Atmospheric Sciences Research Spotlight

Modeling the Effects of Clouds on Climate

New research investigates how mixed-phase cloud partitioning and cloud cover compensate each other in GCMs.

Source: Journal of Advances in Modeling Earth Systems (JAMES)


Clouds have a complex and intricate relationship with the climate. They can cool Earth’s surface by reflecting the incoming rays of the Sun, but they can also warm the atmosphere by absorbing the heat emitted from the planet’s surface. Climate, in turn, can affect the clouds. This relationship is complicated by the fact that not all clouds are created equal; clouds that are supercooled with temperatures between 0°C and −40°C consist of a mixture of liquid and ice, and these two phases have different microphysical and radiative properties. Liquid-filled clouds are composed of small droplets that have a higher albedo (the whiteness of the cloud, or its ability to reflect sunlight) than ice clouds, which contain larger and less reflective ice particles.

Because of the difficulties inherent in representing the dynamics of mixed-phase clouds, there is a lot of variation in how they are portrayed in global climate models (GCMs). Here McCoy et al. show this diversity using the temperature at which ice and liquid are equally prevalent within clouds (T5050). The researchers calculated the T5050 for 26 different global climate models.

They found that the T5050 affected clouds in the current climate in two different ways. In models where T5050 was high (that is, ice forms at warmer temperatures), there was less liquid in supercooled clouds and more ice, which makes sense. However, in these same models, the cloud cover was found to be higher—which did not make sense. Ice crystals should precipitate more readily and decrease the cloud cover, not increase it. The occurrence of cloud albedo and coverage were having compensating effects on the total amount of sunlight being reflected in a given climate model. That is to say, the clouds in high-T5050 models were less white because they were composed of ice rather than liquid, but there were more of them. The combination of these effects led to roughly the same amount of light being reflected by all the different GCMs, even though their individual cloud properties varied widely.

Next, the authors investigated how this apparent tuning between mixed-phase properties and cloud cover affected the cloud feedback. In models with a higher T5050, more ice was available in the current climate to transition into bright liquid droplets as the climate warmed. Because of this, the cloud feedback in regions with lots of mixed-phase clouds was more negative in high-T5050 models. One would expect that the climate sensitivity in these models would be lower. However, in high-T5050 models, the cloud coverage in the subtropics was found to decrease as the climate warmed, leading to a positive cloud feedback in that region. This effect appeared to be due to tuning between cloud cover and mixed-phase partitioning in the current climate, but it led to the subtropical and extratropical cloud feedbacks roughly compensating each other.

Finally, the team reports that the cloud albedo feedback in middle to high latitudes might be “unrealistically negative” in the models examined because the measures of T5050 in the GCMs examined in this study were higher than inferred by either satellites or ground-based lidar observations. This result is consistent with other recent research. The authors note that mixed-phased clouds must be more carefully vetted in future models to reduce biases in albedo and to reduce the uncertainty in cloud feedback and climate sensitivity. (Journal of Advances in Modeling Earth Systems (JAMES), doi:10.1002/2015MS000589, 2016)

—Wudan Yan, Freelance Writer

Correction, 15 April 2016: In an earlier version of this article, the image was incorrectly identified as being in false color. The photo caption has been updated to correct this inaccuracy.

Citation: Yan, W. (2016), Modeling the effects of clouds on climate, Eos, 97, doi:10.1029/2016EO049999. Published on 11 April 2016.

© 2016. The authors. CC BY-NC-ND 3.0