中文摘要：

这研究在台风预报上调查了 drop-windsonde 观察的影响。学习也评估了方法作为这的敏感分析的一个基础预报的有条件的非线性的最佳的不安(CNOP ) 的可行性。这敏感分析能在指向的观察的选择供应指导。学习被进行观察系统实验(OSE ) 执行。这研究使用了第五产生的 Mesoscale 模型(MM5 ) ，天气研究并且预报(WRF ) 在 1200 UTC 17 2004 年 5 月的台风 Nida 的模型，和下投式探空仪观察。下投式探空仪在台湾区域(DOTSTAR ) 程序附近为台风监视在运作的下投式探空仪观察下面被收集。在这研究，五种实验被设计并且进行：(1 ) 没有观察被吸收；(2 ) 所有观察被吸收；(3 ) 在 CNOP 方法揭示的敏感区域的观察被吸收；(4 ) 与在一样(3 ) ，要不是第一单个向量(FSV ) 揭示的区域方法；并且(5 ) 在一个随机选择的区域以内的观察被吸收。OSE 证明(1 ) DOTSTAR 数据在 Nida 的磁道的预报上有积极影响；(2 ) 在 MM5 CNOP 和 FSV 识别的敏感区域的下投式探空仪为在 WRF 站台上为 Nida 改进轨道预报仍然保持有效；并且(3 ) 在轨道预报的最大的改进源于基于 CNOP (第三) 模拟，它显示 CNOP 方法将在关于下投式探空仪推广的决策是有用的。

英文摘要：

This study investigated the influence of dropwindsonde 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 observa- tion 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.