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

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dc.contributor.author Gupta, N.
dc.contributor.author Chavan, S.R.
dc.date.accessioned 2022-08-22T18:24:37Z
dc.date.available 2022-08-22T18:24:37Z
dc.date.issued 2022-08-22
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/3866
dc.description.abstract 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. en_US
dc.language.iso en_US en_US
dc.subject Daily precipitation extremes en_US
dc.subject Global climatic shift en_US
dc.subject Heavy-tailed distribution en_US
dc.subject Light-tailed distribution en_US
dc.title Assessment of temporal change in the tails of probability distribution of daily precipitation over india due to climatic shift in the 1970s en_US
dc.type Article en_US


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