INFLUENCE OF DIFFERENT-SCALE ERRORS INTERACTIONS ON ANALYSIS AND FORECAST OF REGIONAL NWP MODEL

In the previous study, the influences of introducing larger- and smaller-scale errors on the background error covariances estimated at the given scales were investigated, respectively. This study used the covariances obtained in the previous study in the data assimilation and model forecast system based on three-dimensional variational method and the Weather Research and Forecasting model. In this study, analyses and forecasts from this system with different covariances for a period of one month were compared, and the causes for differing results were presented. The variations of analysis increments with different-scale errors are consistent with those of variances and correlations of background errors that were reported in the previous paper. In particular, the introduction of smaller-scale errors leads to greater amplitudes in analysis increments for medium-scale wind at the heights of both high- and low-level jets. Temperature and humidity analysis increments are greater at the corresponding scales at the middle- and upper-levels. These analysis increments could improve the intensity of the jet-convection system that includes jets at different levels and the coupling between them that is associated with latent heat release. These changes in analyses will contribute to more accurate wind and temperature forecasts in the corresponding areas. When smaller-scale errors are included, humidity analysis increments are significantly enhanced at large scales and lower levels, to moisten southern analyses. Thus, dry bias can be corrected, which will improve humidity forecasts. Moreover, the inclusion of larger- (smaller-) scale errors will be beneficial for the accuracy of forecasts of heavy (light) precipitation at large (small) scales because of the amplification (diminution) of the intensity and area in precipitation forecasts.     

全球探空站附近掩星观测资料误差估计北大核心

利用2016年1月1日至2020年10月1日GPS无线电掩星观测、探空观测、美国微波综合反演系统(MiRS)卫星微波资料反演产品、美国国家环境预报中心全球预报系统(Global Forecast System,GFS)分析资料和欧洲中期天气预报中心ERA5再分析资料这5种资料,采用“三角帽”方法,估计GPS掩星资料的观测误差,分析了资料集之间偏差和误差相关性对观测误差估计值的影响。结果表明,用MiRS资料替代ERA5再分析资料后所得到的掩星观测误差大于用掩星、探空观测、GFS分析和ERA5再分析资料的掩星观测误差。掩星观测误差随纬度增加而减小。本文对即将到来的掩星资料的合理应用具有重要意义。