Dynamics and Predictability of the Rapid Intensification of Super Typhoon Usagi (2013)

Su Liu, Dandan Tao, Kun Zhao, Masashi Minamide, Fuqing Zhang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This study explores the dynamics and predictability of the rapid intensification (RI) of Super Typhoon Usagi (2013) through a 60-member convection-permitting ensemble using the Weather Research and Forecasting (WRF) model and an ensemble Kalman filter (EnKF) data assimilation method. The surface maximum wind speed of Usagi, which was an intense category 4 western North Pacific tropical cyclone (TC), increased by 33 m s−1 over a 24-hr period. The RI process was captured by the WRF simulation initialized with the global analysis but with a unique forecast challenge of early prediction. We improved the intensity forecasts by assimilating satellite-derived atmospheric motion vectors into the WRF-EnKF, which primarily reduced the strength of both the primary and secondary circulations in the TC vortex. Nevertheless, our ensemble forecasts initialized with the EnKF analysis ensemble predicted a significant spread in the intensity with considerable differences in the RI onset timing among individual members. Our analyses show that variation in the RI timing is most sensitive to differences in the initial TC vortex intensity and inner-core moisture. Ensemble members with similar initial intensities but greater tropospheric moisture content exhibited earlier vortex axisymmetrization and consequently earlier RI. Further sensitivity experiments showed that variations in the inner-core moisture content have an immediate impact on the structure and strength of inner-core convection. These variations in inner-core convection gradually caused differences in intensity between the TC vortices. In this study, we highlight the importance of accurate estimates of the inner-core moisture content in the modeling and forecasting of TC intensity.

Original languageEnglish (US)
Pages (from-to)7462-7481
Number of pages20
JournalJournal of Geophysical Research: Atmospheres
Volume123
Issue number14
DOIs
StatePublished - Jul 27 2018

All Science Journal Classification (ASJC) codes

  • Atmospheric Science
  • Geophysics
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science

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