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

这项探索性研究的小额赠款将用于改进全球气候模型（GCM）的云参数化。这是气候研究界的首要任务之一。在创建云参数化，在广泛的区域，时间和气候制度的准确结果的困难是，潜在的动力学过程是在目前的GCM网格尺度未解决。此外，许多重要的物理过程，其中最重要的是辐射传输，是非线性相对于未解决的云的空间分布。一个有前途的解决这些问题的当前策略是明确预测这些子网格内的每个GCM网格单元的分布。然而，开发、测试和完善这种“统计云方案”还处于早期阶段。特别是，空间可变的云场对模式辐射传输的影响还没有得到很好的量化。辐射的后果，使用更现实的表示云水的空间变化，将产生的统计云计划和潜在的收益和权衡这样一个战略是主要的悬而未决的问题。更一般地说，通过非均匀云场的辐射传输问题需要更多的工作，这个问题对理解大气和气候系统过程具有重要意义。这项研究的部分动机来自于有机会将联合收割机这两种用于调查云变率和辐射传输的强大工具结合起来，并将这种结合应用于上面讨论的科学问题。这些工具是：（i）最先进的高分辨率三维数值大气模式;（ii）最先进的随机辐射传输模式，可以准确地表示通过高度可变的云场的短波通量。该项目有三个主要目标：1。对于许多案例研究，与更理想化或更均匀（“GCM样”）分布相比，量化大气模型的现实高分辨率云分布对随机辐射传输模型预测的短波通量的影响;2.将这种影响的差异与天气制度，大气动力过程和云类型的差异联系起来;3。开始开发和测试一个有价值的工具，我们希望它在云参数化开发和对通过多云大气的辐射传输问题的基础研究方面有重要的应用：也就是说，从高分辨率，3-三维大气数值模式与先进的辐射传输模式，能够准确地捕捉云的空间异质性的影响。更广泛的影响，气候研究和模拟界将对小尺度云变率对GCM尺度辐射通量的影响，何时何地可能需要或希望表示这种变率，以及这种影响对云场和云产生动力学和热力学的基本分辨率的依赖性提供有用的见解。因此，这项工作直接涉及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.