Prediction of extreme convective rainfall intensities using a free-running 3-D sub-km-scale cloud model initialized from WRF km-scale NWP forecasts

Abstract Most of the heavy rainfall comes from the severe convective storms. Convective scale numerical weather prediction with grid-lengths of a few km or less, is capable for a more successful representation of convective scale processes and explicitly representing different types of convective storms. However, despite these high-non-hydrostatic models, in some specific atmospheric cases associated with very intense convection, the present mesoscale models show some uncertainties and limitations in more accurate quantitative estimation of the intensity of heavy convective rainfall. In a way to overcome this problem we propose a novel forecasting system, that employs three-dimensional (3-D) cloud resolving model at Large Eddy Simulations (LES) type with greatly refined resolution of 100-m over a small sub-domain with the initial representative averaged vertical profiles derived from WRF-NMM 1-km forecasts. LES model is configured to explicitly simulate small-scale, high-intensity convective rainfall at that time and location where convective criteria and threshold values defined in the system interface are previously met. The cloud-model then evolves independently, with open lateral boundary conditions. A set of numerical experiments have been conducted and the method has been extensively tested on both tropical and mid-latitude convective cases. Results show some potential benefits in simulation of convective elements, cell structure and intensity. In this preliminary study, we show that the proposed method gives quantitatively more accurate forecast of high-intensity convective precipitation in most of the eight case-studies presented, when compared to the WRF-NMM 1-km scale forecasts. The improved skill of the forecasts using this forecast system will probably provide useful value to forecasters, so that they would be able to enhance their operational flood prediction capabilities and warnings of severe convective weather risk.