Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling

Expanding the Computational Frontier of Multi-scale Atmospheric Simulation to Advance Understanding of Low Cloud / Climate Feedbacks

Near completion, in no-cost extension.

The objective of this research is to better understand global low-cloud feedbacks and aerosol indirect effects by using innovative methods in multi-scale global climate simulation to explicitly resolve 250-m scale turbulent eddies that form boundary-layer clouds. Marine stratocumulus and shallow cumulus clouds and their interaction with aerosols play a critical role in climate change, but are unrealistically represented in global climate models. An outstanding grand challenge is simulating realistic eddy-cloud microphysics interactions in global models. This has proved a decades-long parameterization challenge for global climate models, leading to a large spread of simulated low cloud feedbacks and climate sensitivity that are a primary source of uncertainty in climate projections for the 21st century.  Even the most advanced global cloud resolving models (CRMs) do not exceed 1-10 km horizontal grid resolution. This does not resolve boundary layer eddies, so their key physics must still be parameterized, producing comparable modeling uncertainties to conventional GCMs. 

We propose to sidestep this problem using innovative software engineering tailored to GPU-accelerated petascale computing systems in order to explicitly resolve the important turbulent eddy scales – 250 m in the horizontal and 25 m in the vertical– in a global framework – for the first time.  This can appear computationally intractable for a global model, due to the extremely high space-time resolution needed, especially around the sharp inversions that form at the top of many marine stratocumulus cloud layers. We propose two related approaches to break this computational barrier. Both use the heterogeneous multi-scale grid approach – i.e. cloud superparameterization - but add novel computational strategies.

Project Term: 
2014 to 2019
Originating Solicitation: 
Project Type: 
University Project