Collaborative Research: PetaApps: Enabling Multiscale Modeling of Turbulent Clouds on Petascale Computers

该奖项是根据2009年《美国复苏和再投资法案》(公法111-5)提供资金的。在地方到全球范围内进行可靠的天气和气候预报，最终取决于对支配单个云滴相互作用及其与云层尺度动态相互作用的微物理过程的充分和定量的准确理解。在那些已知的影响云中单个液滴的生长和云滴群体演化的机制中，湍流引起的碰撞-合并似乎是最复杂的机制之一。以往能够分解单个液滴的直接数值模拟方法传统上仅限于考虑极小的体积(约1立方米)，以及限于相对层流(非湍流)流动。因此，这些方法不能处理通常尺寸为10-100米的湍流涡旋对云滴尺度过程的影响，如凝结、合并和混合。即使是非常高分辨率的大涡模拟(LES)模式，最近才实现常规上接近10m的网格间距，也必须通过简化(和固有的有限)参数化技术来近似云微物理。因此，即使是一朵小云组成的数百万到数十亿个单独的液滴，也不能通过这些传统方法单独表示和跟踪。这个研究团队应用先进的千万亿级计算方法，将允许以无缝的方式处理湍流到云尺度(即多尺度)的云动力学和微物理，而不需要不合理的简化假设。这一方法将使人们对诸如副热带平流层积云和信风积云等浅层无冰对流云有更深入的了解，因为众所周知，这些云在全球气候系统中发挥着关键作用。在这项工作下开发的计算机代码将设计为易于移植，确保它们可在相关研究社区广泛使用。广泛影响：这种合作努力将使先进的工程流体力学研究工具和最先进的千万亿级计算方法有效地融合在一个统一的数值模拟框架内，并应用于关键的大气过程。这种方法将解决云物理研究界多年来面临的几个悬而未决的问题，并最终将有助于改进天气和气候预报。将通过多名研究生和本科生以及一名博士后学者的合作参与，加强多学科教育。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Reliable weather and climate prediction at local-to-global scales ultimately depends on a full and quantitatively accurate understanding of microphysical processes governing interactions of individual cloud droplets and their interplay with cloud-scale dynamics. Of those mechanisms known to affect the growth of individual droplets and evolution of cloud droplet populations within clouds, turbulence induced collision-coalescence appears to be among the most complex. Previous direct numerical simulation methods capable of resolving individual droplets have traditionally been confined to consideration of exceedingly small volumes (of order a cubic meter), as well as being restricted to relatively laminar (non-turbulent) flows. These methods have thus been incapable of addressing the impact of turbulent eddies, which typically have dimensions of 10-100 m, on cloud droplet-scale processes such as condensation, coalescence and mixing. Even very high resolution "Large Eddy Simulation (LES)" models, which have only recently achieved grid spacings routinely approaching 10 m, must approximate cloud microphysics via simplifying (and inherently limited) parameterization techniques. As such, the millions to billions of individual droplets comprised by even a small cloud cannot be individually represented and tracked via these traditional approaches.Application of advanced petascale computing methods by this investigative team will allow turbulence-to-cloud-scale (i.e. multiscale) cloud dynamics and microphysics to be treated in a seamless fashion absent unjustified simplifying assumptions. This approach will lead to a more robust understanding of shallow ice-free convective clouds, such as subtropical stratocumulus and trade-wind cumulus, which are known to play a critical role in the global climate system. Computer codes developed under this effort will be designed for ease of portability, ensuring their availability for broad use throughout the relevant research community.Broader Impact: This collaborative effort will allow advanced engineering fluid-mechanics research tools and state-of-the-art petascale computational methods to be effectively merged and applied to critical atmospheric processes within a unified numerical simulation framework. This approach will address several open questions that have faced the cloud-physics research community for many years, and will ultimately contribute to improved weather and climate forecasts. Multidisciplinary education will be enhanced through collaborative involvement of multiple graduate and undergraduate students, as well as a Postdoctoral scholar.