CAJ | 학술논문

基于 WRF（Weather Research Forecast）模式和 GSI（Gridpoint Statistical Interpolation）同化系统，研究了同化4部多普勒雷达探测资料对“7．21”北京特大暴雨过程中降水预报的改善作用。GSI 系统直接同化径向风，而采用云分析的方式间接同化反射率。2012年7月20日21时—21日00时（世界时）雷达探测资料同化试验采用30 min 循环同化径向风和反射率资料。结果表明，循环同化雷达探测资料改善了短时（0—6 h）和短期（0—24 h）降水预报，ETS 评分提高了约0．2。同化反射率资料增加了初始场的水凝物，改善了温度场分布，直接影响了降水的形成，同时还使650—250 hPa 位势高度的均方根误差平均降低了8 gpm。直接同化径向风资料对中尺度风场产生了一定影响。ETS 评分结果表明：同化反射率资料的效果要优于同化径向风。
기우 WRF（Weather Research Forecast）모식화 GSI（Gridpoint Statistical Interpolation）동화계통，연구료동화4부다보륵뢰체탐측자료대“7．21”북경특대폭우과정중강수예보적개선작용。GSI 계통직접동화경향풍，이채용운분석적방식간접동화반사솔。2012년7월20일21시—21일00시（세계시）뢰체탐측자료동화시험채용30 min 순배동화경향풍화반사솔자료。결과표명，순배동화뢰체탐측자료개선료단시（0—6 h）화단기（0—24 h）강수예보，ETS 평분제고료약0．2。동화반사솔자료증가료초시장적수응물，개선료온도장분포，직접영향료강수적형성，동시환사650—250 hPa 위세고도적균방근오차평균강저료8 gpm。직접동화경향풍자료대중척도풍장산생료일정영향。ETS 평분결과표명：동화반사솔자료적효과요우우동화경향풍。
Based on the WRF (Weather Research Forecast)model and the GSI (Gridpoint Statistical Interpolation)assimilation system,the impact of the assimilating four Doppler weather radars (DWR)reflectivity and radial velocity (Vr )for quantitative precipitation forecasts (QPFs)of the "7.21" Beijing excessive storm have been examined.The GSI directly assimilates Vr , while indirectly assimilates the reflectivity through the cloud analysis.The radar data are assimilated every 30 min from 21:00 UTC 20 Jul to 00:00 UTC 21 Jul 2012.The numerical experiments demonstrate that the DWR data assimilation can improve nowcast and short-term precipitation forecasts,whose ETS scores averagely increase by 0.2.The reflectivity data are used pri-marily in a cloud analysis that retrieves the amount of hydrometeors and adjusts the in-cloud temperature and moisture which have direct influence on generating precipitation.The assimilating reflectivity makes the root-mean-square error (RMSE)of the geopotential height averaged over between 650 and 250 hPa decreases by 8 gpm.The direct assimilation of DWRVr in GSI ex-erts a sure influence in mesoscale wind fields.Through the quantitative verification of the simulation results,the forecast with reflectivity assimilation is better than that with the Vr assimilation.