QUIDIC-RD4

Already today extreme weather events place a huge burden on regional and national economies, e.g. through damages to buildings and infrastructure from tropical cyclones,floods or wildfires, and agricultural production failures from droughts and heatwaves. While the frequency and intensity of the weather events is already changing due to anthropogenic greenhouse gas emissions, the contribution of climate change to reported variations in direct and indirect economic damages is still largely unknown and not systematically separated from the influence of direct human drivers such as changes in population patterns or economic development. Future warming is expected to further change the frequency and intensities of extreme weather events across categories. Associated societal impacts will develop from the temporal and spatial interplay of events, e.g. by not leaving enough time for recovery between subsequent events or accumulating responses along global supply chains. So far, reported national time series of direct annual losses have not been extended into the future in a cross-sectoral consistent way resolving individual events. Existing analyses therefore can not fully address societally relevant questions on the effects of compound impacts or exceedance of coping capacities through subsequent disasters. QUIDIC assesses past and future economic impacts of extreme weather events through process-based impact simulations within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP, www.isimip.org). We constrain our assessment with observations. Based on historical simulations (ISIMIP project phases: 2a and 3a) we develop a better understanding of the effect of climate change versus other direct human influences on observed trends in hazard indicators such as areas affected by flooding in WP1. In WP2 hazard- and socio-economic indicators are combined and assessed against reported direct economic damages to calibrate functional relations between hazards, exposure, vulnerability and damages. These damage functions are applied as a powerful tool to systematically attribute historical variations in reported damage time series. In addition, the calibrated damage functions are used to provide damage projections along climate projections and socio-economic storylines within the Representative Concentration Pathway (RCP) - Shared Socioeconomic Pathway (SSP) scenario framework (O’Neill et al. 2014, 2017) and associated bio-physical impact indicators derived from ISIMIP2b/3b. In WP3 direct damage projections from WP1 and WP2 are used to explore indirect economic damages through disaster induced supply-failures. We assess climate risks for the production system and vulnerable consumers including potentially regressive distributional effects such as scarcity-driven price increases, which place a proportionally larger burden on poorer parts of the population. Income-sensitive metrics enable us to identify hot-spot countries, where economic structures and/or vulnerable low-income populations are particularly exposed to climate risks from extreme weather events. Our approach covers the major categories of extreme-weather-induced damages on global scale and provides critical knowledge about economic risks related to aggregated damages.