Climate projections of spatio-temporally compound extreme events (floods and droughts) using a multivariate drought index

The compound occurrence of two extremes of the hydrological spectrum (droughts and floods) either in space and/or time, could aggravate the associated socio-economic impacts with respect to those caused by the individual extreme event. Both extreme events share the potentially linked driving mechanisms and interconnected characteristics, therefore the better understanding of the dependence structures of the contributing variables is essential to avoid the underestimation of the possible risks of compound hazards. To this end, the present study focusses on spatio-temporally compound extreme events under a changing climate and identify/locate the most vulnerable hotspots in the Upper Jhelum Basin (South Asia), paving the way for adaptation and mitigation measures. Climate models are the main tools to assess climate projections and, particularly, to provide relevant information for sectoral applications. They often present systematic biases, thus some sort of bias adjustment is performed in impact assessments. The framework of the present study is two-fold: (i) evaluation of bias correction (BC) of climate model historical simulations and (ii) projection of extreme compound events in the near future (2040-2059) and far future (2080-2099) for three different Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Droughts and floods are characterized by using a multivariate drought index (namely the Standardized Precipitation Evapotranspiration Index, SPEI), which is derived from daily precipitation (P) and maximum (Tmax) and minimum temperatures (Tmin). In the first step, the intercomparison of different state-of-the-art BC methods (uni- and multi-variate) and BC approaches (direct and component-wise) for climate model simulations stemming from different experiments (CMIP6, CORDEX -WAS-44- and CORDEX CORE -WAS-22) is performed following a multivariate framework. The added value/performance of BC and climate model simulations is examined in terms of inter-variable physical coherence of involved key essential variables (P, Tmax and Tmin) and characteristics of extreme events (duration, severity, intensity, and frequency of floods and droughts) during the historical period. In the second step, projected changes in the extreme events characteristics and their compounding in space and time are analyzed for the near and far future under all available scenarios. Climate projections of this kind of extreme events, spanning different scenarios and other sources of uncertainty is essential to better implement adaptation and mitigation solutions that can help reduce the negative impacts of climate change.