A Simulated Radar Reflectivity Calculation Method in Numerical Weather Prediction Models

Abstract

AbstractThe simulated radar reflectivity used by current mesoscale numerical weather prediction models can reflect the grid precipitation but cannot reflect the subgrid precipitation generated by a cumulus parameterization scheme. To solve this problem, this study developed a new simulated radar reflectivity calculation method to obtain the new radar reflectivity corresponding to the subgrid-scale and grid-scale precipitation based on the mesoscale Global/Regional Assimilation and Prediction System (GRAPES) model of the China Meteorological Administration. Based on this new method, two 15-day forecast experiments were carried out for two different time periods (11–25 April 2019 and 1–15 August 2019), and the radar reflectivity products obtained by the new method and previous method were compared. The results show that the radar reflectivity obtained by the new simulated radar reflectivity calculation method gives a clear indication of the subgrid-scale precipitation in the model. Verification results show that the threat scores of the improved experiments are better than those of the control experiments in general and that the reliability of the simulated radar reflectivity for the indication of precipitation is improved. It is concluded that the new simulated radar reflectivity calculation method is effective and significantly improves the reflectivity products. This method has good prospects for providing more information about forecasting precipitation and convective activity in operational models.