Community Atmosphere Model with a Cloud “Superparameterization.”


Clouds exist in a vast range of conditions and sizes and are, therefore, notoriously difficult to represent in global climate models. Explicitly simulating the physics of individual clouds in climate models would be prohibitively expensive computationally. Instead, clouds in global models are typically represented using parameterizations, or equations that approximate their subgrid-box effects on the larger climate system. For short simulations or small regional domains, the physics of individual clouds has been included, using an embedded cloud resolving model (CRM). Recently, an intermediate approach, called cloud “superparameterization,” has been developed. A team, including U.S. Department of Energy scientists at Pacific Northwest National Laboratory, introduced a cloud superparameterization to the Community Atmosphere Model (CAM). The team’s superparameterization is a two-dimensional version of a CRM that captures the cloud updrafts and downdrafts based on principles of conservation of momentum and energy. Embedded into a global model, the scheme is called a multiscale modeling framework. The particular multiscale modeling framework based on the CAM is called the superparameterized-CAM. Over the past several years, scientists from many institutions have explored the ability of superparameterized-CAM to simulate tropical weather systems, day-night changes of precipitation, Asian and African monsoons, and other climate phenomena. The new model has a stronger physical basis and simulates clouds and cloud-aerosol interactions that are more realistic than simulations with traditional cloud parameterizations, a capability that should improve the ability of climate models to predict climate change.


Randall, D. A., M. Branson, M. Wang, S. Ghan, C. Craig, A. Gettelman, and D. Edwards. 2013. “A Community Atmosphere Model with Clouds Superparameterized,” Eos, Transactions American Geophysical Union 94(25), 221–22. DOI: 10.1002/2013EO250001.