Truncation Optimization for Global Prediction Models

9300976贝尔博士以前的研究结果表明，通过在垂直方向上适当地分布模式水平，可以提高大气预报模式的预报技巧。最初的研究是通过一个模型进行的，该模型从大气静止的基本状态开始。虽然这种近似使问题在数值上易于处理，但它并不是非常现实。根据这一奖项，PI将考虑一个模型，在该模型中，更现实的假设和探索关于纬度和高度的最佳栅格分布。这项研究的结果将导致天气和气候预测模型的数值表示更有效和准确，并消除显着的数值截断误差。***

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. ***