Author(s): Riya Dutta; Subhasmita Dash; Rajib Maity

Linked Author(s): Riya Dutta, Rajib Maity

Keywords: Extreme rainfall event; Large-scale indices; Trend Analysis; Temporal Networks

Abstract: It is well-established that climate change has significantly altered the global hydrological cycle leading to change in climate extremes. Understanding the changes in the characteristics of extremes and their possible driving mechanisms is essential to support the efforts towards reducing their impacts. In this study, a rainfall intensity based extreme event index is developed and the spatio-temporal variation of such extremes is analyzed during the period of 1901-2019. The entire time-period is divided into multiple epochs and trend analysis is carried out using the Mann-Kendall method to identify the regions exhibiting a statistically significant change in the extreme rainfall intensity. Next, the temporal change in the association between large scale coupled atmospheric-oceanic circulations, namely El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), and the extreme rainfall events are analyzed using a recently developed temporal network based approach. This approach provides a complete conditional independence structure among the variables, also referred to network structures. These network structures are updated after a fixed time-interval to obtain a series of networks called temporal networks, which provides the time-varying association among the variables. The results indicate significant change in the intensity of extreme rainfall events for almost all parts of the country. Furthermore, the association between the lagged information of ENSO and IOD changes with time in terms of its spatial pattern and the strength of association.

DOI: https://doi.org/10.3850/IAHR-39WC2521711920221372

Year: 2022