Observing strategy and observation targeting for tropical cyclones using ensemble-based sensitivity analysis and data assimilation

Baoguo Xie, Fuqing Zhang, Qinghong Zhang, Jonathan Poterjoy, Yonghui Weng

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

An ensemble Kalman filter data assimilation systemfor theWeather Research and ForecastingModel 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 typhoonwill 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 the effectiveness of the current-generation ensemble-based tropical cyclone targeting strategies may be limited. The limitations may be due to strong nonlinearity in the governing dynamics of the typhoon (e.g., moist convection), the accuracy of the ensemble background covariance, and the projection of individual dropsonde observations to the complicated targeted sensitivity vectors from the ensemble.

Original languageEnglish (US)
Pages (from-to)1437-1453
Number of pages17
JournalMonthly Weather Review
Volume141
Issue number5
DOIs
StatePublished - May 2013

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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