Polarimetric Radar Simulation with Real Shaped Ice Crystals and Snowflakes for ICON's Radar Forward Operator EMVORADO

Radar Forward Operators (RFO) are an essential link between the physical properties of clouds and precipitation and the observed radar quantities. The assumptions regarding the scattering properties of frozen and mixed-phase hydrometeors are a significant source of uncertainty for RFO. Advanced Discrete Dipole Approximation (DDA) scattering modeling offers the opportunity to replace the traditional homogeneous spheroidal (T-matrix) scattering assumption in RFOs with properties derived from realistic ice crystals and snowflake shapes. However, it is well-known that snow particles appear in a vast variety of habits and it is not straightforward to assume one shape that fits it all. Conversely, operational weather models do not provide sufficient constraints to model ice particle shapes that unambiguously represent the generic internal ice microphysical assumptions (i.e., mostly just mass-size relation). The present study uses a cascade of progressively more detailed models that explicitly predict the shapes of ice crystals and snow aggregates to be used to model their radar multifrequency (C, X, Ka, and W-band) polarimetric signature with DDA.

The numerical weather model ICON is used to simulate the thermodynamic properties of the atmosphere and the large-scale cloud and precipitation fields. Some atmospheric profiles in the ICON solution are selected for further processing in correspondence with radar observation facilities. The core of the modeling framework is the shape-predicting, semi-lagrangian, cloud model McSnow that takes the ICON atmospheric state and simulates the evolution of the microphysical properties of cloud and precipitation particles such as mass, size, aspect ratio, rime fraction, melted fraction as well as the number of monomers composing snow aggregates. By tracking the sequence of aggregation events that originated each aggregate, it is possible to reconstruct the properties (size, mass, and aspect ratio) of each monomer. This information can be used to simulate realistic aggregate shapes using a physically based aggregation model. This model reproduces the collision process with great detail and provides snowflake shapes that match the properties of the snowflake as they are modeled by McSnow. There are multiple scientific questions that this study aims to address:

• How well the predicted properties of McSnow ice and snow particles compare with the strict assumptions of the ICON bulk 2-moment microphysical scheme, especially in terms of mass-size and velocity size relations? Is it possible to derive a parametrization of such properties to large scale atmospheric state?
• How much do the multifrequency and polarimetric radar properties of frozen hydrometeors depend on ice particle shapes?
• Is it possible to derive a snow particle model that can be used in most weather situations as prototype for polarimetric RFO simulations and what is the uncertainty associated with this assumption?