Abstract
Radiative transfer through clouds can be impacted by variations in particle number size distribution, but also in particle spatial distribution. Due to turbulent mixing and inertial effects, spatial correlations often exist, even on scales reaching the cloud droplet separation distance. The resulting clusters and voids within the droplet field can lead to deviations from exponential extinction. Prior work has numerically investigated these departures from exponential attenuation in absorptive and scattering media; this work takes a step towards determining the feasibility of detecting departures from exponential behavior due to spatial correlation in turbulent clouds generated in a laboratory setting. Large Eddy Simulation (LES) is used to mimic turbulent mixing clouds generated in a laboratory convection cloud chamber. Light propagation through the resulting polydisperse and spatially correlated particle fields is explored via Monte Carlo ray tracing simulations. The key finding is that both mean radiative flux and standard deviation about the mean differ when correlations exist, suggesting that an experiment using a laboratory convection cloud chamber could be designed to investigate non-exponential behavior. Total forward flux is largely unchanged (due to scattering being highly forward-dominant for the size parameters considered), allowing it to be used for conditional sampling based on optical thickness. Direct and diffuse forward flux means are modified by approximately one standard deviation. Standard deviations of diffuse forward and backward fluxes are strongly enhanced, suggesting that fluctuations in the scattered light are a more sensitive metric to consider. The results also suggest the possibility that measurements of radiative transfer could be used to infer the strength and scales of correlations in a turbulent cloud, indicating entrainment and mixing effects.
Highlights
Radiative transfer is different in a cloud in which droplet positions are spatially correlated than in a homogeneous cloud with the same mean properties such as droplet size and number density
In Packard et al [12], the particle clustering was idealized in order to give clear results; the purpose of this paper is to take a step toward experimental verification by exploring computationally whether deviations from standard radiative transfer for a homogeneous medium can plausibly be detected in a laboratory-generated cloud containing more realistic spatial correlations in droplet position due to turbulent mixing
We address the problem of predicting radiative transfer through both homogeneous and inhomogeneous media using a Monte
Summary
Radiative transfer is different in a cloud in which droplet positions are spatially correlated than in a homogeneous cloud with the same mean properties such as droplet size and number density. How to quantitatively describe the changes in radiative transfer under conditions where the scale of the correlations is smaller than the mean free path and where the medium must be considered discrete rather than continuous, such as in atmospheric clouds, remains an open question [1,2,3]. This is due to the presence of voids and clusters, where photons propagate further in dilute regions and experience stronger extinction in more dense regions [4]. In Packard et al [12], the particle clustering was idealized in order to give clear results; the purpose of this paper is to take a step toward experimental verification by exploring computationally whether deviations from standard radiative transfer for a homogeneous medium can plausibly be detected in a laboratory-generated cloud containing more realistic spatial correlations in droplet position due to turbulent mixing
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