Analysing Predictability in Indian Monsoon Rainfall: A Data Analytic Approach

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• 作者：Sarita Azad ; Shoubhik Debnath ; M. Rajeevan
• 关键词：Indian monsoon ; Prediction ; Time series ; Wavelets ; Artificial neural networks
• 刊名：Environmental Processes
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：2
• 期：4
• 页码：717-727
• 全文大小：880 KB
• 参考文献：Annamalai H (1995) Intrinsic problems in the seasonal prediction of the Indian summer monsoon rainfall. Meteorol Atmos Phys 55:61鈥?6CrossRef
  Azad S, Narasimha R, Sett SK (2007) Multiresolution analysis for separating closely spaced frequencies with an application to Indian monsoon rainfall data. Int J Wavelets Multiresolution Inf Process 5:735鈥?52CrossRef
  Azad S, Narasimha R, Sett SK (2008) A wavelet based significance test for periodicities in Indian monsoon rainfall. Int J Wavelets Multiresolution Inf Process 6:291鈥?04CrossRef
  Azad S, Vignesh T, Narasimha R (2010) Periodicities in Indian monsoon rainfall over spectrally homogeneous regions. Int J Climatol 30:2289鈥?298CrossRef
  Bhakar SR, Singh R, Hari R (2006) Stochastic modeling of wind speed at Udaipur. Indian J Agril Eng 43(1):1鈥?
  Dabral PP, Pandey A, Baithuri N, Mal BC (2008) Stochastic modeling of rainfall in humid region of northeast India. Water Resour Manag 22:1395鈥?407
  Gilman DL, Fuglister FG, Mitchell JJ (1963) On the power spectrum of 鈥淩ed noise鈥? J Atmos Sci 20:182鈥?84CrossRef
  Guhathakurta P (2006) Long-Range Monsoon Rainfall Prediction of 2005 for the Districts and Sub-Division Kerala with Artificial Neural Network. Curr Sci 90(6):773鈥?79
  Iyengar RN, Kanth STG (2004) Intrinsic mode functions and a strategy for forecasting Indian monsoon rainfall. Meteorol Atmos Phys 90:17鈥?6CrossRef
  Keppenne CL, Ghil M (1992) Adaptive spectral analysis and prediction of the Southern Oscillation Index. J Geophys Res 97:20449鈥?0454CrossRef
  Kishtawal CM, Basu S, Patadia F, Thapliyal PK (2003) Forecasting summer monsoon rainfall over India using genetic algorithm. Geophys Res Lett 30(23):2203鈥?207CrossRef
  Maheswaran R, Khosa R (2014) A wavelet-based second order nonlinear model for forecasting monthly rainfall. Water Resour Manag 28(15):5411鈥?431CrossRef
  Michaelides SC, Pattichis CS, Kleovoulou G (2001) Classification of rainfall variability by using artificial neural networks. Int J Climatol 21:1401鈥?414CrossRef
  Narasimha R, Bhattacharyya S (2010) A wavelet cross-spectral analysis of solar鈥揈NSO鈥?rainfall connections in the Indian monsoons. Appl Comput Harmon Anal 28:285鈥?95CrossRef
  Narasimha R, Kailas SV (2001) A wavelet map of monsoon variability. Proc Indian Natl Sci Acad 67A:327鈥?41
  Narsimlu B, Gosain AK, Chahar BR, Singh SK, Srivastava PK (2015) SWAT Model Calibration and Uncertainty Analysis for Streamflow Prediction in the Kunwari River Basin, India, Using Sequential Uncertainty Fitting. Environ Process 2:64. doi:10.鈥?007/鈥媠40710-015-0064-8 CrossRef
  Parthasarathy B, Rupa Kumar K, Munot AA (1995) Homogeneous regional summer monsoon rainfall over India: Interannual variability and teleconnections. RR No: 070
  Rajeevan M, Guhathakurta P, Thapliyal V (2000) New models for long range forecasts of summer monsoon rainfall over Northwest and Peninsular India. Meteorol Atmos Phys 73:211鈥?25CrossRef
  Rajeevan M, Pai DS, Dikshit SK, Kelkar RR (2004) IMD鈥檚 new operational models for long range forecast of south-west monsoon rainfall over India and their verification for 2003. Curr Sci 86:422鈥?31
  Rajeevan M, Pai DS, Anil Kumar R, Lal B (2007) New statistical models for long range forecasting of southwest monsoon rainfall over India. Clim Dyn 28:813鈥?28CrossRef
  Rajkumar KN, Kumar D (2004) Stochastic modeling of daily rainfall for south west monsoon season of Baptla, Andhra Pradesh. Indian J Agril Engg 41(3):41鈥?5
  Ramana RV, Krishna B, Kumar SR, Pandey NG (2013) Monthly rainfall prediction using wavelet neural network analysis. Water Resour Manag 27:3697鈥?711CrossRef
  Rangarajan GK (1994) Singular spectral analysis of homogeneous Indian monsoon (HIM) rainfall. Proc Indian Acad Sci (Earth Planet Sci) 103(4):439鈥?48
  Sahay RR, Srivastava A (2014) Predicting monsoon floods in rivers embedding wavelet transform, genetic algorithm and neural network. Water Resour Manag 28:301鈥?17CrossRef
  Sehgal V, Sahay RR, Chatterjee C (2014) Effect of utilization of discrete wavelet components on flood forecasting performance of wavelet based ANFIS Models. Water Resour Manag 28(6):1733鈥?749CrossRef
  Shukla J, Mooley DA (1987) Empirical prediction of the summer monsoon rainfall over India. Monthly Weather Rev 117:695鈥?03CrossRef
  Stoica P and Moses RL (1997) Introduction to Spectral Analysis, Prentice Hall, Upper Saddle River, NJ
  Vautard R, Yiou P, Ghil M (1992) Singular spectrum analysis: A toolkit for short, noisy and chaotic series. Physica D 58:95鈥?26CrossRef
  Yao CS (1983) Fitting a linear autoregressive model for long-range forecasting. Monthly Weather Rev 111:692鈥?00CrossRef
  
• 作者单位：Sarita Azad (1)
  Shoubhik Debnath (1)
  M. Rajeevan (2)
  
  1. Indian Institute of Technology Mandi, Mandi, 75001, Himachal Pradesh, India
  2. Indian Institute of Tropical Meteorology, Dr Homi Bhabha Road, Pashan, Pune, 411 008, India
  
• 刊物类别：Environmental Science and Engineering; Environmental Management; Waste Management/Waste Technology;
• 刊物主题：Environmental Science and Engineering; Environmental Management; Waste Management/Waste Technology; Water Quality/Water Pollution;
• 出版者：Springer International Publishing
• ISSN：2198-7505

文摘

This paper examines monthly and annual data to analyse predictability in the Indian monsoon rainfall. The periodic structure in the time series data is extracted using wavelets and the residual random part is separately modeled using artificial neural networks (ANN). Although wavelet and neural network based hybrid techniques have been widely applied in the recent years, the present approach has not been investigated so far. Our results show that the estimated periodic and random components comprise 30 and 15 %, respectively, variance of the total rainfall in case of annual data, whereas the model explains 93 % of variance in case of monthly data. It is shown that the prediction is more accurate when periodic and random parts are treated separately. Keywords Indian monsoon Prediction Time series Wavelets Artificial neural networks