Assimilation of Dual-Polarimetric Radar Observations with WRF 3DVAR and its Impact on Ice Microphysics

Studies have shown that radar data assimilation can help with short-term prediction of convective weather by providing more accurate initial condition. However, it remains a big challenge to accurately describe the moist convective processes, especially the ice microphysics of convection, which is crucial for the modeling of quantitative precipitation forecast (QPF). Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, information on the type, shape, size, and orientation of cloud and precipitation microphysical particles are obtained, more accurate measurement of liquid and solid cloud and precipitation particles can be provided. The assimilation of dual-pol radar data is however, challenging work as few guidelines have been provided on dual-pol radar data assimilation research. It is our goal to examine how to use dual-pol radar data to improve forecast initialization for microphysical properties. This presentation will demonstrate our recent work on developing the forward operators for ice processes with assimilating dual-pol radar data for real case storms. In this study, high-resolution Weather Research and Forecasting (WRF) model and its 3-Dimensional Variational (3DVAR) data assimilation system are used for real convective storms. Our recent research explores the use of the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms and snowfall events, with a significant focus on improving representation of ice hydrometeors. Our previous research indicated that the use of ZDR can bring additional benefit into the hydrometeor fields than the use of ZH only. Furthermore, the combination of KDP and ZDR data provide the best initialization for precipitation particles with warm-rain radar data assimilation. Our ongoing work includes the development of forward model for ice microphysics processes within the 3DVAR assimilation procedure. The ice processes can help to describe the ice particles more precisely at and above the melting layer. In addition to forward model development, high-resolution (≤1 km) WRF model simulations and convective scale data assimilation experiments with WRF 3DVAR system will be discussed, emphasizing both warm rain and ice microphysical processes. Further details of the methodology of data assimilation, the influences of different dual-pol variables, the impact of the dual-pol data on microphysical properties, and the information content of the dual-pol variables and observational operators will also be presented at the conference.