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Tropical Cyclone intensity prediction based on hybrid learning techniques

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Abstract

Coastal regions in India are very frequently hit by Tropical Cyclones (TCs), which result in tremendous loss. Its intensity prediction has been a challenging task because of drastic climatic changes over the past few years in the world. Intensity of Tropical Cyclone is highly influenced by ocean, atmospheric and meteorological parameters which makes the task difficult to define the mechanism of Tropical Cyclone intensity prediction. Here, a hybrid deep learning model is built using historical observations collected from various sources to perform a data-driven prediction of Tropical Cyclone’s intensity using regression model. This hybrid model utilizes convolutional neural network (CNN) architectures for feature extraction and machine learning models for regression. The hyper-parameters are optimized to fine-tune the model. The weights and biases are optimized using stochastic gradient descent (SGD). The proposed system is also compared with other regression models in machine learning and deep learning. The spatial analysis is accomplished using Modern-Era Retrospective analysis for Research and Applications, Version 2 Project Overview (MERRA-2) data for various coastal regions that are hit by cyclones. The temporal analysis is carried out using intensity skill forecast for time-series observation. The proposed system is also tested for Cyclone Amphan that hit eastern coastal regions of India.

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Acknowledgements

We thank Ministry of Earth Sciences, Government of India and Director, NIOT for their support and encouragement.

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Authors and Affiliations

  1. Department of Computer Technology, Madras Institute of Technology, Anna University, Chennai, 600 044, India

    P Varalakshmi & N Vasumathi

  2. National Institute of Ocean Technology, Chennai, India

    R Venkatesan

Authors
  1. P Varalakshmi
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  2. N Vasumathi
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  3. R Venkatesan
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Contributions

VP performed the conceptualization, supervision, project administration, writing, reviewing, and editing. VN performed the data curation and formal analysis and wrote the original draft. VR performed the investigation.

Corresponding author

Correspondence to P Varalakshmi.

Additional information

Communicated by P A Francis

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Varalakshmi, P., Vasumathi, N. & Venkatesan, R. Tropical Cyclone intensity prediction based on hybrid learning techniques. J Earth Syst Sci 132, 28 (2023). https://doi.org/10.1007/s12040-022-02042-5

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  • DOI: https://doi.org/10.1007/s12040-022-02042-5

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