Jointly Funded SciDAC Awards Announced

Sea-ice floes collide in the Southern Ocean near the Mertz Glacier in August 1999. The Research Vessel Aurora Australis (inside the magenta box, which is approximately 100 meters wide) sits in the floe. Sea-ice modeling is the focus of one of the six funded projects.
Sea-ice floes collide in the Southern Ocean near the Mertz Glacier in August 1999. The Research Vessel Aurora Australis (inside the magenta box, which is approximately 100 meters wide) sits in the floe. Sea-ice modeling is the focus of one of the six funded projects.

Six projects beginning in 2017 have been awarded under the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC) program, which is jointly supported by the Office of Biological and Environmental Research (BER) and Advanced Scientific Computing Research (ASCR). Each of these SciDAC projects involve teams of earth system, computational, and mathematical scientists and is developing next-generation methods for earth system modeling. The funded projects are:

Probabilistic sea-level projections from ice sheet and earth system models” is developing advanced, variable-resolution ice sheet models, dynamically coupling them to ocean and Earth system models, and establishing frameworks for tracing uncertainties in ice sheet and earth system processes to uncertainties in sea-level projections.

 “A new discrete element sea-ice model for earth system modeling” is developing a new approach for sea-ice modeling with discrete elements that will be appropriate for very high resolution models where current continuum-approach assumptions are no longer valid. An important aspect will be making the approach scale well on modern computer systems.

Non-hydrostatic dynamics with multi-moment characteristic discontinuous Galerkin (NH-MMCDG) methods” is developing a next-generation, non-hydrostatic dynamical core based on an algorithm expected to scale well on heterogeneous architectures, such as at the Oak Ridge Leadership Class Facility.

Assessing and improving the numerical solution of atmospheric physics in E3SM” is developing systematic methods to assess and improve the convergence and coupling of the equations that represent atmospheric physical processes, such as those in clouds.

Optimization of sensor networks for improving climate model predictions” is developing an uncertainty quantification approach for the Energy Exascale Earth System Model (E3SM) model that will identify the biggest uncertainties in the land system that are important for land-atmosphere interactions, and will determine the optimal location for new measurements to reduce those uncertainties.

"Coupling approaches for next-generation architectures (CANGA)" is improving several different aspects of the earth system model component coupling to improve the coupling effectiveness, permit time-dependence of component boundaries, and to improve computational performance for the overall coupled system by introducing parallelism based on tasks rather than just on spatial distribution.

These projects will contribute to the advancement of DOE’s E3SM and further its progress toward design of earth system codes for leadership class computers and in support of energy science and mission requirements.