Collaborative Research: Type 1 -- LOI02170139: Direct Statistical Approaches to Large-Scale Dynamics, Low Cloud Dynamics, and their Interaction

需要进行变革性的研究，以实现气候模拟的定性改进。研究人员正在开展一个跨学科的项目，将直接统计方法用于气候建模，这有可能极大地提高我们对不同气候过程在短时间尺度和长时间尺度、小空间尺度和大空间尺度上如何相互作用的理解。该计划为一类新的气候模型奠定了基础，这些模型可能会补充甚至最终取代现有的气候模型。它有两条平行的轨道。首先，研究人员正在开发直接计算气候统计数据的方法，这种方法最终可能取代传统的数值模拟，从而产生计算效率更高的气候模型。其次，他们正在改进低云的表示，并改进对云与大尺度环流相互作用的理解，从而产生更准确的气候模式，并减少目前在其中云表示方面的巨大不确定性。直接计算气候统计量的方法是以累积展开为基础的，其中快模态被积分出来。这使人们的注意力重新集中在对主导气候变率的低频模态的评估和理解上。基于云和亚网格尺度动力学的概率闭包，改进了低云的表示，可以系统地提高精度。这些数据被整合到一个综合环流模型（GCM）中，该模型将云与大尺度气流耦合在一起，从而可以系统地研究它们之间的相互作用。这项工作将过去在相对简单的地球物理流模型中直接计算统计数据的工作扩展到日益复杂和现实的gcm，同时提高了统计方法和gcm本身的准确性。

Transformative research is needed to realize qualitative improvements in the modeling of climate. The investigators are carrying out an interdisciplinary program of direct statistical approaches to climate modeling that has the potential to dramatically improve our understanding of how different climate processes interact over short and long time scales and small and large spatial scales. The program lays the foundations for a new class of climate models that may complement or even eventually replace existing climate models. It has two parallel tracks. First, the investigators are developing methods for the direct computation of climate statistics that may eventually replace conventional numerical simulations, leading to computationally more efficient climate models. Second, they are developing improved representations of low clouds and an improved understanding of cloud interactions with large-scale circulations, leading to more accurate climate models and reducing the currently large uncertainties in the representation of clouds in them. The methods for the direct computation of climate statistics are based upon cumulant expansions in which fast modes are integrated out. This refocuses attention on the evaluation and understanding of low-frequency modes, which dominate climate variability. Improved representations of low clouds are developed based on probabilistic closures of cloud and subgrid-scale dynamics, which can be systematically improved in accuracy. These are integrated into a general circulation model (GCM) that couples the clouds to the large-scale flows, allowing a systematic study of their interactions. The work extends past work on the direct computation of statistics in relatively simple models of geophysical flows to GCMs of increasing complexity and realism, while improving the accuracy of the statistical methods and of the GCMs themselves.