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Modulation of south indian ocean tropical cyclones by the Madden-Julian oscillation and convectively coupled equatorial waves

The subseasonal modulation of tropical cyclone (TC) genesis by large-scale atmospheric wave modes is studied using data from the south Indian Ocean region. The modes considered are the Madden-Julian oscillation (MJO), and the convectively coupled equatorial Rossby (ER), Kelvin, and mixed Rossby-grav...

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Bibliographic Details
Published in:Monthly weather review 2006-02, Vol.134 (2), p.638-656
Main Authors: BESSAFI, Miloud, WHEELER, Matthew C
Format: Article
Language:English
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Summary:The subseasonal modulation of tropical cyclone (TC) genesis by large-scale atmospheric wave modes is studied using data from the south Indian Ocean region. The modes considered are the Madden-Julian oscillation (MJO), and the convectively coupled equatorial Rossby (ER), Kelvin, and mixed Rossby-gravity (MRG) waves. Analysis of all TCs west of 100'E reveals a large and statistically significant modulation by the MJO and ER waves, a small yet significant modulation by Kelvin waves, and a statistically insignificant modulation by MRG waves. Attribution of the observed TC modulation was made through examination of the wave-induced perturbations to the dynamical fields of low-level vorticity, vertical shear, and deep convection. Possible thermodynamic influences on TC genesis were neglected. Different combinations of the three dynamical fields were necessary for successful attribution for each of the large-scale wave modes. For example, for the MJO, the modulation was best attributable to its perturbations to both the vorticity and shear fields, while for the ER wave, it was its perturbations to the convection and vorticity fields that appeared to best be able to explain the modulation. It appears that there is no single factor that can be used for the attribution of all subseasonal TC variability. Finally, it is shown that the modulation of TCs by at least the MJO and ER waves is large enough to warrant further investigation for prediction on the weekly time scale.
ISSN:0027-0644
1520-0493
DOI:10.1175/mwr3087.1