Modelling of Compound Drought-Temperature Extreme Event Framework: A Multi-Decadal Perspective

Compound events are the extreme weather and climate events that result from a combination of physical processes (climatic drivers and extreme events) occurring across different temporal (successive) and spatial (simultaneous) scales. Further, multiple drivers with a complex chain of processes, conditional dependencies and extreme return periods of such events lead to severe socio-economic and environmental impacts. The quantification and predictions of such extreme events still need to be advanced with changing climate and global warming. In previous literature, it is documented that precipitation and temperature are the fundamental drivers of different climatic variations resulting in compound extreme events. In light of these perspectives, a Standardized Compound Extreme Event Index (SCEEI) is modelled in this study integrating the joint properties of Standardized Precipitation Index (SPI) and Standardized Temperature Index (STI) that are derived from precipitation and temperature; respectively employing the India Meteorological Department (IMD) data series. The Gaussian model-based multivariate technique is applied to derive SCEEI. The severity of drought and extreme temperature at an annual scale is analysed using SCEEI for two neighbouring river basins of Eastern India, i.e. Brahmani and Baitarani river basins for the study period of 1979-2018. The variations of the extreme events and their severity are further assessed at a multi-decadal scale. The trends of these compound events for different time scales are checked by the Mann-Kendall test followed by Sen’s slope estimator. The multi-decadal time scale is divided as D¹ (1979-1988), D² (1989-1998), D³ (1999-2008), and D⁴ (2009-2018). It is observed that SCEEI captures drought events along with extreme temperatures reasonably well than the individual index (SPI and STI). The outcomes of this study conclude that the multivariate approach is a reliable perspective to assess the severity of compound extreme events. The developed approach in this study is novel for monitoring the compound extreme event severity under the non-availability basin-scale hydrological data that is advantageous for several worldwide data scare river basins to purpose an adaptation strategy and achieve the Sustainable Development Goals (SDGs).

Keywords: Compound events; SCEEI; IMD; multi-decadal; Brahmani; Baitarani; SDGs