Assessment of temporal change in the tails of probability distribution of daily precipitation over India due to climatic shift in the 1970s

Daily precipitation extremes are crucial in the hydrological design of major water control structures and are expected to show a changing tendency over time due to climate change. The magnitude and frequency of extreme precipitation can be assessed by studying the upper tail behavior of probability...

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Autores principales: Neha Gupta, Sagar Rohidas Chavan
Formato: article
Lenguaje:EN
Publicado: IWA Publishing 2021
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Acceso en línea:https://doaj.org/article/d1949cabdc324fafa5cf01974df80e8b
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Sumario:Daily precipitation extremes are crucial in the hydrological design of major water control structures and are expected to show a changing tendency over time due to climate change. The magnitude and frequency of extreme precipitation can be assessed by studying the upper tail behavior of probability distributions of daily precipitation. Depending on the tail behavior, the distributions can be classified into two categories: heavy-tailed and light-tailed distributions. Heavier tails indicate more frequent occurrences of extreme precipitation events. In this paper, we have analyzed the temporal change in the tail behavior of daily precipitation over India from pre- to post-1970 time periods as per the global climatic shift. A modified Probability Ratio Mean Square Error norm is used to identify the best-fit distribution to the tails of daily precipitation among four theoretical distributions (e.g., Pareto-type II, Lognormal, Weibull, and Gamma distributions). The results indicate that the Lognormal distribution, which is a heavy-tailed distribution, fits the tails of daily precipitation for the majority of the grids. It is inferred from the study that there is an increase in the heaviness of tails of daily precipitation data over India from pre- to post-1970 time periods. HIGHLIGHTS This paper attempts to assess the changes in the tail behavior of daily precipitation over India due to climatic shift in the 1970s.; Maps show best-suited probability distributions for pre-/post-1970s and highlight the changes.; Results highlight the use of heavy-tailed probability distributions for analyzing the extreme precipitation.; A significant increase in heaviness of tails is noticed from pre- to post-1970 time periods.;