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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2008.4
- 수록면
- 26 - 31 (6page)
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초록· 키워드
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The architecture of Earth system models is informed by two considerations. One is the need to support a hierarchy ranging from idealized to comprehensive models: understanding the functioning of the Earth system involves constantly moving back and forth between simple and complex models. A second consideration is the tendency of model complexity to grow with time: some components of the physical climate system are initially considered external to the system being modeled, and with the growing maturity of both our physical understanding and the available computational power, these later become full-fledged model components. Modeling frameworks have emerged as a key methodology for supporting the architecture of Earth system models with multiple components. Simultaneously, the comparative analysis of output from multiple models, and against observational data analysis archives, has become a key methodology in reducing uncertainty in climate projections, and in improving forecast skill of medium- and long-term forecasts. There is considerable momentum toward simplifying such analyses by applying comprehensive community-standard metadata to observational and model output data archives. This has led to the development of data frameworks for simplifying the construction of multi-model data archives.
This paper traces the evolution of modeling and data frameworks, and emerging new methodologies enabled by these powerful technologies.
This paper traces the evolution of modeling and data frameworks, and emerging new methodologies enabled by these powerful technologies.
목차
Abstract
1. Introduction
2. Architecture of a Modeling Framework
3. Infrastructure
4. Superstructure
5. Runtime Environment
6. Discussion
Acknowledgments
References
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