TY - JOUR KW - Climatology KW - Dynamic linear models KW - Generalised additive models KW - Geophysics/Geodesy KW - Indo-Gangetic plain KW - La Nina KW - Oceanography KW - Western Ghats AU - Jagdish Krishnaswamy AU - Srinivas Vaidyanathan AU - Balaji Rajagopalan AU - Mike Bonell AU - Mahesh Sankaran AU - R.S. Bhalla AU - Shrinivas Badiger AB -

The El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are widely recognized as major drivers of inter-annual variability of the Indian monsoon (IM) and extreme rainfall events (EREs). We assess the time-varying strength and non-linearity of these linkages using dynamic linear regression and Generalized Additive Models. Our results suggest that IOD has evolved independently of ENSO, with its influence on IM and EREs strengthening in recent decades when compared to ENSO, whose relationship with IM seems to be weakening and more uncertain. A unit change in IOD currently has a proportionately greater impact on IM. ENSO positively influences EREs only below a threshold of 100 mm day-1. Furthermore, there is a non-linear and positive relationship between IOD and IM totals and the frequency of EREs (>100 mm day-1). Improvements in modeling this complex system can enhance the forecasting accuracy of the IM and EREs.

DA - 08/2014 LA - eng N2 -

The El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are widely recognized as major drivers of inter-annual variability of the Indian monsoon (IM) and extreme rainfall events (EREs). We assess the time-varying strength and non-linearity of these linkages using dynamic linear regression and Generalized Additive Models. Our results suggest that IOD has evolved independently of ENSO, with its influence on IM and EREs strengthening in recent decades when compared to ENSO, whose relationship with IM seems to be weakening and more uncertain. A unit change in IOD currently has a proportionately greater impact on IM. ENSO positively influences EREs only below a threshold of 100 mm day-1. Furthermore, there is a non-linear and positive relationship between IOD and IM totals and the frequency of EREs (>100 mm day-1). Improvements in modeling this complex system can enhance the forecasting accuracy of the IM and EREs.

PY - 2014 EP - 1–10 T2 - Climate Dynamics TI - Non-stationary and non-linear influence of ENSO and Indian Ocean Dipole on the variability of Indian monsoon rainfall and extreme rain events UR - http://link.springer.com/article/10.1007/s00382-014-2288-0 SN - 0930-7575, 1432-0894 ER -