同化GPS可降水量资料在安徽地区暴雨预报中的应用

Application of assimilated GPS/PWV data to the rainstorms forecast over Anhui province

利用2014年5月10日08时和5月24日08时的中国GPS(Global Positioning System)可降水量资料、地面气象观测资料及探空资料,基于WRF(Weather Research Forecast)模式及其三维变分同化系统对安徽地区2014年5月10日区域性暴雨过程和5月24日局地性暴雨过程进行了同化研究。结果表明:同化GPS水汽资料能较好地改善WRF模式的湿度场,对风场的调整较小;同化探空资料和地面常规气象观测资料可以同时调整湿度场与风场,但对湿度场的改善效果明显不如同化GPS水汽资料。仅同化GPS可降水资料,可以改进暴雨落区和强度的WRF模式模拟预报效果;而同化探空资料和地面常规气象观测资料对暴雨落区与强度预报的改进效果低于仅同化GPS水汽资料;同时同化地面常规气象观测资料、探空资料和GPS可降水资料对暴雨强度与落区的预报效果改进明显,与实况更接近,暴雨预报的TS评分更高,空报率更低。

GPS/PWV （Precipitable Water Vapor） data, sounding and surface data are assimilated into the WRF model together with a 3DVar assimilation system to investigate their effects on a regional rainstorm on May 10 and a local one on May 24,2015, respectively, over Anhui province. The results show that GPS/PWV data assimilated to WRF can improve the relative humidities in an initial field, but have little influence on wind. However, sounding and surface data assimilation can improve both relative humilities and wind, with a slightly worse result than that of GPS/PWV for the humidities. The forecast capacities of rainstorm locations and intensities may be enhanced with the assimilated GPS/PWV data only, superior to those with sounding and surface data. If all these data were assim- ilated to the WRF, the rainstorm locations and intensities can be significantly improved and closer to the observa- tions, leading to higher TS scores and lower false-alarm rates.