利用SMS-WARR快速更新同化,对三种观测资料(雷达、探空、AMDAR)进行敏感性试验。并且通过对2011年7月31日发生在上海的局地强对流过程的模拟,分析不同类型观测资料的影响。结果表明:雷达资料通过云分析优化了初始场中的水物质含量,使云...利用SMS-WARR快速更新同化,对三种观测资料(雷达、探空、AMDAR)进行敏感性试验。并且通过对2011年7月31日发生在上海的局地强对流过程的模拟,分析不同类型观测资料的影响。结果表明:雷达资料通过云分析优化了初始场中的水物质含量,使云的分布更合理,调整了中小尺度对流系统的结构和强度,降水落区和强度预报得到改进;探空资料在试验中仅使用了一次,但可持续影响后续时刻的模拟,500 h Pa、700 h Pa和850 h Pa高度场和风场均不同程度受到影响,相应的地面温度也发生了变化;同化AMDAR资料后,形势场得到了修正,分析场更加接近实况,改善了降水预报。展开更多
A dual-resolution（DR） version of a regional ensemble Kalman filter（EnKF）-3D ensemble variational（3DEnVar） coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh f...A dual-resolution（DR） version of a regional ensemble Kalman filter（EnKF）-3D ensemble variational（3DEnVar） coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh forecasting system. The DR 3DEnVar system combines a high-resolution（HR） deterministic background forecast with lower-resolution（LR） EnKF ensemble perturbations used for flow-dependent background error covariance to produce a HR analysis. The computational cost is substantially reduced by running the ensemble forecasts and EnKF analyses at LR. The DR 3DEnVar system is tested with 3-h cycles over a 9-day period using a 40/13-km grid spacing combination. The HR forecasts from the DR hybrid analyses are compared with forecasts launched from HR Gridpoint Statistical Interpolation（GSI） 3D variational（3DVar）analyses, and single LR hybrid analyses interpolated to the HR grid. With the DR 3DEnVar system, a 90% weight for the ensemble covariance yields the lowest forecast errors and the DR hybrid system clearly outperforms the HR GSI 3DVar.Humidity and wind forecasts are also better than those launched from interpolated LR hybrid analyses, but the temperature forecasts are slightly worse. The humidity forecasts are improved most. For precipitation forecasts, the DR 3DEnVar always outperforms HR GSI 3DVar. It also outperforms the LR 3DEnVar, except for the initial forecast period and lower thresholds.展开更多
文摘利用SMS-WARR快速更新同化,对三种观测资料(雷达、探空、AMDAR)进行敏感性试验。并且通过对2011年7月31日发生在上海的局地强对流过程的模拟,分析不同类型观测资料的影响。结果表明:雷达资料通过云分析优化了初始场中的水物质含量,使云的分布更合理,调整了中小尺度对流系统的结构和强度,降水落区和强度预报得到改进;探空资料在试验中仅使用了一次,但可持续影响后续时刻的模拟,500 h Pa、700 h Pa和850 h Pa高度场和风场均不同程度受到影响,相应的地面温度也发生了变化;同化AMDAR资料后,形势场得到了修正,分析场更加接近实况,改善了降水预报。
基金supported by the National Natural Science Foundation of China (Grant Nos.41730965,41775099 and 2017YFC1502104)PAPD (the Priority Academic Program Development of Jiangsu Higher Education Institutions)
文摘A dual-resolution（DR） version of a regional ensemble Kalman filter（EnKF）-3D ensemble variational（3DEnVar） coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh forecasting system. The DR 3DEnVar system combines a high-resolution（HR） deterministic background forecast with lower-resolution（LR） EnKF ensemble perturbations used for flow-dependent background error covariance to produce a HR analysis. The computational cost is substantially reduced by running the ensemble forecasts and EnKF analyses at LR. The DR 3DEnVar system is tested with 3-h cycles over a 9-day period using a 40/13-km grid spacing combination. The HR forecasts from the DR hybrid analyses are compared with forecasts launched from HR Gridpoint Statistical Interpolation（GSI） 3D variational（3DVar）analyses, and single LR hybrid analyses interpolated to the HR grid. With the DR 3DEnVar system, a 90% weight for the ensemble covariance yields the lowest forecast errors and the DR hybrid system clearly outperforms the HR GSI 3DVar.Humidity and wind forecasts are also better than those launched from interpolated LR hybrid analyses, but the temperature forecasts are slightly worse. The humidity forecasts are improved most. For precipitation forecasts, the DR 3DEnVar always outperforms HR GSI 3DVar. It also outperforms the LR 3DEnVar, except for the initial forecast period and lower thresholds.
