气象学报2026，Vol.84Issue(3)：518-531,14.DOI:10.11676/qxxb2026.20250147
CMA-MESO背景误差协方差的日变化特征及其应用
Characterizing diurnal variations in CMA-MESO background error covariance for improved data assimilation and weather forecasting
摘要
Abstract
Background error covariance(BEC)is a crucial component of variational data assimilation frameworks.Constructing a BEC that more accurately represents reality is essential for enhancing the assimilation and forecasting capabilities of numerical prediction systems.Based on the CMA-MESO kilometer-scale regional numerical prediction system,diurnal variations of BEC parameters are analyzed,and the variational parameters are applied in actual assimilation and forecasting experiments to assess their impacts.The ensemble method is used to calculate background error samples,and BEC parameters are statistically analyzed at eight times of a day with a 3 h interval(00:0 0-21:0 0 UTC)to investigate their diurnal variations.The results show that the standard deviation(STD)of background error and spatial correlation scale of the background error for various variables exhibit clear diurnal variation features in the lower and middle troposphere.The STD of background error of wind and humidity fields are generally larger at night than during the day,with the maximum values occurring at 12:0 0 UTC.For temperature,the STD is larger at 06:0 0 and 09:0 0 UTC with more pronounced variations below 850 hPa.Regarding horizontal correlation,larger correlation scales are observed during 18:0 0-03:0 0 UTC,while smaller correlation scales are found during 06:0 0-15:0 0 UTC when vertical convective mixing is stronger.As for vertical correlation coefficient of the background error,the diurnal variation is most prominent at 06:0 0 UTC,with smaller differences at other times.The idealized experiment results demonstrate that the newly estimated diurnal variation parameters can adjust the influence weights and propagation distances of observational information at different times,ensuring that the assimilation analysis matches the diurnal variation characteristics of BEC.Month-long assimilation and forecasting cycle experiments show that using the diurnal variation BEC parameters reduces assimilation analysis errors in wind and temperature fields,improves precipitation forecasts-particularly for heavy rain and thunderstorms and also reduces 2 m air temperature forecast errors.关键词
变分资料同化/背景误差协方差/千米尺度数值预报/CMA-MESO模式Key words
Variational data assimilation/Background error covariance(BEC)/Kilometer-scale numerical weather prediction/CMA-MESO model分类
天文与地球科学引用本文复制引用
张舒雨,王瑞春,徐枝芳,李泽椿..CMA-MESO背景误差协方差的日变化特征及其应用[J].气象学报,2026,84(3):518-531,14.基金项目
国家重点研发计划项目(2022YFC3004102)、气象能力提升联合研究专项(23NLTSQ005)、中国气象局创新发展专项(CXFZ2025J004). （2022YFC3004102）
