Climate analysis & attribution
Impact of the Madden–Julian Oscillation on North Indian Ocean Cyclone Intensity
In one sentence. An artificial neural network links MJO indices to North Indian Ocean cyclone wind intensity over 1974–2019, with scatter index falling from 0.45 for depressions to 0.03 for super cyclones.
Abstract
The influence of the Madden–Julian Oscillation (MJO) on the intensity of the Tropical Cyclones in the North Indian Ocean is investigated through a machine learning algorithm. The magnitude of wind, considered as a proxy for the intensity, is taken from the Joint Typhoon Warning Centre (JTWC), and the MJO information for 1974–2019 is from Australia’s Bureau of Meteorology. These two observations have been collocated and the influence of MJO indices on the wind speed was studied using an artificial neural network technique. The scatter index, defined as the root mean square error (RMSE) normalized to the input data mean, varies from 0.45 for depressions to 0.03 for the super cyclonic storms, indicating that the MJO index is another parameter that should be investigated in cyclone activity studies.
Labels
- Topic
- Climate analysis & attribution, Extremes & hazards
- Type
- Application study
- Method
- Other
- Domain
- Regional
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.3390/atmos12121554 OpenAlex:W3216537882
- Added
- 2026-10-22
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