The importance of particle size distribution shape for triple-frequency radar retrievals of the morphology of snow.

The accurate representation of ice particles is essential for both remotely-sensed estimates of cloud and precipitation and numerical models of the atmosphere. As it is typical in radar retrievals to assume that all snow is composed of unrimed aggregate snowflakes, both denser rimed snow and the mixed-phase cloud in which riming occurs may be under-diagnosed in retrievals, and therefore difficult to evaluate in weather and climate models. Recent experimental and numerical studies have yielded methods for using triple-frequency radar measurements to distinguish fractal aggregate snowflakes from more dense and homogeneous rimed particles. In this study we investigate which parameters of the particle size distribution (PSD) and morphology of ice particles are most important to the triple-frequency radar signature of snow, in order to carry out an optimal estimation retrieval using triple-frequency Doppler radar observations. We represent a range of ice particle morphologies using a fractal model for aggregate snowflakes and homogeneous spheroids to represent rimed graupel-like particles, and modulate the prefactor and exponent of the particles' mass-size relations with a density factor. We find that for both fractal particles and homogeneous spheroids the PSD shape has a greater influence on the triple-frequency radar signature than the density factor, and show that the PSD shape must be allowed to vary to adequately constrain a triple-frequency radar retrieval of snow. We then demonstrate a novel triple-frequency Doppler radar retrieval of three parameters of the PSD as well as particle density, and show that the estimated snow rate, PSD and bulk density compare well against in situ observations at the surface. In a case study of compact rimed snow, we find that triple-frequency radar measurements provide a strong constraint on the estimation of PSD shape, but a relatively weak constraint on particle density, which we find can be more directly estimated from the Doppler velocity due to the relation between particle density and fallspeed. Including variations in PSD shape as well as particle morphology allows for a better representation of the triple-frequency radar signatures of rimed and unrimed snow, and suggests the potential for making new insights into the interaction between particles during aggregation and riming mechanisms. However, we find that improved representation of the PSD shape has a limited impact on improved estimates of snow rate from radar. The importance of the PSD shape to triple-frequency radar retrievals of snow suggests that further work is needed to account for variations in PSD shape before triple-frequency radar measurements can be used to better constrain particle morphology. [ABSTRACT FROM AUTHOR]