Center for Analysis and Prediction of Storms (CAPS)

这项来自俄克拉荷马州大学的建议， 与国家海洋和大气局合作 美国国家海洋和大气管理局（NOAA）要求资金建立一个科学和 风暴分析和预报技术中心。 的 该中心的主任将是道格拉斯K.莉莉 必须开发新一代模型来解决 风暴规模的预测问题，目前还没有关键的 在美国任何地方的大量科学家来执行这个任务 research. 该中心将填补这一空白，并将作为 其他对该领域感兴趣的研究人员的联络点。 补充性的建模工作正在国家实验室进行， 大气研究中心（NCAR）和其他大学， 但这些相关研究工作中使用的模型并不 为所需的多尺度任务提供适当的框架， 的中心。 该中心计划加强其工作 与NCAR和其他大学研究人员的关系， 特别是通过交换教职员工和学生。 初步研究将从三个方向进行： 可预测性研究和敏感性测试;以及 数据同化和初始化研究。 的范围 正在解决的问题跨越基础理论，实验， 操作测试。 这种模式的成功必然 需要使用先进的数值技术， 应用于大气建模;许多将迫使一个完整的 改变现有模式的框架。 此外该 同化/初始化问题将需要不同的 理论框架比迄今为止使用的。 最后通过 开发一种新的模式，可以迅速充分利用 不断发展的计算机体系结构，特别是大内存 高度并行的超级计算机。 这项研究结合了多学科的专业知识。 的 控制着许多现象的物理学，例如，云动力学和 表面能量平衡，必须进行调查和建模。 的 然后，必须将模式纳入一般的中尺度 预测能力，使用数值程序， 准确地模拟所涉及的流动。 与所述方法 设想，计算机被允许作为一个“专家系统”， 改变其数值算法及其空间和时间 分辨率，以响应字段中可观察到的变化。 所有 必须使用来自真实的数据的输入进行测试， 这些数据的初始化和同化是关键 的过程中，允许的预测能力， 模拟将根据测量值进行测试和评估 大气过程。

This proposal from the University of Oklahoma (OU) in collaboration with the National Oceanic and Atmospheric Administration (NOAA) requests funds to establish a Science and Technology Center for Analysis and Prediction of Storms. The Director of the Center will be Professor Douglas K. Lilly. A new generation of models must be developed to address the storm-scale prediction problem and there is currently no critical mass of scientists anywhere in the U.S. to carry out this research. The Center will fill this gap and will serve as a focal point for other researchers interested in this area. Complementary modelling work is being carried out at the National Center for Atmospheric Research (NCAR) and other universities, but the models used in these related research efforts do not provide adequate frameworks for the multi-scale tasks required in the OU Center. The Center plans to enhance their working relationships with NCAR and other university researchers, especially through exchange of faculty, staff, and students. The initial research will proceed in three directions: model development; predictability research and sensitivity testing; and data assimilation and initialization research. The scope of the problems being addressed spans basic theory, experimentation, and operational testing. The success of such models will necessarily require the use of advanced numerical techniques not previously applied to atmospheric modelling; many will force a complete change in the framework of existing models. In addition, the assimilation/initialization problem will require a different theoretical framework than has been heretofore used. Finally, by developing a new model, full advantage can be taken of rapidly evolving computer architectures, particularly the large memory and highly parallel supercomputers. The research couples the multidisciplinary expertise at OU. The governing physics of many phenomena, e.g., cloud dynamics and surface energy balance, must be investigated and modelled. The model must then be incorporated into a general mesoscale predictive capability, using numerical procedures which accurately simulate the flows involved. With the methods envisioned, the computer is allowed as an "expert system" to alter its numerical algorithm and its spatial and temporal resolution, in response to observable changes in the fields. All of these must be tested using the inputs from real data, and the initialization and assimilation of these data are the linchpins of the process, allowing the predictive capability of the simulation to be tested and evaluated against measured atmospheric processes.