Direct assimilation of dual-polarization radar data in the idealized setup

The accuracy of numerical weather prediction models is highly dependent on the precision of the initial conditions, especially for forecasting storms and convective-scale weather events. Radars, with their ability to capture the internal structure and important microphysical and dynamical processes within convective systems, play a crucial role in improving weather forecasts at convective scales. Unlike conventional single-polarization radar, dual-polarization radar additionally provides information on the types and sizes of hydrometeor particles. As a result, polarimetric radar data (PRD) is a valuable data source for data assimilation (DA). Despite its potential, PRD is not yet directly assimilated into operational convection-permitting numerical models. This limitation arises from several challenges, including the highly non-linear nature of observation operators for polarimetric variables and the difficulty of estimating model error at convective scales, which require further research.

Our study primarily aims to directly assimilate PRD within an idealized setup. To accomplish this, Observation System Simulation Experiments (OSSEs) were conducted to simulate the evolution of a long-lived supercell using the ICOsahedral Nonhydrostatic (ICON) model with a two-moment microphysics scheme. For the assimilation of PRD data, the Kilometer-scale Ensemble Data Assimilation (KENDA) system was utilized, which incorporates the Local Ensemble Transform Kalman Filter (LETKF), along with the polarimetric radar forward operator EMVORADO-POL developed at the Deutscher Wetterdienst (DWD). In the current idealized setup, two types of DA experiments were conducted: a reference experiment that assimilated only non-polarimetric variables, such as reflectivity and radial velocity, and an experiment that assimilated differential reflectivity (ZDR) in addition to the non-polarimetric variables. The results from both experiments were compared, and appropriate thresholds and equivalents of noreflectivity data for polarimetric data were examined. Additionally, the sensitivity to DA settings, such as localization radius and the number of ensemble members, was also tested.