SciDAC Institute Investigators:
Bert J. Debusschere, QUEST Institute – Sandia National Laboratory
Leonard Oliker, SUPER Institute – Lawrence Berkeley National Laboratory
Samuel W. Williams, SUPER Institute – Lawrence Berkeley National Laboratory
Carol S. Woodward, FASTMath Institute – Lawrence Livermore National Laboratory
Science Team Leads:
Steven J. Ghan, Atmosphere Modeling – Pacific Northwest National Laboratory
Todd J. Ringler, Ocean Modeling – Los Alamos National Laboratory
Donald D. Lucas, Multiscale UQ – Lawrence Livermore National Laboratory
Carol S. Woodward, Computational Science – Lawrence Livermore National Laboratory
Some of the greatest challenges in projecting the future of Earth's climate result from the significant and complex interactions among small-scale features and large-scale structures of the ocean and atmosphere. In order to advanced Earth-system science, a new generation of models that capture the structure and evolution of the climate system across a broad range of spatial and temporal scales are required.
The MULTISCALE project’s 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. An integrated team of climate and computational scientists will accelerate the development and integration of multiscale atmospheric and oceanic parameterizations into the DOE-NSF Community Earth System Model (CESM). The team’s technical objective is to introduce accurate and computationally efficient treatments of interactive clouds, convection, and eddies into the next generation of CESM at resolutions approaching the characteristic scales of these structures. The project delivers treatments of these processes and constituents, which are scientifically useful over resolutions ranging from 2 to 1/16 degrees.
The MULTISCALE team will develop, validate, and apply multiscale models of the climate system based upon atmospheric and oceanic components with variable resolution. The project will exploit new variable-resolution unstructured grids based on finite-element and finite-volume formulations developed by team members. Effective deployment of these dynamical cores will require significant and concurrent advances in time-stepping methods, grid generation, and automated optimization methods for next-generation computer architectures.
This project supports the goal of DOE's Office of Biological and Environmental Research (BER) to produce “improved scientific data and models about the potential response of the Earth's climate and terrestrial biosphere to increased greenhouse gas levels for policy makers to determine safe levels of greenhouse gases in the atmosphere.” The team's objectives are also aligned with the mission of DOE's Advanced Scientific Computing Research Office to “discover, develop, and deploy the computational and networking tools that enable researchers in the scientific disciplines to analyze, model, simulate, and predict complex phenomena important to the DOE."