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Analyzing the complex behavior of extreme precipitation events is essential for a better understanding of the effects of climate change on water resources and for forecasting extreme hydrologic events. In this study, complex network concepts are applied to investigate the synchronization patterns of extreme daily precipitation events across India, with an evaluation of how these patterns may vary in the future. Daily rainfall data provided by the India Meteorological Department (IMD) for the period 1961-2020 at a spatial resolution of 0.250.25 are used to investigate the synchronization patterns of extreme rainfall during the historical period. To assess synchronization patterns in the future, rainfall projections from selected General Circulation Models under different Shared Socio-Economic Pathway Scenarios are employed. A day with precipitation greater than 1 mm is considered a wet day, and a wet day is then classified as an extreme precipitation event only if its precipitation exceeds the 95th percentile of all wet days. For the construction of the network, each grid is considered as a node, and the connections between them are identified using the event synchronization method. Both historical and future precipitation networks are analyzed for two different seasons: (i) Summer (June, July, August, and September); and (ii) Winter (December, January, and February). Two network measures, namely degree centrality and clustering coefficient, are determined for these networks. Changes in network measures, relative to the baseline period of 19612020, are analyzed across three different timeframes: the 2020s, 2040s, and 2070s. The findings from the network measures can reveal crucial geographic locations in terms of their connection patterns to other areas for both seasons.
Deepthi et al. (Fri,) studied this question.