Assessing daily precipitation tails over India under changing climate

Daily precipitation extremes are crucial in the hydrological design of major water control structures. The extremes are usually present in the upper part of the probability distribution of daily precipitation data, known as the tail. The distributions are bifurcated into heavy or light-tailed distributions depending on the tail. Heavy tails signify a higher frequency of occurrences of extreme precipitation events. Prediction of extreme precipitation depends on reliable modelling of the tail. Tail behaviour can be studied by graphical as well as threshold-based fitting approaches; however, each approach has associated shortcomings. In this work, we utilize a versatile and simple empirical index known as the “Obesity Index” (OB) to assess the tail of probability distributions of daily gridded precipitation data for India. This comprehensive regional analysis has been undertaken to quantify the tail heaviness of 4801 daily precipitation records over India for historical (1970–2019) and future (2020–2100) time periods. Future projections of daily precipitation are downscaled from the latest generation of climate models knowns as Coupled Model Intercomparison Project Phase 6 (CMIP6) under different emission scenarios. Finally, the application of the OB-based approach is extended to characterize daily precipitation in Indian Meteorological Subdivisions. Results indicate the applicability of heavy-tailed distributions in representing daily precipitation over India and establish the utility of the OB-based approach in diagnosing tail behaviour. Also, the spatial patterns of the tail heaviness are found to be matching with the Köppen–Geiger climate classification of India. The findings from this can be an input for the policymakers to develop adaptation strategies in response to the projected climate change impact.

Keywords: Extreme precipitation, Climate Change, India, Obesity index, Tail heaviness