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## PhD Seminar - Ryan Honeyager

*Seminar*

#### Event Details

Title: THE IMPACT OF MICROSTRUCTURE ON AN ACCURATE SNOW SCATTERING PARAMETERIZATION AT MICROWAVE WAVELENGTHS. Abstract: High frequency microwave instruments are increasingly used to remotely observe ice clouds and snow. These instruments are signiﬁcantly more sensitive than conventional precipitation radar. This makes them ideal for analyzing ice-bearing clouds, as ice particles are tenuously distributed and have eﬀective densities that are far less than liquid water. However, at shorter wavelengths, the electromagnetic response of ice particles is no longer solely dependent on particle mass. The shape of the ice particles also plays a signiﬁcant role. Thus, in order to understand the observations of high frequency microwave radars and radiometers, it is essential to correctly model the scattering properties of snowﬂakes.Several research groups have proposed detailed models of snow aggregation. Their algorithms simulate snowﬂakes that, ideally, match distributional parameters observed in nature, such as the size – density relation, aspects ratios and fractal dimensions of a series of observations. These particle models are then coupled with computer codes that determine the particles’ electromagnetic properties. However, there is a discrepancy between the particle model outputs and the requirements of the electromagnetic models. Snowﬂakes have countless variations in structure, but we also know that physically similar snowﬂakes scatter light in much the same manner. Then, we ask the question, what features are most important in determining scattering?Ice particles have been frequently modeled using structurally exact electromagnetic models, such as the discrete dipole approximation, which require a very high degree of structural resolution. Such methods are slow; rather, they spend a considerable amount of time processing redundant (i.e. useless) information. Conversely, inexact methods have also been attempted. An example of this is the approximation that all ice particles are merely low-density spheres. While it is easy to determine radiative eﬀects of low-density spheres, these models incorporate too little information, and their resultant radiative properties are not physically realistic. After all, snow particles are not spheres.This leads to considerable uncertainty in interpreting the remote ice signal. What is needed is the development of a general technique that can quickly parameterize the important structural aspects that determine the scattering of many diverse snowﬂake morphologies. Several parts of this development are presented here. A Voronoi bounding neighbor algorithm is ﬁrst employed to decompose aggregates into well-deﬁned interior and surface regions. This is used to test the sensitivity of scattering to interior perturbation, which represents a loss of interior information scenario. The interior structure is replaced with a homogeneous foam0like medium. The loss of interior structure is found to have a negligible impact on the single scattering cross section, and backscatter is lowered by only around ﬁve percent. This establishes that detailed knowledge of interior structure is not necessary when modeling scattering behavior. This also provides support for using an eﬀective medium approximation to describe the interiors of snow aggregates, and it enables the almost trivial determination of the eﬀective density of this medium.This is then used to establish a greatly improved approximation of scattering by equivalent spheroids. The Voronoi eﬀective density approach is found to reasonably match backscatter over frequencies from 10.65 to 183.31 GHz and particle sizes from a few hundred micrometers to nine centimeters in length. Integrated error in backscatter versus DDA is found to be within 25% at 94 GHz. Error in scattering cross-sections and asymmetry parameters is likewise small. This represents a signiﬁcant improvement over established techniques.The present results can be used to supplement retrieval algorithms used by CloudSat, EarthCARE, Galileo, GPM and SWACR radars. The ability to predict the full range of scattering properties is potentially also useful for other particle regimes where a compact particle approximation is applicable.