文献类型：期刊文献

英文题名：Sensitive Areas' Observation Simulation Experiments of Typhoon "Chaba" Based on Ensemble Transform Sensitivity Method

作者：Ao, Yanlong[1];Zhang, Yu[1];Shao, Duanzhou[1];Zhang, Yinhui[1];Tang, Yuan[1];Hu, Jiazheng[1];Zhang, Zhifei[1];Sun, Yuhan[1];Lyu, Peining[1];Yu, Qing[1];He, Ziyan[1]

机构：[1]Guangdong Ocean Univ, Coll Ocean & Meteorol, Zhanjiang 524088, Peoples R China

年份：2024

卷号：15

期号：3

外文期刊名：ATMOSPHERE

收录：SCI-EXPANDED(收录号：WOS:001191414100001)、、EI(收录号：20241315825715)、Scopus(收录号：2-s2.0-85188809441)、WOS

基金：The authors are very grateful to the editor and anonymous reviewers for their help and recommendations.

语种：英文

外文关键词：typhoon; ETS; adaptive observation sensitivity region; data assimilation

外文摘要：High-impact weather (HIW) events, such as typhoons, usually have sensitive regions where additional observations can be deployed and sensitive observations assimilated, which can improve forecasting accuracy. The ensemble transform sensitivity (ETS) method was employed to estimate the sensitive regions in the "Chaba" case in order to explore the impact of observation data in sensitive areas on typhoon forecasting during the rapid intensification phase. A set of observation system simulation experiments were conducted, with assimilations of sensitive observations (SEN), randomly selected observations (RAN), whole domain observations (ALL), and no assimilation (CTRL). The results show that (1) the sensitive areas of Typhoon "Chaba" are primarily located in the southwest of the typhoon center and are associated with the distribution of the wind field structure; (2) the typhoon intensity and tracks simulated by the SEN and RAN experiments are closer to the truth than the CTRL; (3) the SEN experiment, with only 3.6% of assimilated data observations, is comparable with the ALL experiment during the rapid intensification phase of the typhoon; (4) the uncertainty of the mesoscale model can be improved by capturing large-scale vertical wind shear and vorticity features from the GEFS data and then using the data assimilation method, which makes the vertical shear and vorticity field more reasonable.