Skip to main content
SpringerLink
Log in

Prediction of all India summer monsoon rainfall using error-back-propagation neural networks

  • Published:
Meteorology and Atmospheric Physics Aims and scope Submit manuscript

Summary

In this paper, multilayered feedforward neural networks trained with the error-back-propagation (EBP) algorithm have been employed for predicting the seasonal monsoon rainfall over India. Three network models that use, respectively, 2, 3 and 10 input parameters which are known to significantly influence the Indian summer monsoon rainfall (ISMR) have been constructed and optimized. The results obtained thereby are rigorously compared with those from the statistical models. The predictions of network models indicate that they can serve as a potent tool for ISMR prediction.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Banerjee, A. K., Sen, P. N., Raman, C. R. V., 1978: On foreshadowing southwest monsoon rainfall over India with midtropospheric circulation anomaly of April.Indian J. Meteorol. Hydrol. Geophys.,29, 425–431.

    Google Scholar 

  • Basu, S., Andharia, H. I., 1992: The chaotic time series of Indian monsoon rainfall and its prediction.Proc. Indian. Acad. Sci. (Earth Planet. Sci.),101, 27–34.

    Google Scholar 

  • Beale, R., Jackson, T., 1990:Neural Computing: An Introduction, Bristol, UK: Adam Hilger.

    Google Scholar 

  • Bhalme, H. N., Jadhav., S. K., Mooley, D. A., Ramana Murty, Bh V, 1986: Forecasting of monsoon performance over India.J. Climatol.,6, 347–354.

    Google Scholar 

  • Bishop, C. M., 1994: Neural Network and their applicationsRev. Sci. Instr.,65, 1803–1832.

    Google Scholar 

  • Blanford, H. F., 1884: On the connection of the Himalaya snowfall with dry winds and seasons of droughts in India.Proc. Roy. Soc. London,37, 3.

    Google Scholar 

  • Chen, S., Billings, S. A., 1992: Neural networks for nonlinear dynamic system modelling and identification.Int. J. Control. 56, 319–346.

    Google Scholar 

  • Derr, V. E., Slutz, R. J., 1994: Prediction of El-Nino events in the Pacific by means of neural networks.AI Applications,8, 51–63.

    Google Scholar 

  • Dugam, S. S., Kakade, S. B., Verma, R. K., 1993: A new predictor for long-range forecasting of Indian summer monsoon.Vatavaran,15, 6–9.

    Google Scholar 

  • Elliot, W. P., Angell, J. K., 1987: The relation between Indian monsoon rainfall, the southern oscillation, and hemispheric air and sea temperature 1884–1984.J. Climate Appl. Meteor.,26, 943–948.

    Google Scholar 

  • Elliot, W. P., Angell, J. K., 1988: Evidence for changes in Southern Oscillation relationships during the last 100 years.J. Climate,1, 729–737.

    Google Scholar 

  • Elsner, J. B., Tsonis, A. A., 1992: Nonlinear prediction, chaos, and noise,Bull. Amer. Meteor. Soc.,73, 49–60.

    Google Scholar 

  • Freeman, J. A., Skapura, D. M., 1991:Neural Networks: Algorithms, Applications and Programming Techniques. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Fu, C., Fletcher, J., 1988: Large signals of climatic variations over the ocean in the Asian monsoon region.Adv. Atmos. Sci.,5, 389–404.

    Google Scholar 

  • Goswami, P., Srividya, 1996: A novel neural network design for long-range prediction of rainfall pattern.Curr. Sci.,70, 447–457.

    Google Scholar 

  • Gowariker, V., Thapliyal, V., Sarkar, R. P., Mandal, G. S., Sikka, D. R., 1989: Parametric and power regression models: New approach to long range forecasting of monsoon rainfall in India.Mausam,40, 115–122.

    Google Scholar 

  • Gowariker, V., Thapliyal, V., Kulashrestha, S. M., Mondal, G. S., Sen Roy, N., Sikka, D. R., 1991: A power regression model for long range forecast of southwest monsoon rainfall over India.Mausam,42, 125–130.

    Google Scholar 

  • Grieger, B., Latif, M., 1994: Reconstruction of the El-Nino attractor with Neural Networks.Clim. Dyn.,10, 267–276.

    Google Scholar 

  • Hastenrath, S., 1986: On climate prediction in the Tropics.Bull. Amer. Meteor. Soc.,67, 696–702.

    Google Scholar 

  • Hastenrath, S., 1987: On the prediction of Indian Monsoon Rainfall anomalies.J. Climate Appl. Meteor.,26, 847–857.

    Google Scholar 

  • Hastenrath, S., 1995: Recent advances in tropical climate prediction.J. Climate,8, 1519–1532.

    Google Scholar 

  • Haykin, S., 1994:Neural Networks: A Comprehensive Foundation, New York: Macmillan.

    Google Scholar 

  • Hecht-Nielsen, R., 1990:Neurocomputing. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Huang, S. C., Huang, Y. F., 1991: Bounds on the number of hidden neurons in multilayer perceptrons.IEEE Transactions on Neural Networks,2, 47–55.

    Google Scholar 

  • Krishna Kumar, K., Rupakumar, K., Pant, G. B., 1992: Premonsoon ridge location over India and its relation to monsoon rainfall.J. Climate,5, 979–986.

    Google Scholar 

  • Krishna Kumar, K., Rupakumar K., Pant, G. B., 1995: Premonsoon maximum/minimum temperatures over India in relation to the summer monsoon rainfall (Unpublished, copy available from the authors.)

  • Lippmann, R. P., 1987: An introduction to computing with neural nets.IEEE ASSP Mag.,4, 4–22.

    Google Scholar 

  • McCann, D. W., 1992: A neural network short-term forecast of significant thunderstorms.Weather and Forecasting,7, 525–534.

    Google Scholar 

  • Muller, B., Reinhardt, J., 1990:Neural Networks. Berlin: Springer.

    Google Scholar 

  • Minns, A. W., Hall, M. J., 1996: Artificial Neural Networks as rainfall-runoff models.J. Hydrol.,41, 399–417.

    Google Scholar 

  • Mooley, D. A., Parthasarathy, B., 1984: Fluctuations in allindia summer monsoon rainfall during 1871–1978.Climatic Change,6, 287–301.

    Google Scholar 

  • Mooley, D. A., Shukla, J., 1987: Variability and forecasting of the summer monsoon rainfall over India. In: Chang, C. P., Krishnamurti, T. N. (eds.)Monsoon Meteorology. (Oxford monogr. on Geol. and Geophys., No. 7) New York: Oxford University Press, pp. 26–58.

    Google Scholar 

  • Mooley, D. A., Paolino, D. A., 1988: A predictive monsoon signal in the surface level thermal field over India.Mon. Wea. Rev.,116, 339–352.

    Google Scholar 

  • Mooley, D. A., Parthasarathy, B., Pant, G. B., 1986: Relationship between all-india summer monsoon rainfall and location of ridge at 500 mb level along 75° E.J. Climate Appl. Meteor.,25, 633–640.

    Google Scholar 

  • Navone, H. D., Ceccatto, H. A., 1994: Predicting Indian monsoon rainfall: A Neural Network approach.Climate Dynamics,10, 305–312.

    Google Scholar 

  • Parker, D. B., 1982: Learning Logic. Invention Rep. 581–584. Stanford University, CA.

    Google Scholar 

  • Parthasarathy, B., 1984: Interannual and long-term variability of Indian summer monsoon rainfall.Proc. Indian Acad. Sci. (Earth Planet. Sci.) 93, 371–385.

    Google Scholar 

  • Parthasarathy, B., Pant, G. B., 1985: Seasonal relationship between Indian summer monsoon rainfall and Southern Oscillation.J. Climatol.,5, 369–378.

    Google Scholar 

  • Parthasarathy, B., Diaz, H. F., Eischeid, J. K., 1988: Prediction of all-India summer monsoon rainfall with regional and large-scale parameters.J. Geophys. Res.,93/D5, 5341–5350.

    Google Scholar 

  • Parthasarathy, B., Rupakumar, K., Sontakke, N. A., 1990. Surface and upper air temperatures over India in relation to monsoon rainfall.Theor. Appl. Climatol.,42, 93–110.

    Google Scholar 

  • Parthasarathy, B., Rupakumar, K., Munot, A. A., 1991: Evidence of secular variations in Indian monsoon rainfall-circulation relationships.J. Climate 4, 927–938.

    Google Scholar 

  • Parthasarathy, B., Rupakumar, K., Kothawale, D. R., 1992: Indian summer monsoon rainfall indices: 1871–1990.Meteorol. Mag.,12, 174–186.

    Google Scholar 

  • Parthasarathy, B., Rupakumar, K., Munot, A. A., 1993: Homogeneous Indian Monsoon rainfall: Variability and prediction.Proc. Indian Acad. Sci. (Earth Planet. Sci.).102, 121–155.

    Google Scholar 

  • Parthasarathy, B., Munot, A. A., Kothawale, D. R., 1994: All-India monthly and seasonal rainfall series: 1871–1993.Theor. Appl. Climatol.,49, 217–224.

    Google Scholar 

  • Parthasarathy, B., Sontakke, N. A., Munot, A. A., Kothawale, D. R., 1987: Droughts/Floods in the summer monsoon season over different Meteorological subdivisions of India for the period 1871–1984.J. Climatol.,7, 57–70.

    Google Scholar 

  • Peak, J. E., Tag, P. M., 1989: An Expert system approach for prediction of maritime visibility obscuration.Mon. Wea. Rev.,117, 2641–2653.

    Google Scholar 

  • Peak, J. E., Tag, P. M., 1992: Towards automated interpretation of satellite imagery for navy shipboard applications.Bull. Amer. Meteor. Soc.,73, 995–1008.

    Google Scholar 

  • Peak, J. E., Tag, P. M., 1994: Segmentation of satellite imagery using Hierarchical Thresholding and Neural Networks.J. Appl. Meteor.,33, 605–616.

    Google Scholar 

  • Prasad, K. D., 1992: Large-scale features and long-range predictions of the Indian summer monsoon.Ph.D. Thesis, Poona University, Pune, pp. 287.

    Google Scholar 

  • Rumelhart, D. E., Hinton, G. E., Williams, R. J., 1986a:Parallel Distributed Processing, Vol.1, Cambridge, MA: MIT Press, pp. 318–362.

    Google Scholar 

  • Rumelhart, D. E., Hinton, G. E., Williams, R. J., 1986b: Learning representations by back propagating errors.Nature,323, 533–536.

    Google Scholar 

  • Schalkoff, R. J., 1992:Pattern Recognition: Statistical, Structural and Neural approaches. New York: John Wiley.

    Google Scholar 

  • Shukla, J., 1987: Long-range forecasting of monsoons. In: Fein, J. S., Stephens, P. L. (eds.)Monsoons. New York: Wiley and Sons, pp. 523–547.

    Google Scholar 

  • Shukla, J., Paolino, D. A., 1983: The Southern Oscillation and long-range forecasting of the summer monsoon rainfall over India.Mon. Wea. Rev.,111, 1830–1837.

    Google Scholar 

  • Shukla, J., Mooley, D. A., 1987: Empirical prediction of the summer monsoon rainfall over India.Mon. Wea. Rev.,115, 695–703.

    Google Scholar 

  • Tambe, S. S., Kulkarni, B. D., Deshpande, P. B., 1996:Elements of Artificial Neural Networks with Selected Applications in Chemical Engineering and Chemical & Biological Sciences. Louisville: Simulation and Advanced Controls.

    Google Scholar 

  • Tang, B., Flato, G. M., Holloway, G., 1994: A study of Arctic sea ice and sea-level pressure using POP and Neural Network methods.Atmos. Ocean,32, 507–529.

    Google Scholar 

  • Thapliyal, V., 1981: ARIMA model for long-range prediction of monsoon rainfall in Peninsular India.India Meteorological Department Monograph Climatology No. 12/81.

  • Thapliyal, V., 1982: Stochastic dynamic model for longrange prediction of monsoon rainfall in peninsular India.Mausam,33, 399–404.

    Google Scholar 

  • Thapliyal, V., 1990: Large-scale prediction of summer monsoon rainfall over India: Evolution and development of new models.Mausam,41, 339–346.

    Google Scholar 

  • Thomson, A. W. P., 1996: Non-linear predictions of Ap by Activity class and Numerical value.PAGEOPH,146, 163–193.

    Google Scholar 

  • Tong, H., 1990:Nonlinear Time Series: A Dynamic System Approach, Oxford: Clarendon Press.

    Google Scholar 

  • Tsonis, A. A., Elsner, J. B., 1988: The weather attractor over very short time scales.Nature,333, 545–547.

    Google Scholar 

  • Tsonis, A. A., Elsner, J. B., 1989: Chaos, Strange attractors, and weather.Bull. Amer. Meteor. Soc.,70, 14–23.

    Google Scholar 

  • Venkatasubramanian, V., Vaidyanathan, R., Yamamoto, Y., 1990: Process faults detection and diagnosis using neural networks-I. Steady state processes.Compu. Chem. Engng.,14, 699–712.

    Google Scholar 

  • Verma, R. K., 1982: Long-range prediction of monsoon activity: A synoptic diagnostic study.Mausam,33, 35–44.

    Google Scholar 

  • Walker, G. T., 1908: Correlation in seasonal variation of climate (Introduction).Memoirs of India Meteorological Department,20, 117–124.

    Google Scholar 

  • Walker, G. T., 1910: On the meteorological evidence for supposed changes of climate in India. Mem.India Meteorological Department,21, 1–21.

    Google Scholar 

  • Walker, G. T., 1933: Seasonal Weather and its prediction.British Association for Advancement of Science, Rep.103, 25–44. (Reprinted Annual Smithsonian Institute for 1935, 117–138).

  • Wasserman, P. D., 1989:Neural Computing: Theory and Practice. New York: Van Nastrand Reinhold.

    Google Scholar 

  • Werbos, P. J., 1974: Beyond recognition, New tools for prediction and analysis in the behavioral sciences. Ph.D. Thesis, Harvard Univ., Cambridge, MA.

    Google Scholar 

  • Wright, P. B., 1975: An index of the southern oscillation. Climate Research Unit. Rep. No. CRUPR4. University of East Anglia, Norwich, UK, 20 pp.

    Google Scholar 

  • Xu, L., Klasa, S., Yuille, A., 1992: Recent advances on techniques of static feedforward networks with supervised learning.Int. J. Neural System,3, 253.

    Google Scholar 

  • Yoh-Han, Pao, 1989:Adaptive Pattern Recognition and Neural Networks. USA: Addison Wesley.

    Google Scholar 

  • Zhang, M., Scofield, R. A., 1994: Artificial Neural Network techniques for estimating heavy convective rainfall and recognizing cloud mergers from satellite data.Int. J. Remote Sensing, London,15, 3241–3261.

    Google Scholar 

  • Zupan, J., Gasteiger, J., 1993:Neural Networks for Chemists. New York: VCH.

    Google Scholar 

Download references

Author information

Author notes

  1. C. Venkatesan & R. N. Keshavamurty

    Present address: Indian Institute of Tropical Meteorology (IITM), Dr. Homi Bhabha Marg Pashan, 411008, Pune, India

  2. S. D. Raskar, S. S. Tambe & B. D. Kulkarni

    Present address: Chemical Engineering Division, National Chemical Laboratory (NCL), Dr. Homi Bhaba Marg Pashan, 411008, Pune, India

Authors and Affiliations

    Authors
    1. C. Venkatesan
      View author publications

      You can also search for this author in PubMed Google Scholar

    2. S. D. Raskar
      View author publications

      You can also search for this author in PubMed Google Scholar

    3. S. S. Tambe
      View author publications

      You can also search for this author in PubMed Google Scholar

    4. B. D. Kulkarni
      View author publications

      You can also search for this author in PubMed Google Scholar

    5. R. N. Keshavamurty
      View author publications

      You can also search for this author in PubMed Google Scholar

    Rights and permissions

    Reprints and permissions

    About this article

    Cite this article

    Venkatesan, C., Raskar, S.D., Tambe, S.S. et al. Prediction of all India summer monsoon rainfall using error-back-propagation neural networks. Meteorl. Atmos. Phys. 62, 225–240 (1997). https://doi.org/10.1007/BF01029704

    Download citation

    • Received:

    • Revised:

    • Issue Date:

    • DOI: https://doi.org/10.1007/BF01029704

    Keywords

    Search

    Navigation