快速更新循环同化系统的背景场误差协方差日变化特征研究及初步应用

Research on diurnal variation characteristics of background error covariances in rapid update cycling data assimilation and forecasting system and their impacts on preliminary applications

目前多数快速更新循环同化系统在各分析时刻常使用固定的背景场误差协方差。为在快速更新循环同化系统中采用日变化的背景场误差协方差,基于RMAPS-ST系统分析了其夏季和冬季日变化背景场误差协方差特征,并进行了同化及预报对比试验。结果表明,该系统夏、冬两季的背景场误差协方差均呈现出明显的日变化特征,且夜间各变量(U、V、T、RH)的误差标准差与特征值均大于日间,反映模式系统夜间的预报误差大于日间;而夏季各变量误差标准差和特征值大于冬季,也说明系统在夏季的模式预报误差比冬季大;连续3 d的循环同化试验初步表明,采用日变化背景场误差协方差可以提高同化及预报效果。

Background error covariance plays an essential role in data assimilation systems,particularly in variational assimilation systems.The National Meteorological Center(NMC)method has widely been used to generate forecast error samples for estimating background error covariance.Currently,most variational-based rapid update and cycling(RUC)data assimilation and forecasting systems use a fixed background error covariance at each analysis moment to reduce computational costs.However,with the increasing frequency of assimilation in the RUC data assimilation and forecasting systems,a fixed background error covariance may not be suitable for all analysis moments.To adopt diurnal background error covariance in the RUC data assimilation and forecasting system more reasonably,the diurnal background error covariance characteristics in summer and winter are analyzed by the NMC method based on the RMAPS-ST system,and assimilation and forecast experiments are conducted.The results show that the background error covariances in summer and winter exhibit obvious diurnal characteristics.The standard deviation of forecast error samples and the eigenvalues of each control variable(U,V,T,and RH s)are higher at night than during the day,indicating that the forecast errors of the model system are more significant at night than during the day.Meanwhile,the standard deviation of forecast error samples and the eigenvalues of each control variable are higher in summer than in winter,suggesting that the model forecast errors of the system are greater in summer than in winter.The horizontal length scale is generally larger in summer than in winter,which may be because the spatial integrity of the RMAPS-ST system forecast error is more consistent in summer and the horizontal correlation is higher,leading to a larger length scale.The 3-day cycling experiments initially indicate that the use of diurnal background error covariances can improve the assimilation and forecast of the U,V,T,and Q fields of RMAPS-ST system,thereby enhancing the performance of precipitation forecasts.