Data for: Effect of the Rainwater Shape Parameter in Microphysical Schemes on Radar Reflectivity Assimilation Using the Ensemble Kalman Filter

This dataset supports the study titled "Effect of the Rainwater Shape Parameter of Microphysics in a Reflectivity Operator for Direct Assimilation of Radar Reflectivity using Ensemble Kalman Filter". It includes the essential observational data, evaluation metrics, and analysis scripts required to reproduce the key results presented in the manuscript. The archive contains the following components: met_out_r3.tar.gzVerification results generated by the Model Evaluation Tools (MET) point_stat utility, comparing forecasts against surface precipitation observations. rad_dbz_wind_bufr.tar.gzRadar reflectivity (dBZ) and radial velocity observations in BUFR format, used as input for direct assimilation in the EnKF experiments. UPP_OUT_GRIB1.tar.gzSelected model forecast outputs (precipitation-related fields only) in GRIB1 format, post-processed via the Unified Post Processor (UPP), corresponding to different rainwater shape parameter configurations. radar_obs.tar.gzRaw radar volume scans for the case study period (28–29 June 2023), used for cross-section visualization and assimilation validation. regrid_rain1h.tar.gzHourly surface precipitation observations interpolated onto the model grid, serving as a reference for spatial verification. fig_plt.tar.gzPlotting scripts (e.g., Python/NCL) used to generate figures in the paper, along with supplementary radiosonde (sounding) profiles from selected stations. cycle_wrfout_ncks.tar.gzSelected model state variables extracted from full wrfout files using the NCO tool ncks. Includes only the fields and time steps needed for visualization (e.g., wind, temperature, hydrometeor mixing ratios), significantly reducing file size while preserving analysis utility. single_analysis.tar.gzAnalysis fields from the single-analysis (deterministic) experiment under the same background conditions as the ensemble runs. Provides a baseline for comparing ensemble-based assimilation results. ⚠️ Important Note:The full model output (e.g., complete 3D/4D fields, all ensemble members, or entire simulation time series) is not included due to its large volume. However, all observational datasets necessary to reproduce the assimilation experiments and forecast evaluations reported in the paper are provided. With the described experimental setup (microphysics scheme, reflectivity operator, EnKF configuration), users should be able to replicate the core findings using this data. Researchers requiring access to additional model output or raw ensemble members may contact the corresponding author directly([e-mail]).