial Age might ultimately help us better determine how much the world will eventually warm up.