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    Simple multiple regression model for long range forecasting of Indian summer monsoon rainfall

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    Meteorol_Atmos_Phys_99_17.pdf (469.9Kb)
    Date
    2008
    Author
    Sadhuram, Y.
    Murthy, T.V.R.
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    Abstract
    The relationship between the Indian Ocean Sea-Surface Temperature Anomalies (SSTA) and the Indian Summer Monsoon Rainfall (ISMR) have been examined for the period, 1983-2006. High and positive correlation (0.51; significant at greater than 99% level) is noticed between ISMR and SSTA over southeastern Arabian Sea (AS) in the preceding January. Significant and positive correlation (0.61: significant at greater than 99% level) is also observed with the SSTA over northwest of Australia (NWA) in the preceding February. The combined SSTA index (AS+NWA) showed a very high correlation of 0.71 with the ISMR. The correlation between East Asia sea-level pressure (average during February and March in the region, 35 degrees N-45 degrees N; 120 degrees E-130 degrees E) and ISMR is found to be 0.62. The multiple correlation using the above two parameters is 0.85 which explains 72% variance in ISMR. Using the above two parameters a linear multiple regression model to predict ISMR is developed. The results are comparable with those obtained from the power regression (developed with 16, 8 and 10 parameters) and ensemble models (using 3 to 6 parameters) of the Indian Meteorological Department (IMD) (Rajeevan et al. 2004; 2006). The rainfall during 2002 and 2004 could be predicted accurately from the present model. It is well known fact that most of the dynamical / statistical methods failed to predict the rainfall in 2002. However, as for associations between SST and ISMR, the index is quite susceptible to inter decadal fluctuations and markedly reduced skill is found in the decades preceding 1983. The RMS error for 24 years is 5.56 (% of long period average, LPA) and the correlation between the predicted and observed rainfall is 0.79
    URI
    http://drs.nio.org/drs/handle/2264/1042
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