Dynamics and Predictability of the Rapid Intensification of Super Typhoon Usagi (2013)
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 20, 2018
- Source ID
- 10.1029/2018jd028561
Entities
People
- Dandan Tao
- Fuqing Zhang
- Kun Zhao
- Masashi Minamide
- Su Liu
Organizations
- China Meteorological Administration
- Chinese Academy of Meteorological Sciences
- Ministry of Science and Technology of the People's Republic of China
- Nanjing University
- National Aeronautics and Space Administration
- National Natural Science Foundation of China
- Office of Naval Research
- Pennsylvania State University