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Publication Date
26 February 2016

Today's Clouds: They Aren't Reliable Reporters

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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.

Point of Contact
Steven J. Ghan
Pacific Northwest National Laboratory (PNNL)
Funding Program Area(s)

Peter Caldwell prodded our thinking on factorization, Rob Wood coaxed us to explore the role of cloud fraction, and Nicolas Bellouin provided helpful comments. Reviewer comments were also helpful. The Pacific Northwest National Laboratory (PNNL) is operated for the Department of Energy (DOE) by Battelle Memorial Institute under Contract DE-AC06-76RLO 1830. Work at PNNL was supported by the US DOE Decadal and Regional Climate Prediction using Earth System Models program and by the US DOE Earth System Modeling program. Work of M.W. and S.Z. performed at Nanjing University was supported by the One Thousand Young Talent Program, Jiangsu Province Specially-Appointed Professor Grant, and the National Natural Science Foundation of China (41575073). A portion of this research was performed using PNNL Institutional Computing resources. The ECHAM6-HAM model was developed by a consortium composed of ETH Zurich, Max Planck Institut für Meteorologie, Forschungszentrum Jülich, University of Oxford, the Finnish Meteorological Institute, and the Leibniz Institute for Tropospheric Research, and is managed by the Center for Climate Systems Modeling (C2SM) at ETH Zurich. D.N. acknowledges support by the Austrian Science Fund (J 3402-N29, Erwin Schrödinger Fellowship Abroad). C2SM at ETH Zurich is acknowledged for providing technical and scientific support. This work was also supported by a grant from the Swiss National Supercomputing Centre under Project ID s431. D.G.P. and P.S. acknowledge support from the United Kingdom (UK) Natural Environment Research Council Grant NE/I020148/1. P.S. and Z.K. acknowledge funding from the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007–2013) ERC project ACCLAIM (Grant Agreement FP7-280025). The development of modal version of the GLObal Model of Aerosol Processes (GLOMAP-mode) within Hadley Center Global Environmental Mode (HadGEM) is part of the United Kingdom Chemistry and Aerosols (UKCA) project, which is supported by both National Environmental Research Council (NERC) and the Joint Department of Energy & Climate Change/Department for Environment, Food & Rural Affairs Meteorology Office Hadley Centre Climate Programme. We acknowledge use of the Met Office and NERC MONSooN high performance computing system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, a strategic partnership between the Met Office and the NERC. Simulations by SPRINTARS were executed with the supercomputer system SX-9/ACE of the National Institute for Environmental Studies, Japan. SPRINTARS is partly supported by the Environment Research and Technology Development Fund (S-12-3) of the Ministry of the Environment, Japan and Japan Society for the Promotion of Science KAKENHI Grants-in-Aid for Scientific Research 15H01728 and 15K12190. Computing resources for CAM5-MG2 simulations were provided by the Climate Simulation Laboratory at National Center for Atmospheric Research (NCAR) Computational and Information Systems Laboratory. NCAR is sponsored by the US National Science Foundation.