Abstract

With the increasing population in the region, quantification of global warming impact on the mean and daily extremes of NEI rainfall (NEIR) is crucial for food security and preservation of the region’s biodiversity hotspot. Here, using a long (~ 200 years) record of seasonal mean NEIR, we separate oscillatory modes of variability from the secular trend using the improved ensemble empirical mode decomposition (ICEEMD). The long-term change in seasonal mean rainfall over NEI estimated from this nonlinear trend is unbiased by the oscillatory modes and leads to a climate sensitivity of − 3.2 ± 1.65%/K. A similar estimate of the impact on daily rainfall extremes, however, has been lacking due to the absence of long daily rainfall data on a sufficiently large number of fixed stations. Toward this end, a 90-year-long daily rainfall data based on 24-well-distributed fixed stations over NEI is constructed through a data mining effort. Even as the seasonal mean decreases, our estimate indicates that the frequency of occurrence of daily extremes (exceeding 99.5 percentile) over the NEI is increasing at + 51 ± 4.99 %/K while the intensity is increasing at + 12.5 ± 3.32%/K over the past century, a rate much faster than envisaged by Clausius-Clapeyron scaling. In contrast to a significant multi-decadal variability (MDV) of summer rainfall over the rest of India, we find that the MDV of NEIR is weak and indistinguishable from white noise. As on inter-annual time scale, however, it indicates that the NEIR tends to go out of phase with that over the rest of India even on multi-decadal and longer time scales, with significant implications on interpreting past rainfall reconstruction from caves in the NEI. Our findings suggest that vulnerability to meso-scale hydrological disasters over the NEI in the coming years is much higher than that over the rest of India.

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