SGER: Stochastic Radiative Transfer Through Inhomogeneous Cloud Fields Produced by a 3-D, High-Resolution Numerical Atmospheric Model

这项探索性研究小额赠款将用于开发改进的全球气候模式（GCMs）的云参数化。这是气候研究界的首要任务之一。创建云参数化以在大范围的地区、时间和气候条件下给出准确结果的困难在于，在当前的GCM网格尺度上，潜在的动力过程尚未解决。此外，许多重要的物理过程，其中辐射传输是最重要的，相对于未解决的云空间分布是非线性的。当前解决这些问题的一个很有前途的策略是明确地预测每个GCM网格单元内的这些子网格分布。然而，开发、测试和改进这样的“统计云方案”还处于早期阶段。特别是，空间变化的云场对模式辐射传输的影响尚未得到很好的量化。使用统计云方案产生的更真实的云水空间变异性表示的辐射后果以及这种战略的潜在收益和权衡是主要的未解问题。更一般地说，需要对通过非均匀云场的辐射传输问题进行更多的研究，这一问题对理解大气和气候系统过程具有重要意义。进行这项研究的部分动机来自于有机会将研究云变率和辐射传输的两种强大工具结合起来，并将这种结合应用于上述科学问题。这些工具是：(i)最先进的、高分辨率的三维数值大气模型；㈡能够准确表示通过高度可变云场的短波通量的最先进的随机辐射传输模型。本项目有三个主要目标：1。1 .在若干案例研究中，将大气模式实际的高分辨率云分布与更理想化或更均匀的（“类似gcm”）分布相比，对随机辐射传输模式预测的短波通量的影响进行量化；2 .将这种影响的差异与天气状况、大气动力过程和云类型的差异联系起来；开始开发和测试一种有价值的工具，我们期望它对云参数化发展和通过多云大气辐射传输问题的基础研究具有重要应用：即高分辨率，三维大气数值模型与能够准确捕获云空间异质性影响的先进辐射传输模型的耦合输出方法。对气候研究和模拟界的更广泛影响将是对以下方面的有用见解：较小尺度云变率对gcm尺度辐射通量的影响，这种变率的表示可能需要或可取的时间和地点，以及这种影响对云场的基本分辨率以及产云动力学和热力学的依赖性。因此，这项工作直接说明了美国气候变化科学计划的目标，这是一项总统倡议，旨在为环境和能源政策制定提供科学依据。

This Small Grant for Exploratory Research will address the development of improved cloud parameterizations for Global Climate Models (GCMs). This is one of the top priorities of the climate research community. The difficulty in creating cloud parameterizations that give accurate results across a wide range of regions, times, and climate regimes is that the underlying dynamical processes are unresolved at current GCM grid scales. In addition, many important physical processes, of which radiative transfer is among the most important, are nonlinear with respect to the unresolved cloud spatial distribution. One promising current strategy for addressing these issues is to explicitly predict these subgrid distributions inside each GCM grid cell. However, developing, testing, and refining such "statistical cloud schemes" are in their earliest stages. In particular, the impact of spatially variable cloud fields on model radiative transfer has not been well quantified. The radiative consequences of using the more realistic representations of cloud water spatial variability that would be produced by a statistical cloud scheme and the potential gains and tradeoffs of such a strategy are major unanswered questions. More generally, much additional work is needed on the problem of radiative transfer through an inhomogeneous cloud field, a problem that has important implications for understanding atmospheric and climate system processes. Part of the motivation for this study comes from the opportunity to combine two powerful tools for investigating cloud variability and radiative transfer and to apply the combination to the scientific issues discussed above. These tools are: (i) a state-of-the-art, high-resolution, 3-D numerical atmospheric model; (ii) a state-of-the-art stochastic radiative transfer model that can accurately represent shortwave fluxes through a highly variable cloud field. This project has three major objectives:1. To quantify, for a number of case studies, the impact of the atmospheric model's realistic, high- resolution cloud distributions, compared to more idealized or more homogeneous ("GCM-like") distributions, on the shortwave fluxes predicted by the stochastic radiative transfer model;2. To link differences in this impact to differences in synoptic regime, atmospheric dynamical processes, and cloud type;3. To begin developing and testing a valuable tool that we expect to have important applications for cloud parameterization development and fundamental research into the problem of radiative transfer through a cloudy atmosphere: namely, the methodology of coupling output from a high- resolution, 3-D atmospheric numerical model with an advanced radiative transfer model capable of accurately capturing the effects of cloud spatial heterogeneity.The broader impacts on the climate research and modeling communities will be the useful insights into the impact of smaller-scale cloud variability on GCM-scale radiative fluxes, when and where the representation of such variability might be needed or desirable, and the dependence of this impact on the underlying resolution of the cloud field and the cloud-producing dynamics and thermodynamics. As such, the work speaks directly to the goals of the U.S. Climate Change Science Program, a Presidential initiative focused on providing the scientific basis for environmental and energy policymaking.