Iyengar, RN and Kanth, Raghu STG (2005) Intrinsic mode functions and a strategy for forecasting Indian monsoon rainfall. In: Meteorology and Atmospheric Physics, 90 (1-2). pp. 17-36.
Indian monsoon rainfall data is shown to be decomposable into six empirical time series, called intrinsic mode functions. This helps one to identify the first empirical mode as a nonlinear part and the remaining as the linear part of the data. The nonlinear part is handled by artificial neural network (ANN) techniques, where as the linear part is amenable for modeling through simple regression concepts. It is found that the proposed model explains between 75 to 80% of the inter annual variability (IAV) of eight regional rainfall series considered here. The model is efficient in statistical forecasting of rainfall as verified on an independent subset of the data series. It is demonstrated that the model is capable of foreshadowing the drought of 2002, with the help of only antecedent data. The statistical forecast of All India rainfall for the year of 2004 is 80.34 cms with a standard deviation of 3.3 cms. This expected value is 94.25% of the longterm climatic average.
|Item Type:||Journal Article|
|Additional Information:||Copyright for this article belongs to Springer Wien.|
|Department/Centre:||Division of Mechanical Sciences > Civil Engineering
Division of Mechanical Sciences > Centre for Atmospheric & Oceanic Sciences
|Date Deposited:||10 Oct 2005|
|Last Modified:||19 Sep 2010 04:20|
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