气象与减灾研究
氣象與減災研究
기상여감재연구
METEOROLOGY AND DISASTER REDUCTION RESEARCH
2015年
1期
16-24
,共9页
薛谌彬%吴静%肖安%唐春燕%洪浩源
薛諶彬%吳靜%肖安%唐春燕%洪浩源
설심빈%오정%초안%당춘연%홍호원
资料同化%多普勒雷达%WRF模式%大暴雨
資料同化%多普勒雷達%WRF模式%大暴雨
자료동화%다보륵뢰체%WRF모식%대폭우
data assimilation%Doppler radar%WRF%heavy rainfall
采用WRF中尺度模式及其三维变分同化系统WRF-3DVAR,对2014年5月24—25日发生在萍乡、宜春地区一次大暴雨天气过程进行了雷达资料直接同化敏感性试验,并对同化结果和模式降水预报进行了对比分析。结果表明:1)雷达资料的同化能有效改善初始场中风场、湿度场和热力场的量值大小及空间分布,使其包含更多的中尺度系统信息。其中,雷达反射率因子的同化对大气湿度场和温度场的影响较大,而雷达径向速度的同化作用主要是调整大气风场。2)短时降水预报方面,雷达反射率因子的同化对0—12 h短时降水预报的量值影响较大,而径向速度的同化对降水预报的落区影响较大,两者同时的同化对降水预报效果较好。3)雷达资料的同化对较长时间(6—12 h)的降水预报仍有较好效果。
採用WRF中呎度模式及其三維變分同化繫統WRF-3DVAR,對2014年5月24—25日髮生在萍鄉、宜春地區一次大暴雨天氣過程進行瞭雷達資料直接同化敏感性試驗,併對同化結果和模式降水預報進行瞭對比分析。結果錶明:1)雷達資料的同化能有效改善初始場中風場、濕度場和熱力場的量值大小及空間分佈,使其包含更多的中呎度繫統信息。其中,雷達反射率因子的同化對大氣濕度場和溫度場的影響較大,而雷達徑嚮速度的同化作用主要是調整大氣風場。2)短時降水預報方麵,雷達反射率因子的同化對0—12 h短時降水預報的量值影響較大,而徑嚮速度的同化對降水預報的落區影響較大,兩者同時的同化對降水預報效果較好。3)雷達資料的同化對較長時間(6—12 h)的降水預報仍有較好效果。
채용WRF중척도모식급기삼유변분동화계통WRF-3DVAR,대2014년5월24—25일발생재평향、의춘지구일차대폭우천기과정진행료뢰체자료직접동화민감성시험,병대동화결과화모식강수예보진행료대비분석。결과표명:1)뢰체자료적동화능유효개선초시장중풍장、습도장화열력장적량치대소급공간분포,사기포함경다적중척도계통신식。기중,뢰체반사솔인자적동화대대기습도장화온도장적영향교대,이뢰체경향속도적동화작용주요시조정대기풍장。2)단시강수예보방면,뢰체반사솔인자적동화대0—12 h단시강수예보적량치영향교대,이경향속도적동화대강수예보적락구영향교대,량자동시적동화대강수예보효과교호。3)뢰체자료적동화대교장시간(6—12 h)적강수예보잉유교호효과。
Based on the mesoscale model WRF and its three dime nsional variational assimilation system WRF-3DVAR , some sensitivity experiments were carried out to analysis the improvement of model precipitation forecast by directly assimilating Doppler radar reflectivity and radial velocity data to a heavy rainfall case occurred in Pingxiang and Yichun areas on May 24 , 2014. The results showed that:1) assimilation of radar data can effectively improve the magnitude and spatial distribution of the initial field in terms of atmospheric wind, humidity and thermal fields due to more mesoscale information included. Assimilation of radar reflectivity had a greater impact on the atmospheric humidity and temperature fields , while assimilation of radar radial velocity majorly adjusted the atmospheric wind field. 2) for the short-time (0—12 h) precipitation forecast, assimilation of radar reflectivity played an important role in the precipitation amount forecast, while assimilating radar radial velocity influenced on the distribution of the rainfall. And the accumulated precipitation was forecasted with better rainfall pattern when radar reflectivity and radial velocity data were assimilated into the model at the same time. 3) The rainfall forecast of 6—12 h can be improved by assimilating radar data.