09 December 2015

How Does Increasing Horizontal Resolution in a Global Climate Model Improve the Simulation of Aerosol-Cloud Interactions?



How global climate models simulate something so small as the interaction between tiny atmospheric particles and clouds can have a surprisingly big impact on results. A research team led by Pacific Northwest National Laboratory used innovative modeling and diagnostic methods to demonstrate that higher-resolution models more accurately depict the interactions between particles suspended in air, called aerosols, and the complex processes within clouds. Going further, the team identified the physical mechanisms behind the improved calculations. The results could guide the development of next-generation climate models.

"Our analyses indicate that aerosol effects on clouds change as the model detail increases," said Dr. Po-Lun Ma, the PNNL atmospheric scientist who led the study reported in Geophysical Research Letters.

"However, even in very high resolution models, there can be large differences between model results and observations," said Ma. "Such differences suggest that resolution increases are not enough, and the physical treatment of the aerosols and cloud features requires further improvement to reduce the uncertainties associated with aerosol-cloud interactions in climate models."

Scientists used the Community Atmosphere Model version 5.2 (CAM5) to zero in on aerosol-cloud interactions. To facilitate direct comparison between model simulations and satellite observations, they prescribed realistic meteorological fields such as winds and temperature while allowing the model to use equations to calculate how clouds and aerosols interact. They then examined four scenarios of varying degrees of detail. The approach allowed them to compare model results with real-world data at particular times and locations.

Climate models involve millions of calculations on such things as air flow, heat transfer, and movement of moisture through the atmosphere. Researchers examine every process to ensure it functions as close to real-world observations as possible so that results are reliable for understanding climatic changes. Unfortunately, the exact mechanisms of interactions between clouds and tiny aerosol particles from pollution, dust, and soot remained largely a mystery. This study showed that higher resolution climate models tend to more realistically depict how droplets form a cloud and how precipitation develops. The results of such models more closely match estimates based on real-world data.

Po-Lun Ma
Pacific Northwest National Laboratory
"How Does Increasing Horizontal Resolution in a Global Climate Model Improve the Simulation of Aerosol-Cloud Interactions?." How does increasing horizontal resolution in a global climate model improve the simulation of aerosol-cloud interactions? 42, 5058-5065 (2015). [10.1002/2015GL064183].

We thank the reviewers and the editor for their helpful comments. We thank Jonathan H. Jiang for his helpful advice on the susceptibility calculation. We thank Wei-Ting Chen, Stephen A. Klein, Ben Kravitz, Kyo-Sun Lim, Robert Pincus, Yun Qian, Francis Vitt, Hui Wan, and Kai Zhang for their helpful advice. The YOTC analysis is obtained from ECMWF (2010), WCRP and WWRP THORPEX YOTC Project, http://rda.ucar.edu/datasets/ds629.0/, Research Data Archive, maintained by CISL at NCAR. The CCCM data set is obtained from the Atmospheric Science Data Center at NASA Langley Research Center. For cross validation, the YOTC CloudSat-centric collocation data products are obtained from YOTC CloudSat-Collocated A-Train and ECMWF Data Distribution Portal (http://csyotc.cira.colostate.edu/index.php). This work is supported by the U. S. Department of Energy, Office of Science (BER), as part of the Earth System Modeling Program, and by the Department of Energy Early Career grant awarded to W.I. Gustafson Jr. The CESM project is supported by the National Science Foundation and the Office of Science of the Department of Energy. The CESM source code and input data sets are available at http://www2.cesm.ucar.edu/. We acknowledge the use of computational resources (ark:/85065/d7wd3xhc) at the NCAR-Wyoming Supercomputing Center provided by the National Science Foundation and the State of Wyoming and supported by NCAR's CISL. The effort of Y. Zhang and H.-Y. Ma was performed under the auspices of the Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. The Pacific Northwest National Laboratory is operated for the Department of Energy by Battelle Memorial Institute under contract DE-AC05-76RL01830.