大气科学学报2026，Vol.49Issue(3)：472-486,15.DOI:10.13878/j.cnki.dqkxxb.20250312001
强弱强迫条件下对流尺度集合扰动增长特征及对降水预报性能的影响
Convective-scale ensemble perturbation growth and precipitation predicta-bility under strong and weak synoptic forcing conditions
摘要
Abstract
Characterizing the nonlinear growth of small-scale ensemble perturbations remains a major challenge in developing effective initial perturbation techniques for convective-scale ensemble prediction systems.Under-standing the general characteristics of ensemble perturbations,particularly under different synoptic forcing condi-tions,is essential for constructing more representative initial perturbations and improving forecast uncertainty quantification.Although previous studies have investigated ensemble perturbation growth,the differences between strong and weak synoptic forcing conditions remain insufficiently understood. In this study,two concurrent precipitation events over different regions of China are examined:one over northern China under strong synoptic forcing,and the other over southern China under weak synoptic forcing,characterized as a warm-sector heavy rainfall event.To minimize the influence of lateral boundary conditions and emphasize smaller-scale ensemble perturbations,two ensemble experiments were conducted using the China Mete-orological Administration Regional Ensemble Prediction System(CMA-REPS V4.0)over a domain spanning(70.0°—145.0°E and 10.0°—60.1°N).In the control experiment(CTRL),14 ensemble members were genera-ted by adding perturbations to both the initial conditions(ICs)and lateral boundary conditions(LBCs),which were downscaled from the CMA Global Ensemble Prediction System(CMA-GEPS;0.5°×0.5° resolution).The ICs and LBCs for the control member were downscaled from the National Centers for Environmental Prediction Global Forecast System(NCEP-GFS;0.5°×0.5° resolution).In a second experiment(CONS),the cosine analysis constraint method was applied to optimize the initial perturbations in CTRL,allowing assessment of their sensitivity and influence on precipitation predictability under different synoptic forcing regimes. The results show that meso-β scale ensemble perturbations exhibit more pronounced evolution,with faster nonlinear growth under strong forcing than weak forcing.In the CONS experiment,the growth of smaller-scale perturbations is enhanced under both forcing conditions.This indicates that incorporating more small-scale pertur-bations improves the ability of CMA-REPS V4.0 to represent forecast uncertainty,leading to better agreement with observed precipitation tendencies and improved forecast performance for heavy rainfall events.Region-aver-aged results confirm that precipitation under weak forcing has lower predictability than that under strong forcing.Correspondingly,forecast performance improvements are more evident in strong-forcing conditions.Compared with CTRL,the CONS experiment exhibits greater ensemble spread and a stronger ability to capture precipitation uncertainty under both forcing regimes,with some members successfully reproducing observed variability. However,the lower predictability of weak-forcing precipitation suggests that limitations in simulating heavy rainfall cannot be attributed solely to initial perturbation design.The overestimation of precipitation in both events,particularly during the early stage of the weak-forcing case,highlights the important role of physical parameteriza-tion schemes.Therefore,improving forecast skill requires not only optimized initial perturbations but also the se-lection and development of appropriate microphysics and cumulus parameterization schemes to better represent moist convection processes.Although not the primary focus of this study,such improvements are essential for en-hancing CMA-REPS performance in forecasting extreme precipitation events.关键词
对流尺度集合预报/集合扰动增长/天气强迫/降水可预报性Key words
convective-scale ensemble forecasting/ensemble perturbation growth/synoptic forcing/precipitation predictability引用本文复制引用
王秋萍,周勃旸,孙璐,马旭林,陈静..强弱强迫条件下对流尺度集合扰动增长特征及对降水预报性能的影响[J].大气科学学报,2026,49(3):472-486,15.基金项目
国家自然科学基金气象联合基金项目(U2442221 （）
U2242213) （）
