Ice Particle Size Distributions From Composites of Microphysics Observations Collected in Tropical Cyclones

Ice microphysics observations collected from eight flights into tropical cyclones (TCs) were analyzed to examine the performance of exponential versus gamma functions in representing the particle size distributions (PSDs) for cloud ice, snow, and graupel. Eighty-four percent (87%) of cloud ice (snow) PSDs are above the correlation threshold of 0.9 between observations and the corresponding fitted curves by gamma fits, while only 43% (55%) of cloud ice (snow) PSDs by exponential fits. Sixteen percent of graupel PSDs are above the threshold by gamma fits but none by exponential fits. The intercept, slope, and shape in gamma functions are mutually dependent. When one among the three parameters is prescribed, the other two can be empirically rendered from the mutual-dependence relationship. Counterintuitively, temperature does not play a conspicuous role in controlling ice PSDs in the TC environment but horizontal winds do, especially for snow, through the breakup process. Plain Language Summary A crucial component of numerical weather forecasts is to realistically represent how liquid and solid water particles form, grow, and dissipate. Accurate distributions of the sizes of these particles are needed. We analyzed observations of solid water particles from eight research flights into tropical cyclones to estimate these distributions in this study. Our results showed that gamma functions can represent these distributions more realistically than exponential functions. The intercept, slope, and shape in gamma functions are mutually dependent. This mutual dependence simplifies the application of the gamma functions to microphysical process modeling. Our results also showed for the first time that ice particle size distributions do not depend on temperature in the tropical cyclone environment. Instead, horizontal wind speeds play an important role in controlling the ice particle size distributions, especially for snow.