Truncation Optimization for Global Prediction Models

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9300976 Baer Dr. Baer's previous results indicate that improved forecast skill with atmospheric prediction models can be achieved with appropriate distribution of model levels in the vertical. The initial studies were done with a model beginning with a basic state with the atmosphere at rest. While this approximation makes the problem tractable numerically, it is not terribly realistic. Under this award, the PI will consider a model in which more realistic assumptions and explore optimum grid distributions with respect to latitude and height. The results of this research should lead to numerical representations for weather and climate prediction models which are more efficient and accurate and remove significant numerical truncation errors. ***