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Climate Dynamics

, Volume 42, Issue 9–10, pp 2271–2285 | Cite as

The influence of stochasticism on Indian summer monsoon rainfall and its impact on prediction

  • B. G. HuntEmail author
Article

Abstract

Output from a multi-millennial control simulation of the CSIRO Mark 2 coupled model has been used to investigate quantitatively the relation between the Indian summer monsoon rain and El Nino/Southern Oscillation events. A moving window correlation between these two features revealed marked interannual and multi-decadal variability with the correlation coefficient varying between −0.8 and +0.2. This suggests that current observations showing a decline in this correlation are due to natural climatic variability. A scatter diagram of the anomalies of the Indian summer monsoon rainfall and NINO 3.4 surface temperature showed that in almost 40 % of the cases ENSO events were associated with rainfall anomalies opposite to those implied by the climatological correlation coefficient. Case studies and composites of global distributions of surface temperature and rainfall anomalies for El Nino (or La Nina) events highlight the opposite rainfall anomalies over India that can result from very similar ENSO surface temperature anomalies. Composite differences are used to demonstrate the unique sensitivity of Indian summer monsoon rainfall anomalies to ENSO events. The problem of predicting such anomalies is discussed in relation to the fact that time series of the monsoon rainfall, both observed and simulated, consist of white noise. Based on the scatter diagram it is concluded that in about 60 % of the cases seasonal or annual prediction of monsoon rainfall based on individual ENSO events will result in the correct outcome. Unfortunately, there is no way, a priori, of determining for a given ENSO event whether the correct or a rogue prediction will result. Analysis of the present model’s results suggest that this is an almost world-wide problem for seasonal predictions of rainfall.

Keywords

Indian summer rainfall Stochastic influences Climatic model Multi-millennial simulation 

Notes

Acknowledgments

It is a particular pleasure to thank Martin Dix for his assistance with technical aspects of the figures and analysis.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.CSIRO Marine and Atmospheric ResearchAspendaleAustralia

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