US: Using satellite data and complex calculations, scientists from Pacific Northwest National Laboratory (PNNL), US, were able to measure how pollution particles affect clouds. Using this new metric, scientists revealed that aerosols” effects on clouds are overestimated by as much as 30 percent in a global climate model.
“Our study helps narrow the large aerosol-cloud interaction uncertainties in projections of future global warming,” said Dr. Minghuai Wang, atmospheric scientist at PNNL and lead author of the study. “Wide ranges of estimates in aerosol effects on clouds have made it challenging to understand how clouds really affect the climate.” This study shows how satellite observations can be used to hone in on aerosol effects on clouds and make it possible to better understand how clouds will affect climate.
“The use of satellite observations in studying climate processes like these is absolutely critical because it is the only way to obtain cloud and aerosol measurements over the whole globe,” said Dr. Mikhail Ovchinnikov, PNNL atmospheric scientist and co-author of the study.
The study, led by PNNL scientists, constructed a new metric for rain frequency susceptibility, and then closely correlated that metric to the aerosol effect on cloud amount, which is the total amount of water in the cloud and the cloud”s size. This metric, along with satellite measurements, was then used in three global climate models to find new ranges of cloud amount change due to pollution-caused aerosol particles, compared to current estimates.
The team, for the first time, used “A-Train” satellite observations which collect coincident global measurements of aerosols, clouds, and precipitation to develop a new metric, termed rain frequency susceptibility or “S-POP.” This metric provides a quantitative measure of the sensitivity of rain frequency to the amount of aerosols in clouds. They showed how S-POP is closely correlated to aerosols” effects on cloud amount, using three global climate models, including a multi-scale aerosol climate model developed at PNNL (PNNL-MMF) that embeds a cloud-resolving model at each grid column of a host global climate model.
Finally, the relationship between S-POP and the aerosol effects on cloud amount from the global climate models together with the observed rain frequency susceptibility from A-Train observations were used to estimate aerosol effects on cloud amount in global climate models. They showed that in one global model, the National Center for Atmospheric Research”s Community Atmosphere Model version 5 (CAM5), aerosol effects on clouds were overestimated by 30 percent.