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On the Predictability and Dynamics of Tropical Cyclone: Nargis (2008)

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Abstract

Abstract:The predictability of tropical cyclone (TC) Nargis formed over the Bay of Bengal is explored using ensemble forecasts initialized from Ensemble Kalman Filter (EnKF) DA system in Weather Research and Forecasting (WRF) Model. The unusual eastward recurvature followed by the weakening and rapid intensification of Nargis is investigated in this study. The ensemble members display an early recurvature when compared to Joint Typhoon Warning Center (JTWC) best track estimate and indicate a large uncertainty in the prediction of landfall location, which is far north of the actual landfall location. Additionally, the ensemble forecasts depict a rapid movement of TC as compared to the best track estimate. Further investigation on the dynamics of faster movement of TC reveals that the ensemble members with faster (slower) moving TC is associated with stronger (weaker) steering wind. It appears that the early recurvature of Nargis is also associated with strong steering flow in the ensemble forecasts. A few ensemble members could capture the short period weakening of Nargis after initial intensification. The analysis of ensemble forecasts indicates that the weakening of Nargis is associated with the development of a weak vortex to the northeast of the storm center. While the coarser resolution ensemble forecast simulates the rapid intensification (RI) phase in 1 out of the 80 ensemble members, the ensemble simulations performed on convection‐permitting resolution have enhanced the probability of simulating RI phase of Nargis.
Original languageEnglish
Article numbere2019JD032040
JournalJournal of Geophysical Research: Atmospheres
Volume125
Issue number9
DOIs
Publication statusPublished - 16 May 2020

Funding

We are thankful to two anonymous reviewers whose helpful comments that improved this manuscript. The authors thank Indian Institute of Tropical Meteorology (IITM), Pune for providing computational resources to carry out this work. The NCEP global forecast system analyses and forecasts data utilized in this study are openly available in the repository (https://rda.ucar.edu) online (https://doi.org/10.5065/D65Q4TSG). Data assimilation is performed using observations derived from NCEP ADP Global Upper Air and Surface Weather Observations archived (https://rda.ucar.edu) online (https://doi.org/10.5065/Z83F-N512). ERA-interim data used for validation of the model result can be accessed (https://rda.ucar.edu) online (https://doi.org/10.5065/D6CR5RD9).

Funders
NCEP

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