Cooperative Institute for Research in Environmental Sciences
Thursday, June 3, 2021

Warmer clouds, cooler planet

Precipitation-related “feedback” cycle means models may overestimate warming

Big white clouds in front of blue sky
Clouds in the sky
- Marc Wieland/

Today’s climate models are showing more warmth than their predecessors, forecasting an even hotter future for the same rise in atmospheric carbon dioxide. But a paper published this week highlights how models may err on the side of too much warming: Earth’s warming clouds cool the surface more than anticipated, the German-led team reported in Nature Climate Change

“Our work shows that the increase in climate sensitivity from the last generation of climate models should be taken with a huge grain of salt,” said CIRES Fellow Jennifer Kay, an associate professor of atmospheric and oceanic sciences at CU Boulder and co-author on the paper.

She and her colleagues modified a model used in international climate assessments like the IPCC to better understand the impact that warmer clouds have on climate. 

Warmer clouds differ from their colder, icier counterparts in two main ways: (1) they are more reflective, sending more heat back into space; and (2) they don’t precipitate as easily, remaining in the atmosphere for longer periods of time. But climate models used in the IPCC don’t yet account for these differences, introducing model biases that could impact projections of future climate. 

“Climate models do not represent this precipitation efficiency difference between warm and cold clouds, so they underestimate the associated negative feedback with a transition from cold clouds to warm clouds,” Kay said. 

Constraining cloud feedback processes is important for improving future generations of climate models. In Nature Climate Change News and Views, Graeme Stephens, Director of the Center for Climate Sciences at the Jet Propulsion Laboratory, writes "Their study offers a pioneering example of how this can be done, provided the observations exist to do so. This requires a more process-centric approach to address cloud feedback quantification, which is the basis of the design for new global observing systems being planned for the coming decade.”


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