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

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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.