Observation System Experiments for Typhoon Nida (2004) Using the CNOP Method and DOTSTAR Data

被引:11
作者
Chen Bo-Yu [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Atmospher Phys, State Lab Numer Modeling Atmospher Sci & Geophys, Beijing 100029, Peoples R China
[2] Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
targeted observations; OSE; CNOP; sensitive area;
D O I
10.1080/16742834.2011.11446914
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This study investigated the influence of drop-windsonde observations on typhoon forecasts. The study also evaluated the feasibility of the conditional nonlinear optimal perturbation (CNOP) method as a basis for sensitivity analysis of such forecasts. This sensitivity analysis could furnish guidance in the selection of targeted observations. The study was performed by conducting observation system experiments (OSEs). This research used the fifth -generation Mesoscale Model (MM5), the Weather Research and Forecasting (WRF) model, and dropsonde observations of Typhoon Nida at 1200 UTC 17 May 2004. The dropsondes were collected under the operational Dropsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) program. In this research, five kinds of experiments were designed and conducted: (1) no observations were assimilated; (2) all observations were assimilated; (3) observations in the sensitive area revealed by the CNOP method were assimilated; (4) the same as in (3), but for the region revealed by the first singular vector (FSV) method; and (5) observations within a randomly selected area were assimilated. The OSEs showed that (1) the DOTSTAR data had a positive impact on the forecast of Nida's track; (2) dropsondes in the sensitive areas identified by the MM5 CNOP and FSV remained effective for improving the track forecast for Nida on the WRF platform; and (3) the greatest improvement in the track forecast resulted from the CNOP-based (third) simulation, which indicated that the CNOP method would be useful in decision making about dropsonde deployments.
引用
收藏
页码:118 / 123
页数:6
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