Radiative Transfer Through Inhomogeneous Clouds: Stochastic Modeling Using Cloud Structure Observations

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Evans/Abstract The objective of this research is to increase the understanding of how cloud structure affects radiative properties and to improve methods of computing radiative transfer in inhomogeneous clouds for parameterizations an remote sensing. This research will focus on using stochastic radiative transfer, in which ensemble mean radiative properties are computed directly from probability distributions that describe cloud inhomogeneity. Stochastic modeling is appropriate because information about cloud structure is inherently statistical. Data from millimeterwave radars and cloud probes on aircraft will be used to characterize spatial structure in liquid water clouds, including within cloud variability, in terms of the stochastic transfer probability distributions. Radiative transfer modeling will be done to learn what aspects of cloud inhomogeneity are most important for the mean radiative effects and how these may be best expressed with a few simple parameters. The modeled radiances and fluxes will be compared with aircraft and ground based radiometers. An approximate method of using these inhomogeneous cloud parameters for rapidly computing stochastic radiative transfer for use in cloud radiation parameterizations will be sought. Deterministic radiative transfer modeling will also be done to investigate relationships between the statistics of upwelling radiances and the underlying inhomogeneity for use in remote sensing of clouds.