Heavy Rainfall Ensemble Prediction: Initial Condition Perturbation vs Multi-Physics Perturbation

Mesoscale ensemble is an encouraging technology for improving the accuracy of heavy rainfall predictions.Occurrences of heavy rainfall are closely related to convective instability and topography. In mid-latitudes,perturbed initial elds for medium-range weather forecasts are often con gured to focus on the baroclinic instability rather than the convective instability. Thus, alternative approaches to generate initial perturba-tions need to be developed to accommodate the uncertainty of the convective instability. In this paper, an initial condition perturbation approach to mesoscale heavy rainfall ensemble prediction, named as Di erent Physics Mode Method (DPMM), is presented in detail. Based on the PSU/NCAR mesoscale model MM5,an ensemble prediction experiment on a typical heavy rainfall event in South China is carried out by using the DPMM, and the structure of the initial condition perturbation is analyzed. Further, the DPMM ensem-ble prediction is compared with a multi-physics ensemble prediction, and the results show that the initial perturbation elds from the DPMM have a reasonable mesoscale circulation structure and could re ect the prediction uncertainty in the sensitive regions of convective instability. An evaluation of the DPMM ini-tial condition perturbation indicates that the DPMM method produces better ensemble members than the multi-physics perturbation method, and can signi cantly improve the precipitation forecast than the control non-ensemble run.