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.
Highlights
Modern numerical weather prediction (NWP) models offer capabilities to simulate radar reflectivity from the output of NWP models, such as single-level radar reflectivity and composite reflectivity (CR)
How is simulated radar reflectivity determined from NWP outputs? the moist physical process, which is used to describe the mutual conversion between water vapor and various hydrometeors and the corresponding dynamic and thermal impacts in NWP models (Kuo and Reed 1988; Sheng et al 2003), plays a key role in the calculation of simulated radar reflectivity
Simulated radar reflectivity is computed from the forecast mixing ratios of grid-resolved hydrometeor species of a grid-scale cloud microphysics parameterization scheme, assuming Rayleigh scattering by spherical particles of known density and an exponential size distribution (Smith et al 1975)
Summary
Modern numerical weather prediction (NWP) models offer capabilities to simulate radar reflectivity from the output of NWP models, such as single-level radar reflectivity and composite reflectivity (CR) (the maximum reflectivity in a grid column). Based on the Kain–Fritsch (new Eta) scheme (Kain 2004), we try to design a new simulated radar reflectivity calculation method for subgrid-scale and grid-scale precipitation.
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