Observing Strategy and Observation Targeting for Tropical Cyclones Using Ensemble-Based Sensitivity Analysis and Data Assimilation
Observing Strategy and Observation Targeting for Tropical Cyclones Using Ensemble-Based Sensitivity Analysis and Data Assimilation
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DOI：
10.1175/mwr-d-12-00188.1
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发表时间：
2013-05
影响因子：
3.2
通讯作者：
Baoguo Xie;Fuqing Zhang;Qinghong Zhang;J. Poterjoy;Y. Weng
中科院分区：
文献类型：
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作者：
Baoguo Xie;Fuqing Zhang;Qinghong Zhang;J. Poterjoy;Y. Weng
摘要利用天气研究与预报模式的集合卡尔曼滤波资料同化系统，结合集合敏感性分析，探讨热带气旋的观测策略和观测目标。本研究所选取的个案是2009年的莫拉克台风，这是一场西太平洋风暴，为台湾带来了破纪录的降雨量。在登陆前48小时，集合灵敏度分析使用50个成员的对流允许集合预测，位于台风西南象限的下投式探空仪观测将有最大的影响，减少预测的不确定性的路径，强度和降雨的莫拉克。一系列的观测系统模拟实验（OSSEs）表明，同化位于较高的预测观测影响的区域的合成下投式探空仪观测，平均而言，会导致一个更好的降雨预报比在较小的预测影响的区域。然而，这些OSSE也表明，该...
AbstractAn ensemble Kalman filter data assimilation system for the Weather Research and Forecasting Model is used with ensemble-based sensitivity analysis to explore observing strategies and observation targeting for tropical cyclones. The case selected for this study is Typhoon Morakot (2009), a western Pacific storm that brought record-breaking rainfall to Taiwan. Forty-eight hours prior to making landfall, ensemble sensitivity analysis using a 50-member convection-permitting ensemble predicts that dropsonde observations located in the southwest quadrant of the typhoon will have the highest impact on reducing the forecast uncertainty of the track, intensity, and rainfall of Morakot. A series of observing system simulation experiments (OSSEs) demonstrate that assimilating synthetic dropsonde observations located in regions with higher predicted observation impacts will, on average, lead to a better rainfall forecast than in regions with smaller predicted impacts. However, these OSSEs also suggest that th...