Motivation

1. Effects of cloud variability representation on mean microphysical process rates and radiative fluxes  We use four distribution functions, i.e., the truncated Gaussian, Gamma, lognormal, and Weibull, to represent cloud subgrid variability and examine the resultant mean bias in calculated grid-average process rates and radiative fluxes. The truncated Gaussian representation results in up to 30% mean bias in autoconversion rate whereas the mean bias for the lognormal representation is about 10%. The Gamma and Weibull distribution function performs the best for the grid-average autoconversion rate with the mean relative bias less than 5%. For radiative fluxes, the lognormal and truncated Gaussian representations perform better than the Gamma and Weibull representations. The results show that the optimal choice of subgrid cloud distribution function depends on the nonlinearity of the process of interest and thus there is no single distribution function that works best for all parameterizations. Reference: Statistical characteristics of cloud variability, Part II: implication for cloud microphysical and radiative transfer processes. J. Geophys. Res. Accepted. Contact: Dorothy Koch, SC23.1, 301-903-0105

2. Effects of cloud variability representation on microphysical process rates and radiative fluxes  • Motivation • Which probability density function (PDF) distribution is the most appropriate to represent cloud subgrid variaiblity? • Approach • We use the truncated Gaussian, Gamma, lognormal, and Weibull distributions to represent cloud subgrid variability. The PDFs are then used to upscale relevant physical processes to obtain grid-average process rates and compare their differences. • Result • The optimal choice of PDF function depends on the nonlinearity of the process of interest and thus there is no single distribution function that works best for all parameterizations. The dependence of mean relative bias in grid-average autoconversion rate on averaging window size using the five representations of subgrid cloud variability. The data from the ARM Tropical Western Pacific site during 2002-2010 are used. Statistical characteristics of cloud variability, Part II: implication for cloud microphysical and radiative transfer processes. J. Geophys. Res. (in press).