Study on the influence of model topography perturbation on prediction skill in a convection-allowing scale ensemble prediction system - Lianglü CHEN; Zheng WU; Song GAO (暴雨灾害, 2019)
Based on the convection-allowing scale high resolution (3 km) ensemble prediction system which has been operationally implemented in meteorological services of Chongqing and includes initial perturbation, model physical process perturbation and lateral boundary perturbation in it, the perturbation to model static topographic height field is realized by adopting different topographic interpolation schemes and smoothing schemes to generate static topographic height field of each ensemble members to express the uncertainty of the topographic conversions in the numerical model to some extent. Using these perturbations, we have performed a month consecutive ensemble prediction tests and the comparative analysis with respect to the ensemble forecast results without model topography perturbation. The results show that (1) after adding the model topography perturbation scheme into the ensemble prediction system, the topographic height spread among ensemble members has a good correspondence with the real topographic height gradient, and both spatial distribution characteristics are very similar. The topographic height spread in the plain area is small, while that in the plateau area or mountainous area with complicated terrain is large. (2) The addition of model topography perturbation scheme increases the ensemble different total energy (DTE) whose increase ratio in the low-level is larger than that in the mid- and upper-level. The enhancement of DTE in the short forecast lead time (12 h) is the most significant. It gradually decreased with the forecast lead time becoming longer. Large enhancement centers of DTE mainly appear in the areas with complicated topography and the great topographic height spread among the ensemble members. (3) In general, the addition of model topography perturbation scheme can improve the probability forecast skill and ensemble mean forecast skill of 24 h accumulated rain to some extent. It can optimize the ensemble distribution of all the elements in upper air, and 2 m air temperature, 10 m zonal wind, 10 m meridional wind and other elements near the ground level to a certain extent without the negative effect in the ensemble mean forecast error and ensemble spread.