Construction of multiscale initial perturbations and the associated impacts on convection-permitting ensemble forecasting

To avoid selection of filtered scales in multiscale initial perturbations and to evaluate the roles of multiscale initial perturbations on the China Meteorological Administration-convection-permitting ensemble prediction system (CMA-CPEPS), we proposed a new scale-blending technique and then constructed a blended initial perturbation scheme (BLEND) based on the ensemble transform Kalman filter (ETKF) and dynamical downscaling (DOWN) schemes. First, the results revealed that the BLEND scheme can increase the small-scale (largescale) perturbations of the DOWN (ETKF) scheme, with the multiscale characteristics. Second, for dynamical variables, the BLEND scheme can improve the under-dispersion of the ETKF scheme at all forecast hours, and also improve the over-dispersion of the DOWN scheme at the initial lead time. Additionally, the probabilistic forecasting skill of the BLEND scheme is similar to that of the DOWN and ETKF schemes. Third, for precipitation, the BLEND scheme can increase the ensemble spread and reduce the forecast error of the ETKF scheme at all forecast hours, and at 15-21 and 30-36 h, respectively. And the BLEND scheme can reduce the forecast error of the DOWN scheme for most forecast hours and neighborhood radii. Furthermore, the BLEND scheme can completely improve the Brier scores of the ETKF scheme, and improve those of the DOWN scheme for large neighborhood radii and the final 6-12 h. Therefore, it is desirable to construct multiscale initial perturbations in CPEPSs.

Automated summary

In this study, a new scale-blending technique was proposed to evaluate the impact of multiscale initial perturbations on the CMA-CPEPS. The results showed that the blended scheme improved the dispersion of dynamical variables and increased the ensemble spread of precipitation, leading to reduced forecast error.