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Seasonal prediction of tropical cyclone activity over the north Indian Ocean using three artificial neural networks

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Abstract

Three artificial neural network (ANN) methods, namely, multilayer perceptron (MLP), radial basis function (RBF) and generalized regression neural network (GRNN) are utilized to predict the seasonal tropical cyclone (TC) activity over the north Indian Ocean (NIO) during the post-monsoon season (October, November, December). The frequency of TC and large-scale climate variables derived from NCEP/NCAR reanalysis dataset of resolution 2.5° × 2.5° were analyzed for the period 1971–2013. Data for the years 1971–2002 were used for the development of the models, which were tested with independent sample data for the year 2003–2013. Using the correlation analysis, the five large-scale climate variables, namely, geopotential height at 500 hPa, relative humidity at 500 hPa, sea-level pressure, zonal wind at 700 hPa and 200 hPa for the preceding month September, are selected as potential predictors of the post-monsoon season TC activity. The result reveals that all the three different ANN methods are able to provide satisfactory forecast in terms of the various metrics, such as root mean-square error (RMSE), standard deviation (SD), correlation coefficient (r), and bias and index of agreement (d). Additionally, leave-one-out cross validation (LOOCV) method is also performed and the forecast skill is evaluated. The results show that the MLP model is found to be superior to the other two models (RBF, GRNN). The (MLP) is expected to be very useful to operational forecasters for prediction of TC activity.

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Acknowledgments

The authors are grateful to the Director General of Meteorology, India Meteorological Department, New Delhi, for providing all the facilities to carry out this research work. The authors acknowledge the use of NCEP data in this research work. The authors are also grateful to the anonymous reviewers for their suggestions for improvement of the paper.

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Authors and Affiliations

  1. India Meteorological Department, Mausam Bhavan, Lodi Road, New Delhi, 110003, India

    Sankar Nath & S. D. Kotal

  2. Department of Mathematics, Jadavpur University, Kolkata, 700032, India

    P. K. Kundu

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  1. Sankar Nath
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  2. S. D. Kotal
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  3. P. K. Kundu
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Correspondence to Sankar Nath.

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Responsible Editor: J. T. Fasullo.

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Nath, S., Kotal, S.D. & Kundu, P.K. Seasonal prediction of tropical cyclone activity over the north Indian Ocean using three artificial neural networks. Meteorol Atmos Phys 128, 751–762 (2016). https://doi.org/10.1007/s00703-016-0446-0

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