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The computational challenges of Earth-system science.
Alan O'Neill1, Lois Steenman-Clark
1Centre for Global Atmospheric Modelling, Department of Meteorology, University of Reading, Whiteknights, Reading RG6 6BB, UK.
Summary
Understanding Earth system evolution is a grand scientific challenge. Advanced computing and data are key to modeling its complexity for societal benefit.
Area of Science:
- Earth System Science
- Climate Science
- Environmental Modeling
Background:
- The Earth system, encompassing atmosphere, ocean, land, cryosphere, and biosphere, is highly complex.
- Predicting Earth system evolution is a major scientific challenge with significant societal implications.
Purpose of the Study:
- To outline key scientific and technical challenges in Earth system modeling.
- To emphasize the role of high-performance computing in advancing Earth system science.
Main Methods:
- Utilizing high-performance computing to link Earth system components.
- Integrating vast observational data into Earth system models.
Main Results:
- Identified four primary challenges: complexity, spatial resolution, uncertainty, and time-scales.
- Demonstrated the revolutionizing impact of computing and data on Earth system simulation.
Conclusions:
- Overcoming modeling challenges necessitates increased high-performance computing power.
- Investing in Earth system prediction capabilities offers substantial societal returns.