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Tropical cyclone intensity forecasting in the Bay of Bengal using a biologically inspired computational model

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Abstract

Background

Effective management of tropical cyclone (TC) emergencies largely depends on accurate forecasting of TC intensity. Despite being essential for successful disaster warning/management, accurate forecasting of TC intensity has remained a challenging task still today, mainly because of inadequate knowledge about the processes associated with TC intensity change as well as lack of suitable data representing those processes.

Objective

This study aims at employing a biologically inspired computational model with combined supervised and unsupervised learning capabilities to forecast tropical cyclone (TC) intensity 12– and 24 h ahead in the Bay of Bengal (BoB).

Method

The model was simulated separately in train and test phases based on temporal sequences of infrared, sea surface temperature, sea-level pressure, wind direction and wind speed images of ten TCs formed between 2006 and 2021 in the BoB. Intensity forecasts were produced on a four-point scale used by the Bangladesh Meteorological Department and validated against the observed wind speeds in the TC best track datasets.

Results

Intensity prediction accurately was over 90% when the model was tested using datasets consisting of temporal continuances of TC lifecycle images kept out of training. However, TC intensity forecasting accuracy remained between 36 and 48%, when the model was used to generate forecasts for the images of a completely new TC.

Conclusions

These findings indicate, biologically inspired computational model may further be developed into a useful TC intensity forecasting technique through systematic training and testing using images of more TCs in the BoB.

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Data Availability

All the images used for training and testing the model will be made available on reasonable request.

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Authors and Affiliations

  1. Department of Geography and Environmental Studies, University of Rajshahi, Rajshahi, 6205, Bangladesh

    Chandan Roy, Md. Rejaur Rahman, Manoj Kumer Ghosh & Shoumen Biswas

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  1. Chandan Roy
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  2. Md. Rejaur Rahman
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  3. Manoj Kumer Ghosh
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Contributions

CR together with SB conceptualized the study. CR and SB analyzed the data. SB helped CR to prepare the TC images for training and testing the network. CR prepared the first draft, RR and MKG reviewed and improved it. CR made it ready for submission. The final manuscript was reviewed and approved by all the authors.

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Correspondence to Chandan Roy.

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Roy, C., Rahman, M.R., Ghosh, M.K. et al. Tropical cyclone intensity forecasting in the Bay of Bengal using a biologically inspired computational model. Model. Earth Syst. Environ. 10, 523–537 (2024). https://doi.org/10.1007/s40808-023-01786-3

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