Improved Representations of Ice Cloud Microphysics for Hurricane Models

Particle size distributions are commonly written as analytic functions, such as exponential or gamma functions, in mesoscale and cloud resolving models. Cloud parameterization schemes that predict one or two moments of the size distribution typically require additional assumptions about the shapes of the distributions which are obtained from in-situ observations. In this paper, a new incomplete gamma fitting (IGF) method for deriving the intercept (N0), slope (gamma) and shape (mu) of a gamma function from in-situ observations is described. Ten second averages of size distributions obtained using two-dimensional cloud and precipitation probes during the Convection and Moisture Experiment (CAMEX-4) and the NASA African Monsoon Multidisciplinary Analyses (NAMMA) are used with the IGF to determine the dependence of N0, gamma and mu on temperature, total water content, vertical velocity and stage of tropical cyclone (TC) evolution. Implications for the development of cloud microphysical parameterization schemes for mesoscale models are discussed.