文献类型：期刊文献

英文题名：Impact of GPS radio occultation assimilation on the 18-21 July 2021 heavy rainfall event in Henan

作者：Chen, Siqi[1,2,3,5];Xu, Jianjun[2,3,5];Zhang, Yu[2,3,4,5];Shen, Wenqi[2,3,4,5];Guan, Zhaoyong[6];Dong, Changming[1]

机构：[1]Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing, Peoples R China;[2]Guangdong Ocean Univ, GDOU Joint Lab Marine Meteorol, CMA, Zhanjiang, Peoples R China;[3]Guangdong Ocean Univ, South China Sea Inst Marine Meteorol, Zhanjiang, Peoples R China;[4]Guangdong Ocean Univ, Coll Ocean & Meteorol, Zhanjiang, Peoples R China;[5]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen, Peoples R China;[6]Nanjing Univ Informat Sci & Technol, Key Lab Meteorol Disasters China Minist Educ KLME, Nanjing, Peoples R China

年份：2023

卷号：286

外文期刊名：ATMOSPHERIC RESEARCH

收录：SCI-EXPANDED(收录号：WOS:000944621700001)、、EI(收录号：20230813617580)、Scopus(收录号：2-s2.0-85148329710)、WOS

基金：This study was jointly supported and funded by Chinese Nature Science Foundation (72293604) , the National Key Research and Development Program of China (2019YFC1510002) , Chinese Nature Science Foundation (42130605 and 41705140) , Guangdong Basic and Applied Basic Science Research Foundation (2019B1515120018, 2019A1515111009) , Shenzhen Nature Science Foundation (JCYJ20210324131810029) , and Open Foundation of Key Laboratory of Highland Basin Storm Drought and Flood Disaster (SZKT201902) .

语种：英文

外文关键词：GPS-RO; Data assimilation; EFSO; "21 center dot 7" rainstorm event in Henan Province

外文摘要：The Gridpoint Statistical Interpolation (GSI) assimilation system and Weather Research & Forecasting (WRF) mesoscale regional model were used to investigate the sensitivity of assimilating Global Positioning System radio occultation (GPS-RO) data for a "21 center dot 7" heavy rainfall event in Henan Province. The Ensemble Forecast Sensitivity to Observation (EFSO) algorithm was used to assess the influence of the GPS-RO assimilation relative to conventional heavy rainfall observations in Henan. Sensitivity experiments revealed that the 6-h accumulated precipitation simulated by the three experiments surpassed 200 mm, which was similar to the automated station observations, and the rainfall center location and intensity simulated by the assimilated GPS-RO experiment (EXPR2) were also similar to the observations. Following GPS-RO data assimilation, the upper-level west border continental high pressure was improved, which increased the pressure gradient on the east and west sides of the heavy rainfall, resulting in enhanced dynamic lifting and water vapor flow from the lower level to the whole Henan downpour center. The entire convective convergence rising height increased, which had an optimum influence on the dynamic and thermal conditions of heavy rainfall. The EFSO estimates revealed that most observations improved the model predictions, with the conventional surface pressure and U-wind observations making a positive standardized contribution of approximately 0.05 and 0.075, respectively, but T(Temperature) and Q(Specific humidity) making a negative standardized contribution of approximately-0.025. The GNSS GPS-RO greatly improved the prediction results by decreasing the error by 0.125, and the National Satellite Meteorological Center (NSMC) FY-3D contributed the most to the model.