Supercomputing and Computation

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Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System


The DOE BER SciDAC funded Multiscale project is tasked to improve global Earth system models by addressing the representation of multiscale interactions among small-scale features and large-scale structures of the ocean and atmosphere. The primary goal is to produce better models for these critical processes and constituents from ocean-eddy and cloud-system to global scales through improved physical and computational implementations.

The ORNL contribution to this project is to address the time stepping methods used to integrate the model across the multiple ranges of space and time scales in the atmosphere. These include improvements to the integration of the large-scale dynamics through non-CFL limited time-stepping methods and their extension to improve the methods used to integrate the diagnostic cloud physics packages within the model. These packages are concurrently being redesigned to allow scale-aware behavior as the model is refined globally and regionally. As part of these efforts, research into scalable preconditioners and the optimized use of generic solver libraries will be key focus areas.

Related Projects

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Multiscale Methods for Accurate, E_cient, and Scale-Aware Models of the Earth System
— The DOE BER SciDAC funded Multiscale project is tasked to improve global Earth system models by addressing the representation of multiscale interactions among small-scale features and large-scale structures of the ocean and atmosphere.

OLCF CAAR project: acceleration of CAM-SE using GPU
— Future success in climate simulation requires not only added spatial resolution but improvement in the fidelity of physical processes modeled, which in turn increases the number of processes to be modeled, such as chemical tracer quantities to be transported.

Ultra High Resolution Global Climate Simulation
— The problem of predicting climate change and its consequences is motivated by the increasingly urgent need to adapt to near term trends in climate change and the potential changes in the frequency and intensity of extreme events. This project is developing the scientific framework to determine the benefit of employing very-high-resolution global models to investigate regional-scale phenomena.

 
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