SCIENCE TEAM III GRAND CHALLENGE INVESTIGATORS
Computational Technologies for Earth and Space Sciences (COMTESS)
A Grand Challenge is a fundamental problem in science and engineering, with broad scientific and economic impact, whose solution can be advanced by high-performance computing.
Using a Cooperative Agreement Notice, NASA selected 11 Grand Challenge Investigator teams to develop software frameworks that enable more realistic simulations of natural phenomena and interpretation of vast quantities of observational data on high-end computers. Read about the initial awards in a Goddard Space Flight Center news release. Prof. C. Roberto Mechoso, UCLA, is COMTESS Chair.
- The Earth System Modeling Framework
- Part I: Core Development
Timothy Killeen, National Center for Atmospheric Research
Expected outcome: Software infrastructure to enable the interoperability and reuse of Earth System Model components on high-end computing platforms across the Earth modeling community.
- The Earth System Modeling Framework
- Part II: Modeling Applications
John Marshall, Massachusetts Institute of Technology
Expected outcome: Integration of major U.S. climate and numerical weather prediction models into the Earth System Modeling Framework.
- The Earth System Modeling Framework
- Part III: Data Assimilation Applications
Arlindo da Silva, NASA/Goddard Space Flight Center
Expected outcome: Atmospheric and oceanic data assimilation systems integrated into the Earth System Modeling Framework.
- Numerical Simulations for Active Tectonic Processes
- Andrea Donnellan, NASA/Jet Propulsion Laboratory
Expected outcome: Multi-year Southern California earthquake forecast using realistic modeling of crustal fault interactions based on observational data.
- Land Information Systems
- Paul Houser, George Mason University, and Christa Peters-Lidard, NASA/Goddard Space Flight Center
Expected outcome: Enable near-real-time, observation-driven modeling of regional and global terrestrial water and energy cycles for coupled Earth System Models.
- Biotic Prediction: Building the Computational Technology Infrastructure for Public Health and Environmental Forecasting
- John L. Schnase, NASA/Goddard Space Flight Center
Expected outcome: High-performance, landscape-scale modeling of the changing geospatial distribution of the Earth's living components.
- Atmosphere/Ocean Dynamics and Tracers Chemistry
- C. Roberto Mechoso, UCLA
Expected outcome: Earth System Modeling Framework components for better understanding of the El Niño/Southern Oscillation.
- A High-Performance Adaptive Simulation Framework for Space Weather Modeling
- Tamas Gombosi, University of Michigan
Expected outcome: Real-time space weather prediction capability using coupled models driven by solar and interplanetary observations.
- A C++ Framework for Block-Structured Adaptive Mesh Refinement Models
- Phillip Colella, Lawrence Berkeley National Laboratory
Expected outcome: Computational technologies for multi-scale modeling of astrophysical and microgravity phenomenon.
- Interoperability Based Environment for Adaptive Meshes (IBEAM) with Applications to Radiation-Hydrodynamic Models of Gamma-Ray Bursts
- Paul Saylor, University of Illinois at Urbana-Champaign
Expected outcome: Understanding of observational data from gamma-ray bursts through development of a component-based parallel framework for astrophysical simulation.
- High-Performance Cornerstone Technologies for the National Virtual Observatory (NVO)
- Thomas Prince, California Institute of Technology
Expected outcome: Deploying an on-demand astronomical image mosaic service for the NVO.
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