利用GRAPES(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统)三维变分同化系统,针对对流天气系统特点,用改进的郭晓岚对流参数化方案作为观测算子,同化广东省自动站记录的对流天气系统的雨量...利用GRAPES(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统)三维变分同化系统,针对对流天气系统特点,用改进的郭晓岚对流参数化方案作为观测算子,同化广东省自动站记录的对流天气系统的雨量资料,并且与同化探空资料进行了比较。在雨带有明显改进的区域,分别同化这两种资料都可以调整大气低层水汽辐合增加(或辐散),对流层中下层增暖增湿(或变冷变干),从而增加(或减少)降水,表明降水的同化方案对初始场的调整在一定程度上符合探空观测。进一步讨论同时同化这两种资料对暴雨预报的影响,结果表明同化自动站降水资料对暴雨系统短时预报有正面影响,同时同化这两种资料,可以弥补资料的不足。展开更多
This study evaluates the impact of atmospheric observations from the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observing system on numerical weather prediction of hurricane Ike (2008) using three-di...This study evaluates the impact of atmospheric observations from the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observing system on numerical weather prediction of hurricane Ike (2008) using three-dimensional data assimilation system for the Weather Research and Forecast (WRF) model (WRF 3D-Var). The TAMDAR data assimilation capability is added to WRF 3D-Var by incorporating the TAMDAR observation operator and corresponding observation processing procedure. Two 6-h cycling data assimilation and forecast experiments are conducted. Track and intensity forecasts are verified against the best track data from the National Hurricane Center. The results show that, on average, assimilating TAMDAR observations has a positive impact on the forecasts of hurricane Ike. The TAMDAR data assimilation reduces the track errors by about 30 km for 72-h forecasts. Improvements in intensity forecasts are also seen after four 6-h data assimilation cycles. Diagnostics show that assimilation of TAMDAR data improves subtropical ridge and steering flow in regions along Ike's track, resulting in better forecasts.展开更多
文摘利用GRAPES(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统)三维变分同化系统,针对对流天气系统特点,用改进的郭晓岚对流参数化方案作为观测算子,同化广东省自动站记录的对流天气系统的雨量资料,并且与同化探空资料进行了比较。在雨带有明显改进的区域,分别同化这两种资料都可以调整大气低层水汽辐合增加(或辐散),对流层中下层增暖增湿(或变冷变干),从而增加(或减少)降水,表明降水的同化方案对初始场的调整在一定程度上符合探空观测。进一步讨论同时同化这两种资料对暴雨预报的影响,结果表明同化自动站降水资料对暴雨系统短时预报有正面影响,同时同化这两种资料,可以弥补资料的不足。
基金funded by the Air Dat projectThe National Center for Atmospheric Research is sponsored by the National Science Foundation
文摘This study evaluates the impact of atmospheric observations from the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observing system on numerical weather prediction of hurricane Ike (2008) using three-dimensional data assimilation system for the Weather Research and Forecast (WRF) model (WRF 3D-Var). The TAMDAR data assimilation capability is added to WRF 3D-Var by incorporating the TAMDAR observation operator and corresponding observation processing procedure. Two 6-h cycling data assimilation and forecast experiments are conducted. Track and intensity forecasts are verified against the best track data from the National Hurricane Center. The results show that, on average, assimilating TAMDAR observations has a positive impact on the forecasts of hurricane Ike. The TAMDAR data assimilation reduces the track errors by about 30 km for 72-h forecasts. Improvements in intensity forecasts are also seen after four 6-h data assimilation cycles. Diagnostics show that assimilation of TAMDAR data improves subtropical ridge and steering flow in regions along Ike's track, resulting in better forecasts.
